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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Mon, 19 Nov 2012 07:16:25 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/19/t1353327402zk55jyjczizffg0.htm/, Retrieved Sun, 28 Apr 2024 16:42:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=190472, Retrieved Sun, 28 Apr 2024 16:42:44 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R PD  [Multiple Regression] [] [2012-11-17 11:47:21] [6808ef3204f32b6b44f616bd4c52b0ae]
-   PD      [Multiple Regression] [] [2012-11-19 12:16:25] [00ffffaac852cc6d7cd42123567c45a2] [Current]
- R PD        [Multiple Regression] [] [2012-11-19 16:51:03] [af1abf97761ac0cf7dc5c55ff51240a9] 

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Dataseries X:

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12.3	23	154.25	67.75	36.2	93.1	85.2	94.5	59.0	37.3	21.9	32.0	27.4	17.1
6.1	22	173.25	72.25	38.5	93.6	83.0	98.7	58.7	37.3	23.4	30.5	28.9	18.2
25.3	22	154.00	66.25	34.0	95.8	87.9	99.2	59.6	38.9	24.0	28.8	25.2	16.6
10.4	26	184.75	72.25	37.4	101.8	86.4	101.2	60.1	37.3	22.8	32.4	29.4	18.2
28.7	24	184.25	71.25	34.4	97.3	100.0	101.9	63.2	42.2	24.0	32.2	27.7	17.7
20.9	24	210.25	74.75	39.0	104.5	94.4	107.8	66.0	42.0	25.6	35.7	30.6	18.8
19.2	26	181.00	69.75	36.4	105.1	90.7	100.3	58.4	38.3	22.9	31.9	27.8	17.7
12.4	25	176.00	72.50	37.8	99.6	88.5	97.1	60.0	39.4	23.2	30.5	29.0	18.8
4.1	25	191.00	74.00	38.1	100.9	82.5	99.9	62.9	38.3	23.8	35.9	31.1	18.2
11.7	23	198.25	73.50	42.1	99.6	88.6	104.1	63.1	41.7	25.0	35.6	30.0	19.2
7.1	26	186.25	74.50	38.5	101.5	83.6	98.2	59.7	39.7	25.2	32.8	29.4	18.5
7.8	27	216.00	76.00	39.4	103.6	90.9	107.7	66.2	39.2	25.9	37.2	30.2	19.0
20.8	32	180.50	69.50	38.4	102.0	91.6	103.9	63.4	38.3	21.5	32.5	28.6	17.7
21.2	30	205.25	71.25	39.4	104.1	101.8	108.6	66.0	41.5	23.7	36.9	31.6	18.8
22.1	35	187.75	69.50	40.5	101.3	96.4	100.1	69.0	39.0	23.1	36.1	30.5	18.2
20.9	35	162.75	66.00	36.4	99.1	92.8	99.2	63.1	38.7	21.7	31.1	26.4	16.9
29.0	34	195.75	71.00	38.9	101.9	96.4	105.2	64.8	40.8	23.1	36.2	30.8	17.3
22.9	32	209.25	71.00	42.1	107.6	97.5	107.0	66.9	40.0	24.4	38.2	31.6	19.3
16.0	28	183.75	67.75	38.0	106.8	89.6	102.4	64.2	38.7	22.9	37.2	30.5	18.5
16.5	33	211.75	73.50	40.0	106.2	100.5	109.0	65.8	40.6	24.0	37.1	30.1	18.2
19.1	28	179.00	68.00	39.1	103.3	95.9	104.9	63.5	38.0	22.1	32.5	30.3	18.4
15.2	28	200.50	69.75	41.3	111.4	98.8	104.8	63.4	40.6	24.6	33.0	32.8	19.9
15.6	31	140.25	68.25	33.9	86.0	76.4	94.6	57.4	35.3	22.2	27.9	25.9	16.7
17.7	32	148.75	70.00	35.5	86.7	80.0	93.4	54.9	36.2	22.1	29.8	26.7	17.1
14.0	28	151.25	67.75	34.5	90.2	76.3	95.8	58.4	35.5	22.9	31.1	28.0	17.6
3.7	27	159.25	71.50	35.7	89.6	79.7	96.5	55.0	36.7	22.5	29.9	28.2	17.7
7.9	34	131.50	67.50	36.2	88.6	74.6	85.3	51.7	34.7	21.4	28.7	27.0	16.5
22.9	31	148.00	67.50	38.8	97.4	88.7	94.7	57.5	36.0	21.0	29.2	26.6	17.0
3.7	27	133.25	64.75	36.4	93.5	73.9	88.5	50.1	34.5	21.3	30.5	27.9	17.2
8.8	29	160.75	69.00	36.7	97.4	83.5	98.7	58.9	35.3	22.6	30.1	26.7	17.6
11.9	32	182.00	73.75	38.7	100.5	88.7	99.8	57.5	38.7	33.9	32.5	27.7	18.4
5.7	29	160.25	71.25	37.3	93.5	84.5	100.6	58.5	38.8	21.5	30.1	26.4	17.9
11.8	27	168.00	71.25	38.1	93.0	79.1	94.5	57.3	36.2	24.5	29.0	30.0	18.8
21.3	41	218.50	71.00	39.8	111.7	100.5	108.3	67.1	44.2	25.2	37.5	31.5	18.7
32.3	41	247.25	73.50	42.1	117.0	115.6	116.1	71.2	43.3	26.3	37.3	31.7	19.7
40.1	49	191.75	65.00	38.4	118.5	113.1	113.8	61.9	38.3	21.9	32.0	29.8	17.0
24.2	40	202.25	70.00	38.5	106.5	100.9	106.2	63.5	39.9	22.6	35.1	30.6	19.0
28.4	50	196.75	68.25	42.1	105.6	98.8	104.8	66.0	41.5	24.7	33.2	30.5	19.4
35.2	46	363.15	72.25	51.2	136.2	148.1	147.7	87.3	49.1	29.6	45.0	29.0	21.4
32.6	50	203.00	67.00	40.2	114.8	108.1	102.5	61.3	41.1	24.7	34.1	31.0	18.3
34.5	45	262.75	68.75	43.2	128.3	126.2	125.6	72.5	39.6	26.6	36.4	32.7	21.4
32.9	44	205.00	29.50	36.6	106.0	104.3	115.5	70.6	42.5	23.7	33.6	28.7	17.4
31.6	48	217.00	70.00	37.3	113.3	111.2	114.1	67.7	40.9	25.0	36.7	29.8	18.4
32.0	41	212.00	71.50	41.5	106.6	104.3	106.0	65.0	40.2	23.0	35.8	31.5	18.8
7.7	39	125.25	68.00	31.5	85.1	76.0	88.2	50.0	34.7	21.0	26.1	23.1	16.1
13.9	43	164.25	73.25	35.7	96.6	81.5	97.2	58.4	38.2	23.4	29.7	27.4	18.3
10.8	40	133.50	67.50	33.6	88.2	73.7	88.5	53.3	34.5	22.5	27.9	26.2	17.3
5.6	39	148.50	71.25	34.6	89.8	79.5	92.7	52.7	37.5	21.9	28.8	26.8	17.9
13.6	45	135.75	68.50	32.8	92.3	83.4	90.4	52.0	35.8	20.6	28.8	25.5	16.3
4.0	47	127.50	66.75	34.0	83.4	70.4	87.2	50.6	34.4	21.9	26.8	25.8	16.8
10.2	47	158.25	72.25	34.9	90.2	86.7	98.3	52.6	37.2	22.4	26.0	25.8	17.3
6.6	40	139.25	69.00	34.3	89.2	77.9	91.0	51.4	34.9	21.0	26.7	26.1	17.2
8.0	51	137.25	67.75	36.5	89.7	82.0	89.1	49.3	33.7	21.4	29.6	26.0	16.9
6.3	49	152.75	73.50	35.1	93.3	79.6	91.6	52.6	37.6	22.6	38.5	27.4	18.5
3.9	42	136.25	67.50	37.8	87.6	77.6	88.6	51.9	34.9	22.5	27.7	27.5	18.5
22.6	54	198.00	72.00	39.9	107.6	100.0	99.6	57.2	38.0	22.0	35.9	30.2	18.9
20.4	58	181.50	68.00	39.1	100.0	99.8	102.5	62.1	39.6	22.5	33.1	28.3	18.5
28.0	62	201.25	69.50	40.5	111.5	104.2	105.8	61.8	39.8	22.7	37.7	30.9	19.2
31.5	54	202.50	70.75	40.5	115.4	105.3	97.0	59.1	38.0	22.5	31.6	28.8	18.2
24.6	61	179.75	65.75	38.4	104.8	98.3	99.6	60.6	37.7	22.9	34.5	29.6	18.5
26.1	62	216.00	73.25	41.4	112.3	104.8	103.1	61.6	40.9	23.1	36.2	31.8	20.2
29.8	56	178.75	68.50	35.6	102.9	94.7	100.8	60.9	38.0	22.1	32.5	29.8	18.3
30.7	54	193.25	70.25	38.0	107.6	102.4	99.4	61.0	39.4	23.6	32.7	29.9	19.1
25.8	61	178.00	67.00	37.4	105.3	99.7	99.7	60.8	40.1	22.7	33.6	29.0	18.8
32.3	57	205.50	70.00	40.1	105.3	105.5	108.3	65.0	41.2	24.7	35.3	31.1	18.4
30.0	55	183.50	67.50	40.9	103.0	100.3	104.2	64.8	40.2	22.7	34.8	30.1	18.7
21.5	54	151.50	70.75	35.6	90.0	83.9	93.9	55.0	36.1	21.7	29.6	27.4	17.4
13.8	55	154.75	71.50	36.9	95.4	86.6	91.8	54.3	35.4	21.5	32.8	27.4	18.7
6.3	54	155.25	69.25	37.5	89.3	78.4	96.1	56.0	37.4	22.4	32.6	28.1	18.1
12.9	55	156.75	71.50	36.3	94.4	84.6	94.3	51.2	37.4	21.6	27.3	27.1	17.3
24.3	62	167.50	71.50	35.5	97.6	91.5	98.5	56.6	38.6	22.4	31.5	27.3	18.6
8.8	55	146.75	68.75	38.7	88.5	82.8	95.5	58.9	37.6	21.6	30.3	27.3	18.3
8.5	56	160.75	73.75	36.4	93.6	82.9	96.3	52.9	37.5	23.1	29.7	27.3	18.2
13.5	55	125.00	64.00	33.2	87.7	76.0	88.6	50.9	35.4	19.1	29.3	25.7	16.9
11.8	61	143.00	65.75	36.5	93.4	83.3	93.0	55.5	35.2	20.9	29.4	27.0	16.8
18.5	61	148.25	67.50	36.0	91.6	81.8	94.8	54.5	37.0	21.4	29.3	27.0	18.3
8.8	57	162.50	69.50	38.7	91.6	78.8	94.3	56.7	39.7	24.2	30.2	29.2	18.1
22.2	69	177.75	68.50	38.7	102.0	95.0	98.3	55.0	38.3	21.8	30.8	25.7	18.8
21.5	81	161.25	70.25	37.8	96.4	95.4	99.3	53.5	37.5	21.5	31.4	26.8	18.3
18.8	66	171.25	69.25	37.4	102.7	98.6	100.2	56.5	39.3	22.7	30.3	28.7	19.0
31.4	67	163.75	67.75	38.4	97.7	95.8	97.1	54.8	38.2	23.7	29.4	27.2	19.0
26.8	64	150.25	67.25	38.1	97.1	89.0	96.9	54.8	38.0	22.0	29.9	25.2	17.7
18.4	64	190.25	72.75	39.3	103.1	97.8	99.6	58.9	39.0	23.0	34.3	29.6	19.0
27.0	70	170.75	70.00	38.7	101.8	94.9	95.0	56.0	36.5	24.1	31.2	27.3	19.2
27.0	72	168.00	69.25	38.5	101.4	99.8	96.2	56.3	36.6	22.0	29.7	26.3	18.0
26.6	67	167.00	67.50	36.5	98.9	89.7	96.2	54.7	37.8	33.7	32.4	27.7	18.2
14.9	72	157.75	67.25	37.7	97.5	88.1	96.9	57.2	37.7	21.8	32.6	28.0	18.8
23.1	64	160.00	65.75	36.5	104.3	90.9	93.8	57.8	39.5	23.3	29.2	28.4	18.1
8.3	46	176.75	72.50	38.0	97.3	86.0	99.3	61.0	38.4	23.8	30.2	29.3	18.8
14.1	48	176.00	73.00	36.7	96.7	86.5	98.3	60.4	39.9	24.4	28.8	29.6	18.7
20.5	46	177.00	70.00	37.2	99.7	95.6	102.2	58.3	38.2	22.5	29.1	27.7	17.7
18.2	44	179.75	69.50	39.2	101.9	93.2	100.6	58.9	39.7	23.1	31.4	28.4	18.8
8.5	47	165.25	70.50	37.5	97.2	83.1	95.4	56.9	38.3	22.1	30.1	28.2	18.4
24.9	46	192.50	71.75	38.0	106.6	97.5	100.6	58.9	40.5	24.5	33.3	29.6	19.1
9.0	47	184.25	74.50	37.3	99.6	88.8	101.4	57.4	39.6	24.6	30.3	27.9	17.8
17.4	53	224.50	77.75	41.1	113.2	99.2	107.5	61.7	42.3	23.2	32.9	30.8	20.4
9.6	38	188.75	73.25	37.5	99.1	91.6	102.4	60.6	39.4	22.9	31.6	30.1	18.5
11.3	50	162.50	66.50	38.7	99.4	86.7	96.2	62.1	39.3	23.3	30.6	27.8	18.2
17.8	46	156.50	68.25	35.9	95.1	88.2	92.8	54.7	37.3	21.9	31.6	27.5	18.2
22.2	47	197.00	72.00	40.0	107.5	94.0	103.7	62.7	39.0	22.3	35.3	30.9	18.3
21.2	49	198.50	73.50	40.1	106.5	95.0	101.7	59.0	39.4	22.3	32.2	31.0	18.6
20.4	48	173.75	72.00	37.0	99.1	92.0	98.3	59.3	38.4	22.4	27.9	26.2	17.0
20.1	41	172.75	71.25	36.3	96.7	89.2	98.3	60.0	38.4	23.2	31.0	29.2	18.4
22.3	49	196.75	73.75	40.7	103.5	95.5	101.6	59.1	39.8	25.4	31.0	30.3	19.7
25.4	43	177.00	69.25	39.6	104.0	98.6	99.5	59.5	36.1	22.0	30.1	27.2	17.7
18.0	43	165.50	68.50	31.1	93.1	87.3	96.6	54.7	39.0	24.8	31.0	29.4	18.8
19.3	43	200.25	73.50	38.6	105.2	102.8	103.6	61.2	39.3	23.5	30.5	28.5	18.1
18.3	52	203.25	74.25	42.0	110.0	101.6	100.7	55.8	38.7	23.4	35.1	29.6	19.1
17.3	43	194.00	75.50	38.5	110.1	88.7	102.1	57.5	40.0	24.8	35.1	30.7	19.2
21.4	40	168.50	69.25	34.2	97.8	92.3	100.6	57.5	36.8	22.8	32.1	26.0	17.3
19.7	43	170.75	68.50	37.2	96.3	90.6	99.3	61.9	38.0	22.3	33.3	28.2	18.1
28.0	43	183.25	70.00	37.1	108.0	105.0	103.0	63.7	40.0	23.6	33.5	27.8	17.4
22.1	47	178.25	70.00	40.2	99.7	95.0	98.6	62.3	38.1	23.9	35.3	31.1	19.8
21.3	42	163.00	70.25	35.3	93.5	89.6	99.8	61.5	37.8	21.9	30.7	27.6	17.4
26.7	48	175.25	71.75	38.0	100.7	92.4	97.5	59.3	38.1	21.8	31.8	27.3	17.5
16.7	40	158.00	69.25	36.3	97.0	86.6	92.6	55.9	36.3	22.1	29.8	26.3	17.3
20.1	48	177.25	72.75	36.8	96.0	90.0	99.7	58.8	38.4	22.8	29.9	28.0	18.1
13.9	51	179.00	72.00	41.0	99.2	90.0	96.4	56.8	38.8	23.3	33.4	29.8	19.5
25.8	40	191.00	74.00	38.3	95.4	92.4	104.3	64.6	41.1	24.8	33.6	29.5	18.5
18.1	44	187.50	72.25	38.0	101.8	87.5	101.0	58.5	39.2	24.5	32.1	28.6	18.0
27.9	52	206.50	74.50	40.8	104.3	99.2	104.1	58.5	39.3	24.6	33.9	31.2	19.5
25.3	44	185.25	71.50	39.5	99.2	98.1	101.4	57.1	40.5	23.2	33.0	29.6	18.4
14.7	40	160.25	68.75	36.9	99.3	83.3	97.5	60.5	38.7	22.6	34.4	28.0	17.6
16.0	47	151.50	66.75	36.9	94.0	86.1	95.2	58.1	36.5	22.1	30.6	27.5	17.6
13.8	50	161.00	66.50	37.7	98.9	84.1	94.0	58.5	36.6	23.5	34.4	29.2	18.0
17.5	46	167.00	67.00	36.6	101.0	89.9	100.0	60.7	36.0	21.9	35.6	30.2	17.6
27.2	42	177.50	68.75	38.9	98.7	92.1	98.5	60.7	36.8	22.2	33.8	30.3	17.2
17.4	43	152.25	67.75	37.5	95.9	78.0	93.2	53.5	35.8	20.8	33.9	28.2	17.4
20.8	40	192.25	73.25	39.8	103.9	93.5	99.5	61.7	39.0	21.8	33.3	29.6	18.1
14.9	42	165.25	69.75	38.3	96.2	87.0	97.8	57.4	36.9	22.2	31.6	27.8	17.7
18.1	49	171.75	71.50	35.5	97.8	90.1	95.8	57.0	38.7	23.2	27.5	26.5	17.6
22.7	40	171.25	70.50	36.3	94.6	90.3	99.1	60.3	38.5	23.0	31.2	28.4	17.1
23.6	47	197.00	73.25	37.8	103.6	99.8	103.2	61.2	38.1	22.6	33.5	28.6	17.9
26.1	50	157.00	66.75	37.8	100.4	89.4	92.3	56.1	35.6	20.5	33.6	29.3	17.3
24.4	41	168.25	69.50	36.5	98.4	87.2	98.4	56.0	36.9	23.0	34.0	29.8	18.1
27.1	44	186.00	69.75	37.8	104.6	101.1	102.1	58.9	37.9	22.7	30.9	28.8	17.6
21.8	39	166.75	70.75	37.0	92.9	86.1	95.6	58.8	36.1	22.4	32.7	28.3	17.1
29.4	43	187.75	74.00	37.7	97.8	98.6	100.6	63.6	39.2	23.8	34.3	28.4	17.7
22.4	40	168.25	71.25	34.3	98.3	88.5	98.3	58.1	38.4	22.5	31.7	27.4	17.6
20.4	49	212.75	75.00	40.8	104.7	106.6	107.7	66.5	42.5	24.5	35.5	29.8	18.7
24.9	40	176.75	71.00	37.4	98.6	93.1	101.6	59.1	39.6	21.6	30.8	27.9	16.6
18.3	40	173.25	69.50	36.5	99.5	93.0	99.3	60.4	38.2	22.0	32.0	28.5	17.8
23.3	52	167.00	67.75	37.5	102.7	91.0	98.9	57.1	36.7	22.3	31.6	27.5	17.9
9.4	23	159.75	72.25	35.5	92.1	77.1	93.9	56.1	36.1	22.7	30.5	27.2	18.2
10.3	23	188.15	77.50	38.0	96.6	85.3	102.5	59.1	37.6	23.2	31.8	29.7	18.3
14.2	24	156.00	70.75	35.7	92.7	81.9	95.3	56.4	36.5	22.0	33.5	28.3	17.3
19.2	24	208.50	72.75	39.2	102.0	99.1	110.1	71.2	43.5	25.2	36.1	30.3	18.7
29.6	25	206.50	69.75	40.9	110.9	100.5	106.2	68.4	40.8	24.6	33.3	29.7	18.4
5.3	25	143.75	72.50	35.2	92.3	76.5	92.1	51.9	35.7	22.0	25.8	25.2	16.9
25.2	26	223.00	70.25	40.6	114.1	106.8	113.9	67.6	42.7	24.7	36.0	30.4	18.4
9.4	26	152.25	69.00	35.4	92.9	77.6	93.5	56.9	35.9	20.4	31.6	29.0	17.8
19.6	26	241.75	74.50	41.8	108.3	102.9	114.4	72.9	43.5	25.1	38.5	33.8	19.6
10.1	27	146.00	72.25	34.1	88.5	72.8	91.1	53.6	36.8	23.8	27.8	26.3	17.4
16.5	27	156.75	67.25	37.9	94.0	88.2	95.2	56.8	37.4	22.8	30.6	28.3	17.9
21.0	27	200.25	73.50	38.2	101.1	100.1	105.0	62.1	40.0	24.9	33.7	29.2	19.4
17.3	28	171.50	75.25	35.6	92.1	83.5	98.3	57.3	37.8	21.7	32.2	27.7	17.7
31.2	28	205.75	69.00	38.5	105.6	105.0	106.4	68.6	40.0	25.2	35.2	30.7	19.1
10.0	28	182.50	72.25	37.0	98.5	90.8	102.5	60.8	38.5	25.0	31.6	28.0	18.6
12.5	30	136.50	68.75	35.9	88.7	76.6	89.8	50.1	34.8	21.8	27.0	34.9	16.9
22.5	31	177.25	71.50	36.2	101.1	92.4	99.3	59.4	39.0	24.6	30.1	28.2	18.2
9.4	31	151.25	72.25	35.0	94.0	81.2	91.5	52.5	36.6	21.0	27.0	26.3	16.5
14.6	33	196.00	73.00	38.5	103.8	95.6	105.1	61.4	40.6	25.0	31.3	29.2	19.1
13.0	33	184.25	68.75	40.7	98.9	92.1	103.5	64.0	37.3	23.5	33.5	30.6	19.7
15.1	34	140.00	70.50	36.0	89.2	83.4	89.6	52.4	35.6	20.4	28.3	26.2	16.5
27.3	34	218.75	72.00	39.5	111.4	106.0	108.8	63.8	42.0	23.4	34.0	31.2	18.5
19.2	35	217.00	73.75	40.5	107.5	95.1	104.5	64.8	41.3	25.6	36.4	33.7	19.4
21.8	35	166.25	68.00	38.5	99.1	90.4	95.6	55.5	34.2	21.9	30.2	28.7	17.7
20.3	35	224.75	72.25	43.9	108.2	100.4	106.8	63.3	41.7	24.6	37.2	33.1	19.8
34.3	35	228.25	69.50	40.4	114.9	115.9	111.9	74.4	40.6	24.0	36.1	31.8	18.8
16.5	35	172.75	69.50	37.6	99.1	90.8	98.1	60.1	39.1	23.4	32.5	29.8	17.4
3.0	35	152.25	67.75	37.0	92.2	81.9	92.8	54.7	36.2	22.1	30.4	27.4	17.7
.7	35	125.75	65.50	34.0	90.8	75.0	89.2	50.0	34.8	22.0	24.8	25.9	16.9
20.5	35	177.25	71.00	38.4	100.5	90.3	98.7	57.8	37.3	22.4	31.0	28.7	17.7
16.9	36	176.25	71.50	38.7	98.2	90.3	99.9	59.2	37.7	21.5	32.4	28.4	17.8
25.3	36	226.75	71.75	41.5	115.3	108.8	114.4	69.2	42.4	24.0	35.4	21.0	20.1
9.9	37	145.25	69.25	36.0	96.8	79.4	89.2	50.3	34.8	22.2	31.0	26.9	16.9
13.1	37	151.00	67.00	35.3	92.6	83.2	96.4	60.0	38.1	22.0	31.5	26.6	16.7
29.9	37	241.25	71.50	42.1	119.2	110.3	113.9	69.8	42.6	24.8	34.4	29.5	18.4
22.5	38	187.25	69.25	38.0	102.7	92.7	101.9	64.7	39.5	24.7	34.8	30.3	18.1
16.9	39	234.75	74.50	42.8	109.5	104.5	109.9	69.5	43.1	25.8	39.1	32.5	19.9
26.6	39	219.25	74.25	40.0	108.5	104.6	109.8	68.1	42.8	24.1	35.6	29.0	19.0
.0	40	118.50	68.00	33.8	79.3	69.4	85.0	47.2	33.5	20.2	27.7	24.6	16.5
11.5	40	145.75	67.25	35.5	95.5	83.6	91.6	54.1	36.2	21.8	31.4	28.3	17.2
12.1	40	159.25	69.75	35.3	92.3	86.8	96.1	58.0	39.4	22.7	30.0	26.4	17.4
17.5	40	170.50	74.25	37.7	98.9	90.4	95.5	55.4	38.9	22.4	30.5	28.9	17.7
8.6	40	167.50	71.50	39.4	89.5	83.7	98.1	57.3	39.7	22.6	32.9	29.3	18.2
23.6	41	232.75	74.25	41.9	117.5	109.3	108.8	67.7	41.3	24.7	37.2	31.8	20.0
20.4	41	210.50	72.00	38.5	107.4	98.9	104.1	63.5	39.8	23.5	36.4	30.4	19.1
20.5	41	202.25	72.50	40.8	109.2	98.0	101.8	62.8	41.3	24.8	36.6	32.4	18.8
24.4	41	185.00	68.25	38.0	103.4	101.2	103.1	61.5	40.4	22.9	33.4	29.2	18.5
11.4	41	153.00	69.25	36.4	91.4	80.6	92.3	54.3	36.3	21.8	29.6	27.3	17.9
38.1	42	244.25	76.00	41.8	115.2	113.7	112.4	68.5	45.0	25.5	37.1	31.2	19.9
15.9	42	193.50	70.50	40.7	104.9	94.1	102.7	60.6	38.6	24.7	34.0	30.1	18.7
24.7	42	224.75	74.75	38.5	106.7	105.7	111.8	65.3	43.3	26.0	33.7	29.9	18.5
22.8	42	162.75	72.75	35.4	92.2	85.6	96.5	60.2	38.9	22.4	31.7	27.1	17.1
25.5	42	180.00	68.25	38.5	101.6	96.6	100.6	61.1	38.4	24.1	32.9	29.8	18.8
22.0	42	156.25	69.00	35.5	97.8	86.0	96.2	57.7	38.6	24.0	31.2	27.3	17.4
17.7	42	168.00	71.50	36.5	92.0	89.7	101.0	62.3	38.0	22.3	30.8	27.8	16.9
6.6	42	167.25	72.75	37.6	94.0	78.0	99.0	57.5	40.0	22.5	30.6	30.0	18.5
23.6	43	170.75	67.50	37.4	103.7	89.7	94.2	58.5	39.0	24.1	33.8	28.8	18.8
12.2	43	178.25	70.25	37.8	102.7	89.2	99.2	60.2	39.2	23.8	31.7	28.4	18.6
22.1	43	150.00	69.25	35.2	91.1	85.7	96.9	55.5	35.7	22.0	29.4	26.6	17.4
28.7	43	200.50	71.50	37.9	107.2	103.1	105.5	68.8	38.3	23.7	32.1	28.9	18.7
6.0	44	184.00	74.00	37.9	100.8	89.1	102.6	60.6	39.0	24.0	32.9	29.2	18.4
34.8	44	223.00	69.75	40.9	121.6	113.9	107.1	63.5	40.3	21.8	34.8	30.7	17.4
16.6	44	208.75	73.00	41.9	105.6	96.3	102.0	63.3	39.8	24.1	37.3	23.1	19.4
32.9	44	166.00	65.50	39.1	100.6	93.9	100.1	58.9	37.6	21.4	33.1	29.5	17.3
32.8	47	195.00	72.50	40.2	102.7	101.3	101.7	60.7	39.4	23.3	36.7	31.6	18.4
9.6	47	160.50	70.25	36.0	99.8	83.9	91.8	53.0	36.2	22.5	31.4	27.5	17.7
10.8	47	159.75	70.75	34.5	92.9	84.4	94.0	56.0	38.2	22.6	29.0	26.2	17.6
7.1	49	140.50	68.00	35.8	91.2	79.4	89.0	51.1	35.0	21.7	30.9	28.8	17.4
27.2	49	216.25	74.50	40.2	115.6	104.0	109.0	63.7	40.3	23.2	36.8	31.0	18.9
19.5	49	168.25	71.75	38.3	98.3	89.7	99.1	56.3	38.8	23.0	29.5	27.9	18.6
18.7	50	194.75	70.75	39.0	103.7	97.6	104.2	60.0	40.9	25.5	32.7	30.0	19.0
19.5	50	172.75	73.00	37.4	98.7	87.6	96.1	57.1	38.1	21.8	28.6	26.7	18.0
47.5	51	219.00	64.00	41.2	119.8	122.1	112.8	62.5	36.9	23.6	34.7	29.1	18.4
13.6	51	149.25	69.75	34.8	92.8	81.1	96.3	53.8	36.5	21.5	31.3	26.3	17.8
7.5	51	154.50	70.00	36.9	93.3	81.5	94.4	54.7	39.0	22.6	27.5	25.9	18.6
24.5	52	199.25	71.75	39.4	106.8	100.0	105.0	63.9	39.2	22.9	35.7	30.4	19.2
15.0	53	154.50	69.25	37.6	93.9	88.7	94.5	53.7	36.2	22.0	28.5	25.7	17.1
12.4	54	153.25	70.50	38.5	99.0	91.8	96.2	57.7	38.1	23.9	31.4	29.9	18.9
26.0	54	230.00	72.25	42.5	119.9	110.4	105.5	64.2	42.7	27.0	38.4	32.0	19.6
11.5	54	161.75	67.50	37.4	94.2	87.6	95.6	59.7	40.2	23.4	27.9	27.0	17.8
5.2	55	142.25	67.25	35.2	92.7	82.8	91.9	54.4	35.2	22.5	29.4	26.8	17.0
10.9	55	179.75	68.75	41.1	106.9	95.3	98.2	57.4	37.1	21.8	34.1	31.1	19.2
12.5	55	126.50	66.75	33.4	88.8	78.2	87.5	50.8	33.0	19.7	25.3	22.0	15.8
14.8	55	169.50	68.25	37.2	101.7	91.1	97.1	56.6	38.5	22.6	33.4	29.3	18.8
25.2	55	198.50	74.25	38.3	105.3	96.7	106.6	64.0	42.6	23.4	33.2	30.0	18.4
14.9	56	174.50	69.50	38.1	104.0	89.4	98.4	58.4	37.4	22.5	34.6	30.1	18.8
17.0	56	167.75	68.50	37.4	98.6	93.0	97.0	55.4	38.8	23.2	32.4	29.7	19.0
10.6	57	147.75	65.75	35.2	99.6	86.4	90.1	53.0	35.0	21.3	31.7	27.3	16.9
16.1	57	182.25	71.75	39.4	103.4	96.7	100.7	59.3	38.6	22.8	31.8	29.1	19.0
15.4	58	175.50	71.50	38.0	100.2	88.1	97.8	57.1	38.9	23.6	30.9	29.6	18.0
26.7	58	161.75	67.25	35.1	94.9	94.9	100.2	56.8	35.9	21.0	27.8	26.1	17.6
25.8	60	157.75	67.50	40.4	97.2	93.3	94.0	54.3	35.7	21.0	31.3	28.7	18.3
18.6	62	168.75	67.50	38.3	104.7	95.6	93.7	54.4	37.1	22.7	30.3	26.3	18.3
24.8	62	191.50	72.25	40.6	104.0	98.2	101.1	59.3	40.3	23.0	32.6	28.5	19.0
27.3	63	219.15	69.50	40.2	117.6	113.8	111.8	63.4	41.1	22.3	35.1	29.6	18.5
12.4	64	155.25	69.50	37.9	95.8	82.8	94.5	61.2	39.1	22.3	29.8	28.9	18.3
29.9	65	189.75	65.75	40.8	106.4	100.5	100.5	59.2	38.1	24.0	35.9	30.5	19.1
17.0	65	127.50	65.75	34.7	93.0	79.7	87.6	50.7	33.4	20.1	28.5	24.8	16.5
35.0	65	224.50	68.25	38.8	119.6	118.0	114.3	61.3	42.1	23.4	34.9	30.1	19.4
30.4	66	234.25	72.00	41.4	119.7	109.0	109.1	63.7	42.4	24.6	35.6	30.7	19.5
32.6	67	227.75	72.75	41.3	115.8	113.4	109.8	65.6	46.0	25.4	35.3	29.8	19.5
29.0	67	199.50	68.50	40.7	118.3	106.1	101.6	58.2	38.8	24.1	32.1	29.3	18.5
15.2	68	155.50	69.25	36.3	97.4	84.3	94.4	54.3	37.5	22.6	29.2	27.3	18.5
30.2	69	215.50	70.50	40.8	113.7	107.6	110.0	63.3	44.0	22.6	37.5	32.6	18.8
11.0	70	134.25	67.00	34.9	89.2	83.6	88.8	49.6	34.8	21.5	25.6	25.7	18.5
33.6	72	201.00	69.75	40.9	108.5	105.0	104.5	59.6	40.8	23.2	35.2	28.6	20.1
29.3	72	186.75	66.00	38.9	111.1	111.5	101.7	60.3	37.3	21.5	31.3	27.2	18.0
26.0	72	190.75	70.50	38.9	108.3	101.3	97.8	56.0	41.6	22.7	30.5	29.4	19.8
31.9	74	207.50	70.00	40.8	112.4	108.5	107.1	59.3	42.2	24.6	33.7	30.0	20.9

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	26 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 26 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190472&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]26 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190472&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190472&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	26 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Fat[t] = -18.1884850809836 + 0.0620786463547041Age[t] -0.0884446759002108Weight[t] -0.0695904296150214Height[t] -0.470600013585041Neck[t] -0.0238641465015974Chest[t] + 0.954773457529579Abdomen[t] -0.207541123438142Hip[t] + 0.236099844751604Thigh[t] + 0.0152812146458913Knee[t] + 0.1739953675909Ankle[t] + 0.181602416094232Biceps[t] + 0.452024914117847Forearm[t] -1.62063909894191Wrist[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Fat[t] =  -18.1884850809836 +  0.0620786463547041Age[t] -0.0884446759002108Weight[t] -0.0695904296150214Height[t] -0.470600013585041Neck[t] -0.0238641465015974Chest[t] +  0.954773457529579Abdomen[t] -0.207541123438142Hip[t] +  0.236099844751604Thigh[t] +  0.0152812146458913Knee[t] +  0.1739953675909Ankle[t] +  0.181602416094232Biceps[t] +  0.452024914117847Forearm[t] -1.62063909894191Wrist[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190472&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Fat[t] =  -18.1884850809836 +  0.0620786463547041Age[t] -0.0884446759002108Weight[t] -0.0695904296150214Height[t] -0.470600013585041Neck[t] -0.0238641465015974Chest[t] +  0.954773457529579Abdomen[t] -0.207541123438142Hip[t] +  0.236099844751604Thigh[t] +  0.0152812146458913Knee[t] +  0.1739953675909Ankle[t] +  0.181602416094232Biceps[t] +  0.452024914117847Forearm[t] -1.62063909894191Wrist[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190472&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190472&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
Fat[t] = -18.1884850809836 + 0.0620786463547041Age[t] -0.0884446759002108Weight[t] -0.0695904296150214Height[t] -0.470600013585041Neck[t] -0.0238641465015974Chest[t] + 0.954773457529579Abdomen[t] -0.207541123438142Hip[t] + 0.236099844751604Thigh[t] + 0.0152812146458913Knee[t] + 0.1739953675909Ankle[t] + 0.181602416094232Biceps[t] + 0.452024914117847Forearm[t] -1.62063909894191Wrist[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	-18.1884850809836	17.348566	-1.0484	0.295511	0.147756
Age	0.0620786463547041	0.032349	1.919	0.056176	0.028088
Weight	-0.0884446759002108	0.053526	-1.6524	0.099775	0.049888
Height	-0.0695904296150214	0.096006	-0.7249	0.469254	0.234627
Neck	-0.470600013585041	0.232467	-2.0244	0.044049	0.022025
Chest	-0.0238641465015974	0.099147	-0.2407	0.809999	0.404999
Abdomen	0.954773457529579	0.086448	11.0444	0	0
Hip	-0.207541123438142	0.14591	-1.4224	0.156223	0.078111
Thigh	0.236099844751604	0.144358	1.6355	0.103262	0.051631
Knee	0.0152812146458913	0.241977	0.0632	0.949699	0.474849
Ankle	0.1739953675909	0.221466	0.7857	0.432853	0.216426
Biceps	0.181602416094232	0.171125	1.0612	0.289663	0.144832
Forearm	0.452024914117847	0.199129	2.27	0.024102	0.012051
Wrist	-1.62063909894191	0.534946	-3.0295	0.00272	0.00136

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & -18.1884850809836 & 17.348566 & -1.0484 & 0.295511 & 0.147756 \tabularnewline
Age & 0.0620786463547041 & 0.032349 & 1.919 & 0.056176 & 0.028088 \tabularnewline
Weight & -0.0884446759002108 & 0.053526 & -1.6524 & 0.099775 & 0.049888 \tabularnewline
Height & -0.0695904296150214 & 0.096006 & -0.7249 & 0.469254 & 0.234627 \tabularnewline
Neck & -0.470600013585041 & 0.232467 & -2.0244 & 0.044049 & 0.022025 \tabularnewline
Chest & -0.0238641465015974 & 0.099147 & -0.2407 & 0.809999 & 0.404999 \tabularnewline
Abdomen & 0.954773457529579 & 0.086448 & 11.0444 & 0 & 0 \tabularnewline
Hip & -0.207541123438142 & 0.14591 & -1.4224 & 0.156223 & 0.078111 \tabularnewline
Thigh & 0.236099844751604 & 0.144358 & 1.6355 & 0.103262 & 0.051631 \tabularnewline
Knee & 0.0152812146458913 & 0.241977 & 0.0632 & 0.949699 & 0.474849 \tabularnewline
Ankle & 0.1739953675909 & 0.221466 & 0.7857 & 0.432853 & 0.216426 \tabularnewline
Biceps & 0.181602416094232 & 0.171125 & 1.0612 & 0.289663 & 0.144832 \tabularnewline
Forearm & 0.452024914117847 & 0.199129 & 2.27 & 0.024102 & 0.012051 \tabularnewline
Wrist & -1.62063909894191 & 0.534946 & -3.0295 & 0.00272 & 0.00136 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190472&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]-18.1884850809836[/C][C]17.348566[/C][C]-1.0484[/C][C]0.295511[/C][C]0.147756[/C][/ROW]
[ROW][C]Age[/C][C]0.0620786463547041[/C][C]0.032349[/C][C]1.919[/C][C]0.056176[/C][C]0.028088[/C][/ROW]
[ROW][C]Weight[/C][C]-0.0884446759002108[/C][C]0.053526[/C][C]-1.6524[/C][C]0.099775[/C][C]0.049888[/C][/ROW]
[ROW][C]Height[/C][C]-0.0695904296150214[/C][C]0.096006[/C][C]-0.7249[/C][C]0.469254[/C][C]0.234627[/C][/ROW]
[ROW][C]Neck[/C][C]-0.470600013585041[/C][C]0.232467[/C][C]-2.0244[/C][C]0.044049[/C][C]0.022025[/C][/ROW]
[ROW][C]Chest[/C][C]-0.0238641465015974[/C][C]0.099147[/C][C]-0.2407[/C][C]0.809999[/C][C]0.404999[/C][/ROW]
[ROW][C]Abdomen[/C][C]0.954773457529579[/C][C]0.086448[/C][C]11.0444[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Hip[/C][C]-0.207541123438142[/C][C]0.14591[/C][C]-1.4224[/C][C]0.156223[/C][C]0.078111[/C][/ROW]
[ROW][C]Thigh[/C][C]0.236099844751604[/C][C]0.144358[/C][C]1.6355[/C][C]0.103262[/C][C]0.051631[/C][/ROW]
[ROW][C]Knee[/C][C]0.0152812146458913[/C][C]0.241977[/C][C]0.0632[/C][C]0.949699[/C][C]0.474849[/C][/ROW]
[ROW][C]Ankle[/C][C]0.1739953675909[/C][C]0.221466[/C][C]0.7857[/C][C]0.432853[/C][C]0.216426[/C][/ROW]
[ROW][C]Biceps[/C][C]0.181602416094232[/C][C]0.171125[/C][C]1.0612[/C][C]0.289663[/C][C]0.144832[/C][/ROW]
[ROW][C]Forearm[/C][C]0.452024914117847[/C][C]0.199129[/C][C]2.27[/C][C]0.024102[/C][C]0.012051[/C][/ROW]
[ROW][C]Wrist[/C][C]-1.62063909894191[/C][C]0.534946[/C][C]-3.0295[/C][C]0.00272[/C][C]0.00136[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190472&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190472&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	-18.1884850809836	17.348566	-1.0484	0.295511	0.147756
Age	0.0620786463547041	0.032349	1.919	0.056176	0.028088
Weight	-0.0884446759002108	0.053526	-1.6524	0.099775	0.049888
Height	-0.0695904296150214	0.096006	-0.7249	0.469254	0.234627
Neck	-0.470600013585041	0.232467	-2.0244	0.044049	0.022025
Chest	-0.0238641465015974	0.099147	-0.2407	0.809999	0.404999
Abdomen	0.954773457529579	0.086448	11.0444	0	0
Hip	-0.207541123438142	0.14591	-1.4224	0.156223	0.078111
Thigh	0.236099844751604	0.144358	1.6355	0.103262	0.051631
Knee	0.0152812146458913	0.241977	0.0632	0.949699	0.474849
Ankle	0.1739953675909	0.221466	0.7857	0.432853	0.216426
Biceps	0.181602416094232	0.171125	1.0612	0.289663	0.144832
Forearm	0.452024914117847	0.199129	2.27	0.024102	0.012051
Wrist	-1.62063909894191	0.534946	-3.0295	0.00272	0.00136

Multiple Linear Regression - Regression Statistics
Multiple R	0.86547672940887
R-squared	0.749049969148275
Adjusted R-squared	0.73534261452192
F-TEST (value)	54.6458444803127
F-TEST (DF numerator)	13
F-TEST (DF denominator)	238
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	4.3052869798689
Sum Squared Residuals	4411.44804300883

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.86547672940887 \tabularnewline
R-squared & 0.749049969148275 \tabularnewline
Adjusted R-squared & 0.73534261452192 \tabularnewline
F-TEST (value) & 54.6458444803127 \tabularnewline
F-TEST (DF numerator) & 13 \tabularnewline
F-TEST (DF denominator) & 238 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 4.3052869798689 \tabularnewline
Sum Squared Residuals & 4411.44804300883 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190472&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.86547672940887[/C][/ROW]
[ROW][C]R-squared[/C][C]0.749049969148275[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.73534261452192[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]54.6458444803127[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]13[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]238[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]4.3052869798689[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]4411.44804300883[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190472&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190472&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R	0.86547672940887
R-squared	0.749049969148275
Adjusted R-squared	0.73534261452192
F-TEST (value)	54.6458444803127
F-TEST (DF numerator)	13
F-TEST (DF denominator)	238
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	4.3052869798689
Sum Squared Residuals	4411.44804300883

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.3	16.1527808735027	-3.8527808735027
2	6.1	8.84370385843499	-2.74370385843499
3	25.3	18.5567680591844	6.74323194081556
4	10.4	11.9214552413727	-1.52145524137271
5	28.7	27.291078276092	1.40892172390801
6	20.9	16.9403379002368	3.9596620997632
7	19.2	16.7388495527999	2.46115044720013
8	12.4	13.9159145832453	-1.51591458324533
9	4.1	9.67746577513297	-5.57746577513297
10	11.7	10.1835718161123	1.51642818388769
11	7.1	9.0172397753499	-1.9172397753499
12	7.8	12.8674106701886	-5.06741067018856
13	20.8	17.8253553607477	2.97464463925229
14	21.2	25.0509120093389	-3.8509120093389
15	22.1	24.0839261930635	-1.98392619306349
16	20.9	22.974522973426	-2.07452297342601
17	29	23.5383160426835	5.46168395731649
18	22.9	19.4482119736127	3.45178802638735
19	16	16.7412889924041	-0.741288992404074
20	16.5	23.1708745480026	-6.67087454800263
21	19.1	21.1090526029561	-2.00905260295613
22	15.2	19.8877007794151	-4.68770077941515
23	15.6	9.55142001673523	6.04857998326477
24	17.7	11.1210173638967	6.57898263610333
25	14	8.13272944733555	5.86727055266445
26	3.7	8.50909673551517	-4.80909673551517
27	7.9	9.10335612465817	-1.20335612465817
28	22.9	17.9549559240456	4.94504407595442
29	3.7	6.36291763406911	-2.66291763406911
30	8.8	11.6265136518852	-2.82651365188516
31	11.9	14.6030169839567	-2.7030169839567
32	5.7	11.0311632144958	-5.33116321449585
33	11.8	6.13512290331984	5.66487709668016
34	21.3	23.8185171226594	-2.51851712265942
35	32.3	32.270251629979	0.0297483700210498
36	40.1	37.5795849138025	2.52041508619753
37	24.2	24.1199576401647	0.0800423598352868
38	28.4	21.9034111736215	6.49658882637849
39	35.2	44.0348892206514	-8.8348892206514
40	32.6	32.5253234873826	0.0746765126174193
41	34.5	36.6759455720518	-2.17594557205179
42	32.9	32.534837730462	0.36516226953798
43	31.6	34.2348802376012	-2.63488023760119
44	32	26.3752707892707	5.62472921072933
45	7.7	10.9041158347347	-3.20411583473465
46	13.9	9.95654610857628	3.94345389142372
47	10.8	7.77130190782924	3.02869809217076
48	5.6	9.54087987928135	-3.94087987928135
49	13.6	17.8087240189123	-4.20872401891228
50	4	5.52042426159203	-1.52042426159203
51	10.2	14.7376710858701	-4.5376710858701
52	6.6	9.49173918261154	-2.89173918261154
53	8	14.2232161490253	-6.22321614902531
54	6.3	10.7942358851282	-4.49423588512817
55	3.9	7.67501483428857	-3.77501483428857
56	22.6	23.5568277520263	-0.956827752026322
57	20.4	25.8571231872631	-5.45712318726308
58	28	27.6803234657295	0.319676534270531
59	31.5	28.6335301315892	2.86646986841075
60	24.6	26.2675867967314	-1.66758679673135
61	26.1	25.3583613773373	0.741638622662733
62	29.8	23.5185986747457	6.28140132525435
63	30.7	27.4819304361293	3.21806956387069
64	25.8	27.238220569014	-1.43822056901398
65	32.3	30.0937699487517	2.20623005124832
66	30	26.2143659822871	3.78563401771288
67	21.5	15.4317550835511	6.06824491644888
68	13.8	15.6908050845803	-1.89080508458028
69	6.3	8.72373308212155	-2.42373308212155
70	12.9	13.8422665868639	-0.942266586863908
71	24.3	19.5211929410977	4.77880705890229
72	8.8	12.7974020670645	-3.99740206706452
73	8.5	11.0593887554809	-2.55938875548086
74	13.5	11.6052405516314	1.89475944836864
75	11.8	16.7956358731265	-4.99563587312649
76	18.5	12.1113244702206	6.38867552977937
77	8.8	8.9622133190289	-0.1622133190289
78	22.2	19.3690191542168	2.83098084578324
79	21.5	23.1809993587453	-1.68099935874531
80	18.8	24.8105847410993	-6.01058474109935
81	31.4	22.1734533713676	9.22654662863235
82	26.8	17.915296817829	8.88470318217095
83	18.4	22.9669182866307	-4.56691828663072
84	27	21.2964142716412	5.7035857283588
85	27	27.1762996837945	-0.17629968379453
86	26.6	20.9091399423399	5.69086005766009
87	14.9	17.5685386181121	-2.66853861811206
88	23.1	21.8244498195397	1.27555018046026
89	8.3	12.6768186686851	-4.3768186686851
90	14.1	14.1726277485466	-0.0726277485466366
91	20.5	21.7048262542423	-1.20482625424235
92	18.2	17.6395286050088	0.560471394991212
93	8.5	11.0409841057249	-2.54098410572493
94	24.9	21.6946234526603	3.2053765473397
95	9	14.7619819523051	-5.76198195230511
96	17.4	16.2814693633775	1.11853063662254
97	9.6	16.8286594768529	-7.22865947685293
98	11.3	16.0886489423768	-4.7886489423768
99	17.8	17.83201518129	-0.0320151812899643
100	22.2	19.1323573861095	3.06764261389052
101	21.2	18.4947082022095	2.70529179779049
102	20.4	19.9181559590088	0.481844040991178
103	20.1	17.2921848917938	2.80781510820625
104	22.3	17.1715268119271	5.12847318807287
105	25.4	23.8832302188857	1.51676978111433
106	18	17.7991025878039	0.200897412196126
107	19.3	25.855505521198	-6.55550552119796
108	18.3	22.2486916414326	-3.94869164143261
109	17.3	12.4586798226311	4.84132017736893
110	21.4	21.0413278180696	0.358672181930379
111	19.7	19.2374863421416	0.462513657858414
112	28	32.4479213825049	-4.44792138250494
113	22.1	20.8647753370022	1.23522466299777
114	21.3	19.8654581100321	1.43454188996792
115	26.7	20.1282218802149	6.57177811978511
116	16.7	16.4296732842605	0.270326715739459
117	20.1	16.8700960335713	3.22990396642873
118	13.9	14.3870160368787	-0.487016036878727
119	25.8	18.1758899152996	7.62411008470042
120	18.1	13.4601408816459	4.63985911835407
121	27.9	20.3599924453783	7.54000755462167
122	25.3	22.5354064531427	2.76459354685733
123	14.7	14.0878701416476	0.612129858352424
124	16	17.1093250592991	-1.10932505929914
125	13.8	15.4686597586299	-1.6686597586299
126	17.5	20.9649283178635	-3.46492831786346
127	27.2	21.4814795451094	5.71852045489058
128	17.4	8.99568501052695	8.40431498947305
129	20.8	18.6554410256316	2.14455897436839
130	14.9	14.9957824062943	-0.0957824062942603
131	18.1	18.3249598860606	-0.224959886060557
132	22.7	20.1683890756069	2.53161092439306
133	23.6	24.7812259038293	-1.18122590382932
134	26.1	21.065764851441	5.03423514855899
135	24.4	16.0470727579408	8.35292724205917
136	27.1	26.8328285689513	0.267171431048742
137	21.8	16.6463875432494	5.15361245675065
138	29.4	26.0494307457112	3.35056925428877
139	22.4	17.9023849221525	4.4976150778475
140	20.4	28.7693513231312	-8.36935132313121
141	24.9	21.1901065486414	3.70989345135857
142	18.3	21.2874832510073	-2.98748325100727
143	23.3	18.8969112455707	4.40308875442932
144	9.4	5.3879797177854	4.0120202822146
145	10.3	9.29350172003732	1.00649827996269
146	14.2	12.5257836007293	1.67421639927069
147	19.2	22.4900682420478	-3.29006824204783
148	29.6	22.9712437747845	6.62875622521552
149	5.3	6.07669239355771	-0.776692393557707
150	25.2	26.6853088533332	-1.48530885333316
151	9.4	8.49938891475277	0.900611085247233
152	19.6	21.8567929671057	-2.25679296710571
153	10.1	4.08395329722268	6.01604670277732
154	16.5	16.6070948700781	-0.107094870078076
155	21	21.5373788453854	-0.537378845385381
156	17.3	11.0810445274885	6.21895547251153
157	31.2	28.5889127394687	2.61108726053125
158	10	15.5828292017915	-5.58282920179146
159	12.5	11.7476191632248	0.75238083677518
160	22.5	18.8655545444495	3.63444545555045
161	9.4	11.8135612648151	-2.41356126481514
162	14.6	17.7093322453172	-3.10933224531718
163	13	15.4787047695703	-2.47870476957027
164	15.1	15.3029529201382	-0.202952920138215
165	27.3	27.0150597699644	0.284940230035648
166	19.2	17.9335253468734	1.26647465312655
167	21.8	17.7445961026552	4.05540389734483
168	20.3	19.0224532412961	1.2775467587039
169	34.3	37.4647554582104	-3.1647554582104
170	16.5	20.1749516327618	-3.67495163276181
171	3	11.6614922824002	-8.66149228240016
172	0.7	8.21931356392329	-7.51931356392329
173	20.5	16.6604097717546	3.83959022824537
174	16.9	16.5774245000356	0.322575499964404
175	25.3	21.3619380224731	3.93806197752688
176	9.9	11.1580427933185	-1.25804279331849
177	13.1	15.9546758307041	-2.85467583070406
178	29.9	28.0190753101463	1.88092468985371
179	22.5	20.6750161404783	1.82498385952166
180	16.9	23.5933458300709	-6.69334583007093
181	26.6	25.0493748179193	1.55062518208068
182	0	4.4835871175848	-4.4835871175848
183	11.5	16.2857695563239	-4.78576955632391
184	12.1	16.8986822108644	-4.79868221086435
185	17.5	17.9262613450789	-0.426261345078887
186	8.6	11.1726328869192	-2.57263288691921
187	23.6	27.488218002501	-3.88821800250099
188	20.4	21.9566805209941	-1.5566805209941
189	20.5	22.654674809194	-2.15467480919396
190	24.4	26.5249786689317	-2.12497866893171
191	11.4	10.3675387306747	1.03246126932527
192	38.1	30.2245077151199	7.87549228488014
193	15.9	17.9412594155828	-2.04125941558284
194	24.7	26.6476434872506	-1.9476434872506
195	22.8	16.8020073817374	5.99799261826257
196	25.5	22.7418451403148	2.75815485968522
197	22	17.0983050413875	4.9016949586125
198	17.7	19.8341699342606	-2.13416993426056
199	6.6	5.78955390753603	0.810446092463967
200	23.6	17.9888278940982	5.61117210590176
201	12.2	15.5688310875904	-3.36883108759042
202	22.1	16.0100965617249	6.08990343827511
203	28.7	27.4592378817029	1.24076211829707
204	6	15.0884068668999	-9.08840686689985
205	34.8	35.7365826167461	-0.936582616746097
206	16.6	15.0590908237717	1.54090917622835
207	32.9	22.8932274765389	10.0067725234611
208	32.8	26.7963129869015	6.00368701309846
209	9.6	13.8041452455772	-4.20414524557716
210	10.8	14.6218896493548	-3.82188964935479
211	7.1	12.8146602256118	-5.71466022561185
212	27.2	25.298109536207	1.90189046379297
213	19.5	15.3975712122928	4.10242878770724
214	18.7	21.4341933681247	-2.73419336812471
215	19.5	14.2421542155849	5.25784578441505
216	47.5	41.1360867068648	6.36391329313517
217	13.6	11.5035407790987	2.09645922090126
218	7.5	9.07253141426621	-1.57253141426621
219	24.5	23.797876497438	0.702123502561987
220	15	17.8976294290144	-2.89762942901444
221	12.4	20.8570326854669	-8.45703268546692
222	26	30.6249637849874	-4.62496378498744
223	11.5	17.3142231577787	-5.81422315777871
224	5.2	16.3686552410365	-11.1686552410365
225	10.9	20.3067119847869	-9.40671198478685
226	12.5	12.9175396179704	-0.417539617970372
227	14.8	19.1049446781936	-4.30494467819357
228	25.2	21.7713669680745	3.42863303192551
229	14.9	17.236779698869	-2.33677969886904
230	17	20.6198279340688	-3.61982793406875
231	10.6	20.0202197764307	-9.42021977643071
232	16.1	21.3502601958206	-5.25026019582062
233	15.4	16.4603312044749	-1.06033120447488
234	26.7	23.391925051944	3.30807494805601
235	25.8	21.1456332741339	4.65436672586607
236	18.6	22.438752950964	-3.83875295096397
237	24.8	21.5126943162467	3.28730568375334
238	27.3	34.4781054582083	-7.17810545820826
239	12.4	14.2821370584909	-1.88213705849092
240	29.9	25.9331965050411	3.9668034949589
241	17	14.9833192464073	2.01668075359274
242	35	36.7603624407249	-1.76036244072494
243	30.4	27.9757388228863	2.42426117711371
244	32.6	32.9378648641109	-0.337864864110928
245	29	29.4170182341806	-0.417018234180571
246	15.2	13.9357603743344	1.26423962566557
247	30.2	30.74713168204	-0.547131682040026
248	11	14.7250283731179	-3.72502837311793
249	33.6	25.8534188596453	7.74658114035471
250	29.3	36.9192667885211	-7.6192667885211
251	26	24.5811687082071	1.41883129179286
252	31.9	27.3994554001923	4.50054459980766

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.3 & 16.1527808735027 & -3.8527808735027 \tabularnewline
2 & 6.1 & 8.84370385843499 & -2.74370385843499 \tabularnewline
3 & 25.3 & 18.5567680591844 & 6.74323194081556 \tabularnewline
4 & 10.4 & 11.9214552413727 & -1.52145524137271 \tabularnewline
5 & 28.7 & 27.291078276092 & 1.40892172390801 \tabularnewline
6 & 20.9 & 16.9403379002368 & 3.9596620997632 \tabularnewline
7 & 19.2 & 16.7388495527999 & 2.46115044720013 \tabularnewline
8 & 12.4 & 13.9159145832453 & -1.51591458324533 \tabularnewline
9 & 4.1 & 9.67746577513297 & -5.57746577513297 \tabularnewline
10 & 11.7 & 10.1835718161123 & 1.51642818388769 \tabularnewline
11 & 7.1 & 9.0172397753499 & -1.9172397753499 \tabularnewline
12 & 7.8 & 12.8674106701886 & -5.06741067018856 \tabularnewline
13 & 20.8 & 17.8253553607477 & 2.97464463925229 \tabularnewline
14 & 21.2 & 25.0509120093389 & -3.8509120093389 \tabularnewline
15 & 22.1 & 24.0839261930635 & -1.98392619306349 \tabularnewline
16 & 20.9 & 22.974522973426 & -2.07452297342601 \tabularnewline
17 & 29 & 23.5383160426835 & 5.46168395731649 \tabularnewline
18 & 22.9 & 19.4482119736127 & 3.45178802638735 \tabularnewline
19 & 16 & 16.7412889924041 & -0.741288992404074 \tabularnewline
20 & 16.5 & 23.1708745480026 & -6.67087454800263 \tabularnewline
21 & 19.1 & 21.1090526029561 & -2.00905260295613 \tabularnewline
22 & 15.2 & 19.8877007794151 & -4.68770077941515 \tabularnewline
23 & 15.6 & 9.55142001673523 & 6.04857998326477 \tabularnewline
24 & 17.7 & 11.1210173638967 & 6.57898263610333 \tabularnewline
25 & 14 & 8.13272944733555 & 5.86727055266445 \tabularnewline
26 & 3.7 & 8.50909673551517 & -4.80909673551517 \tabularnewline
27 & 7.9 & 9.10335612465817 & -1.20335612465817 \tabularnewline
28 & 22.9 & 17.9549559240456 & 4.94504407595442 \tabularnewline
29 & 3.7 & 6.36291763406911 & -2.66291763406911 \tabularnewline
30 & 8.8 & 11.6265136518852 & -2.82651365188516 \tabularnewline
31 & 11.9 & 14.6030169839567 & -2.7030169839567 \tabularnewline
32 & 5.7 & 11.0311632144958 & -5.33116321449585 \tabularnewline
33 & 11.8 & 6.13512290331984 & 5.66487709668016 \tabularnewline
34 & 21.3 & 23.8185171226594 & -2.51851712265942 \tabularnewline
35 & 32.3 & 32.270251629979 & 0.0297483700210498 \tabularnewline
36 & 40.1 & 37.5795849138025 & 2.52041508619753 \tabularnewline
37 & 24.2 & 24.1199576401647 & 0.0800423598352868 \tabularnewline
38 & 28.4 & 21.9034111736215 & 6.49658882637849 \tabularnewline
39 & 35.2 & 44.0348892206514 & -8.8348892206514 \tabularnewline
40 & 32.6 & 32.5253234873826 & 0.0746765126174193 \tabularnewline
41 & 34.5 & 36.6759455720518 & -2.17594557205179 \tabularnewline
42 & 32.9 & 32.534837730462 & 0.36516226953798 \tabularnewline
43 & 31.6 & 34.2348802376012 & -2.63488023760119 \tabularnewline
44 & 32 & 26.3752707892707 & 5.62472921072933 \tabularnewline
45 & 7.7 & 10.9041158347347 & -3.20411583473465 \tabularnewline
46 & 13.9 & 9.95654610857628 & 3.94345389142372 \tabularnewline
47 & 10.8 & 7.77130190782924 & 3.02869809217076 \tabularnewline
48 & 5.6 & 9.54087987928135 & -3.94087987928135 \tabularnewline
49 & 13.6 & 17.8087240189123 & -4.20872401891228 \tabularnewline
50 & 4 & 5.52042426159203 & -1.52042426159203 \tabularnewline
51 & 10.2 & 14.7376710858701 & -4.5376710858701 \tabularnewline
52 & 6.6 & 9.49173918261154 & -2.89173918261154 \tabularnewline
53 & 8 & 14.2232161490253 & -6.22321614902531 \tabularnewline
54 & 6.3 & 10.7942358851282 & -4.49423588512817 \tabularnewline
55 & 3.9 & 7.67501483428857 & -3.77501483428857 \tabularnewline
56 & 22.6 & 23.5568277520263 & -0.956827752026322 \tabularnewline
57 & 20.4 & 25.8571231872631 & -5.45712318726308 \tabularnewline
58 & 28 & 27.6803234657295 & 0.319676534270531 \tabularnewline
59 & 31.5 & 28.6335301315892 & 2.86646986841075 \tabularnewline
60 & 24.6 & 26.2675867967314 & -1.66758679673135 \tabularnewline
61 & 26.1 & 25.3583613773373 & 0.741638622662733 \tabularnewline
62 & 29.8 & 23.5185986747457 & 6.28140132525435 \tabularnewline
63 & 30.7 & 27.4819304361293 & 3.21806956387069 \tabularnewline
64 & 25.8 & 27.238220569014 & -1.43822056901398 \tabularnewline
65 & 32.3 & 30.0937699487517 & 2.20623005124832 \tabularnewline
66 & 30 & 26.2143659822871 & 3.78563401771288 \tabularnewline
67 & 21.5 & 15.4317550835511 & 6.06824491644888 \tabularnewline
68 & 13.8 & 15.6908050845803 & -1.89080508458028 \tabularnewline
69 & 6.3 & 8.72373308212155 & -2.42373308212155 \tabularnewline
70 & 12.9 & 13.8422665868639 & -0.942266586863908 \tabularnewline
71 & 24.3 & 19.5211929410977 & 4.77880705890229 \tabularnewline
72 & 8.8 & 12.7974020670645 & -3.99740206706452 \tabularnewline
73 & 8.5 & 11.0593887554809 & -2.55938875548086 \tabularnewline
74 & 13.5 & 11.6052405516314 & 1.89475944836864 \tabularnewline
75 & 11.8 & 16.7956358731265 & -4.99563587312649 \tabularnewline
76 & 18.5 & 12.1113244702206 & 6.38867552977937 \tabularnewline
77 & 8.8 & 8.9622133190289 & -0.1622133190289 \tabularnewline
78 & 22.2 & 19.3690191542168 & 2.83098084578324 \tabularnewline
79 & 21.5 & 23.1809993587453 & -1.68099935874531 \tabularnewline
80 & 18.8 & 24.8105847410993 & -6.01058474109935 \tabularnewline
81 & 31.4 & 22.1734533713676 & 9.22654662863235 \tabularnewline
82 & 26.8 & 17.915296817829 & 8.88470318217095 \tabularnewline
83 & 18.4 & 22.9669182866307 & -4.56691828663072 \tabularnewline
84 & 27 & 21.2964142716412 & 5.7035857283588 \tabularnewline
85 & 27 & 27.1762996837945 & -0.17629968379453 \tabularnewline
86 & 26.6 & 20.9091399423399 & 5.69086005766009 \tabularnewline
87 & 14.9 & 17.5685386181121 & -2.66853861811206 \tabularnewline
88 & 23.1 & 21.8244498195397 & 1.27555018046026 \tabularnewline
89 & 8.3 & 12.6768186686851 & -4.3768186686851 \tabularnewline
90 & 14.1 & 14.1726277485466 & -0.0726277485466366 \tabularnewline
91 & 20.5 & 21.7048262542423 & -1.20482625424235 \tabularnewline
92 & 18.2 & 17.6395286050088 & 0.560471394991212 \tabularnewline
93 & 8.5 & 11.0409841057249 & -2.54098410572493 \tabularnewline
94 & 24.9 & 21.6946234526603 & 3.2053765473397 \tabularnewline
95 & 9 & 14.7619819523051 & -5.76198195230511 \tabularnewline
96 & 17.4 & 16.2814693633775 & 1.11853063662254 \tabularnewline
97 & 9.6 & 16.8286594768529 & -7.22865947685293 \tabularnewline
98 & 11.3 & 16.0886489423768 & -4.7886489423768 \tabularnewline
99 & 17.8 & 17.83201518129 & -0.0320151812899643 \tabularnewline
100 & 22.2 & 19.1323573861095 & 3.06764261389052 \tabularnewline
101 & 21.2 & 18.4947082022095 & 2.70529179779049 \tabularnewline
102 & 20.4 & 19.9181559590088 & 0.481844040991178 \tabularnewline
103 & 20.1 & 17.2921848917938 & 2.80781510820625 \tabularnewline
104 & 22.3 & 17.1715268119271 & 5.12847318807287 \tabularnewline
105 & 25.4 & 23.8832302188857 & 1.51676978111433 \tabularnewline
106 & 18 & 17.7991025878039 & 0.200897412196126 \tabularnewline
107 & 19.3 & 25.855505521198 & -6.55550552119796 \tabularnewline
108 & 18.3 & 22.2486916414326 & -3.94869164143261 \tabularnewline
109 & 17.3 & 12.4586798226311 & 4.84132017736893 \tabularnewline
110 & 21.4 & 21.0413278180696 & 0.358672181930379 \tabularnewline
111 & 19.7 & 19.2374863421416 & 0.462513657858414 \tabularnewline
112 & 28 & 32.4479213825049 & -4.44792138250494 \tabularnewline
113 & 22.1 & 20.8647753370022 & 1.23522466299777 \tabularnewline
114 & 21.3 & 19.8654581100321 & 1.43454188996792 \tabularnewline
115 & 26.7 & 20.1282218802149 & 6.57177811978511 \tabularnewline
116 & 16.7 & 16.4296732842605 & 0.270326715739459 \tabularnewline
117 & 20.1 & 16.8700960335713 & 3.22990396642873 \tabularnewline
118 & 13.9 & 14.3870160368787 & -0.487016036878727 \tabularnewline
119 & 25.8 & 18.1758899152996 & 7.62411008470042 \tabularnewline
120 & 18.1 & 13.4601408816459 & 4.63985911835407 \tabularnewline
121 & 27.9 & 20.3599924453783 & 7.54000755462167 \tabularnewline
122 & 25.3 & 22.5354064531427 & 2.76459354685733 \tabularnewline
123 & 14.7 & 14.0878701416476 & 0.612129858352424 \tabularnewline
124 & 16 & 17.1093250592991 & -1.10932505929914 \tabularnewline
125 & 13.8 & 15.4686597586299 & -1.6686597586299 \tabularnewline
126 & 17.5 & 20.9649283178635 & -3.46492831786346 \tabularnewline
127 & 27.2 & 21.4814795451094 & 5.71852045489058 \tabularnewline
128 & 17.4 & 8.99568501052695 & 8.40431498947305 \tabularnewline
129 & 20.8 & 18.6554410256316 & 2.14455897436839 \tabularnewline
130 & 14.9 & 14.9957824062943 & -0.0957824062942603 \tabularnewline
131 & 18.1 & 18.3249598860606 & -0.224959886060557 \tabularnewline
132 & 22.7 & 20.1683890756069 & 2.53161092439306 \tabularnewline
133 & 23.6 & 24.7812259038293 & -1.18122590382932 \tabularnewline
134 & 26.1 & 21.065764851441 & 5.03423514855899 \tabularnewline
135 & 24.4 & 16.0470727579408 & 8.35292724205917 \tabularnewline
136 & 27.1 & 26.8328285689513 & 0.267171431048742 \tabularnewline
137 & 21.8 & 16.6463875432494 & 5.15361245675065 \tabularnewline
138 & 29.4 & 26.0494307457112 & 3.35056925428877 \tabularnewline
139 & 22.4 & 17.9023849221525 & 4.4976150778475 \tabularnewline
140 & 20.4 & 28.7693513231312 & -8.36935132313121 \tabularnewline
141 & 24.9 & 21.1901065486414 & 3.70989345135857 \tabularnewline
142 & 18.3 & 21.2874832510073 & -2.98748325100727 \tabularnewline
143 & 23.3 & 18.8969112455707 & 4.40308875442932 \tabularnewline
144 & 9.4 & 5.3879797177854 & 4.0120202822146 \tabularnewline
145 & 10.3 & 9.29350172003732 & 1.00649827996269 \tabularnewline
146 & 14.2 & 12.5257836007293 & 1.67421639927069 \tabularnewline
147 & 19.2 & 22.4900682420478 & -3.29006824204783 \tabularnewline
148 & 29.6 & 22.9712437747845 & 6.62875622521552 \tabularnewline
149 & 5.3 & 6.07669239355771 & -0.776692393557707 \tabularnewline
150 & 25.2 & 26.6853088533332 & -1.48530885333316 \tabularnewline
151 & 9.4 & 8.49938891475277 & 0.900611085247233 \tabularnewline
152 & 19.6 & 21.8567929671057 & -2.25679296710571 \tabularnewline
153 & 10.1 & 4.08395329722268 & 6.01604670277732 \tabularnewline
154 & 16.5 & 16.6070948700781 & -0.107094870078076 \tabularnewline
155 & 21 & 21.5373788453854 & -0.537378845385381 \tabularnewline
156 & 17.3 & 11.0810445274885 & 6.21895547251153 \tabularnewline
157 & 31.2 & 28.5889127394687 & 2.61108726053125 \tabularnewline
158 & 10 & 15.5828292017915 & -5.58282920179146 \tabularnewline
159 & 12.5 & 11.7476191632248 & 0.75238083677518 \tabularnewline
160 & 22.5 & 18.8655545444495 & 3.63444545555045 \tabularnewline
161 & 9.4 & 11.8135612648151 & -2.41356126481514 \tabularnewline
162 & 14.6 & 17.7093322453172 & -3.10933224531718 \tabularnewline
163 & 13 & 15.4787047695703 & -2.47870476957027 \tabularnewline
164 & 15.1 & 15.3029529201382 & -0.202952920138215 \tabularnewline
165 & 27.3 & 27.0150597699644 & 0.284940230035648 \tabularnewline
166 & 19.2 & 17.9335253468734 & 1.26647465312655 \tabularnewline
167 & 21.8 & 17.7445961026552 & 4.05540389734483 \tabularnewline
168 & 20.3 & 19.0224532412961 & 1.2775467587039 \tabularnewline
169 & 34.3 & 37.4647554582104 & -3.1647554582104 \tabularnewline
170 & 16.5 & 20.1749516327618 & -3.67495163276181 \tabularnewline
171 & 3 & 11.6614922824002 & -8.66149228240016 \tabularnewline
172 & 0.7 & 8.21931356392329 & -7.51931356392329 \tabularnewline
173 & 20.5 & 16.6604097717546 & 3.83959022824537 \tabularnewline
174 & 16.9 & 16.5774245000356 & 0.322575499964404 \tabularnewline
175 & 25.3 & 21.3619380224731 & 3.93806197752688 \tabularnewline
176 & 9.9 & 11.1580427933185 & -1.25804279331849 \tabularnewline
177 & 13.1 & 15.9546758307041 & -2.85467583070406 \tabularnewline
178 & 29.9 & 28.0190753101463 & 1.88092468985371 \tabularnewline
179 & 22.5 & 20.6750161404783 & 1.82498385952166 \tabularnewline
180 & 16.9 & 23.5933458300709 & -6.69334583007093 \tabularnewline
181 & 26.6 & 25.0493748179193 & 1.55062518208068 \tabularnewline
182 & 0 & 4.4835871175848 & -4.4835871175848 \tabularnewline
183 & 11.5 & 16.2857695563239 & -4.78576955632391 \tabularnewline
184 & 12.1 & 16.8986822108644 & -4.79868221086435 \tabularnewline
185 & 17.5 & 17.9262613450789 & -0.426261345078887 \tabularnewline
186 & 8.6 & 11.1726328869192 & -2.57263288691921 \tabularnewline
187 & 23.6 & 27.488218002501 & -3.88821800250099 \tabularnewline
188 & 20.4 & 21.9566805209941 & -1.5566805209941 \tabularnewline
189 & 20.5 & 22.654674809194 & -2.15467480919396 \tabularnewline
190 & 24.4 & 26.5249786689317 & -2.12497866893171 \tabularnewline
191 & 11.4 & 10.3675387306747 & 1.03246126932527 \tabularnewline
192 & 38.1 & 30.2245077151199 & 7.87549228488014 \tabularnewline
193 & 15.9 & 17.9412594155828 & -2.04125941558284 \tabularnewline
194 & 24.7 & 26.6476434872506 & -1.9476434872506 \tabularnewline
195 & 22.8 & 16.8020073817374 & 5.99799261826257 \tabularnewline
196 & 25.5 & 22.7418451403148 & 2.75815485968522 \tabularnewline
197 & 22 & 17.0983050413875 & 4.9016949586125 \tabularnewline
198 & 17.7 & 19.8341699342606 & -2.13416993426056 \tabularnewline
199 & 6.6 & 5.78955390753603 & 0.810446092463967 \tabularnewline
200 & 23.6 & 17.9888278940982 & 5.61117210590176 \tabularnewline
201 & 12.2 & 15.5688310875904 & -3.36883108759042 \tabularnewline
202 & 22.1 & 16.0100965617249 & 6.08990343827511 \tabularnewline
203 & 28.7 & 27.4592378817029 & 1.24076211829707 \tabularnewline
204 & 6 & 15.0884068668999 & -9.08840686689985 \tabularnewline
205 & 34.8 & 35.7365826167461 & -0.936582616746097 \tabularnewline
206 & 16.6 & 15.0590908237717 & 1.54090917622835 \tabularnewline
207 & 32.9 & 22.8932274765389 & 10.0067725234611 \tabularnewline
208 & 32.8 & 26.7963129869015 & 6.00368701309846 \tabularnewline
209 & 9.6 & 13.8041452455772 & -4.20414524557716 \tabularnewline
210 & 10.8 & 14.6218896493548 & -3.82188964935479 \tabularnewline
211 & 7.1 & 12.8146602256118 & -5.71466022561185 \tabularnewline
212 & 27.2 & 25.298109536207 & 1.90189046379297 \tabularnewline
213 & 19.5 & 15.3975712122928 & 4.10242878770724 \tabularnewline
214 & 18.7 & 21.4341933681247 & -2.73419336812471 \tabularnewline
215 & 19.5 & 14.2421542155849 & 5.25784578441505 \tabularnewline
216 & 47.5 & 41.1360867068648 & 6.36391329313517 \tabularnewline
217 & 13.6 & 11.5035407790987 & 2.09645922090126 \tabularnewline
218 & 7.5 & 9.07253141426621 & -1.57253141426621 \tabularnewline
219 & 24.5 & 23.797876497438 & 0.702123502561987 \tabularnewline
220 & 15 & 17.8976294290144 & -2.89762942901444 \tabularnewline
221 & 12.4 & 20.8570326854669 & -8.45703268546692 \tabularnewline
222 & 26 & 30.6249637849874 & -4.62496378498744 \tabularnewline
223 & 11.5 & 17.3142231577787 & -5.81422315777871 \tabularnewline
224 & 5.2 & 16.3686552410365 & -11.1686552410365 \tabularnewline
225 & 10.9 & 20.3067119847869 & -9.40671198478685 \tabularnewline
226 & 12.5 & 12.9175396179704 & -0.417539617970372 \tabularnewline
227 & 14.8 & 19.1049446781936 & -4.30494467819357 \tabularnewline
228 & 25.2 & 21.7713669680745 & 3.42863303192551 \tabularnewline
229 & 14.9 & 17.236779698869 & -2.33677969886904 \tabularnewline
230 & 17 & 20.6198279340688 & -3.61982793406875 \tabularnewline
231 & 10.6 & 20.0202197764307 & -9.42021977643071 \tabularnewline
232 & 16.1 & 21.3502601958206 & -5.25026019582062 \tabularnewline
233 & 15.4 & 16.4603312044749 & -1.06033120447488 \tabularnewline
234 & 26.7 & 23.391925051944 & 3.30807494805601 \tabularnewline
235 & 25.8 & 21.1456332741339 & 4.65436672586607 \tabularnewline
236 & 18.6 & 22.438752950964 & -3.83875295096397 \tabularnewline
237 & 24.8 & 21.5126943162467 & 3.28730568375334 \tabularnewline
238 & 27.3 & 34.4781054582083 & -7.17810545820826 \tabularnewline
239 & 12.4 & 14.2821370584909 & -1.88213705849092 \tabularnewline
240 & 29.9 & 25.9331965050411 & 3.9668034949589 \tabularnewline
241 & 17 & 14.9833192464073 & 2.01668075359274 \tabularnewline
242 & 35 & 36.7603624407249 & -1.76036244072494 \tabularnewline
243 & 30.4 & 27.9757388228863 & 2.42426117711371 \tabularnewline
244 & 32.6 & 32.9378648641109 & -0.337864864110928 \tabularnewline
245 & 29 & 29.4170182341806 & -0.417018234180571 \tabularnewline
246 & 15.2 & 13.9357603743344 & 1.26423962566557 \tabularnewline
247 & 30.2 & 30.74713168204 & -0.547131682040026 \tabularnewline
248 & 11 & 14.7250283731179 & -3.72502837311793 \tabularnewline
249 & 33.6 & 25.8534188596453 & 7.74658114035471 \tabularnewline
250 & 29.3 & 36.9192667885211 & -7.6192667885211 \tabularnewline
251 & 26 & 24.5811687082071 & 1.41883129179286 \tabularnewline
252 & 31.9 & 27.3994554001923 & 4.50054459980766 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190472&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.3[/C][C]16.1527808735027[/C][C]-3.8527808735027[/C][/ROW]
[ROW][C]2[/C][C]6.1[/C][C]8.84370385843499[/C][C]-2.74370385843499[/C][/ROW]
[ROW][C]3[/C][C]25.3[/C][C]18.5567680591844[/C][C]6.74323194081556[/C][/ROW]
[ROW][C]4[/C][C]10.4[/C][C]11.9214552413727[/C][C]-1.52145524137271[/C][/ROW]
[ROW][C]5[/C][C]28.7[/C][C]27.291078276092[/C][C]1.40892172390801[/C][/ROW]
[ROW][C]6[/C][C]20.9[/C][C]16.9403379002368[/C][C]3.9596620997632[/C][/ROW]
[ROW][C]7[/C][C]19.2[/C][C]16.7388495527999[/C][C]2.46115044720013[/C][/ROW]
[ROW][C]8[/C][C]12.4[/C][C]13.9159145832453[/C][C]-1.51591458324533[/C][/ROW]
[ROW][C]9[/C][C]4.1[/C][C]9.67746577513297[/C][C]-5.57746577513297[/C][/ROW]
[ROW][C]10[/C][C]11.7[/C][C]10.1835718161123[/C][C]1.51642818388769[/C][/ROW]
[ROW][C]11[/C][C]7.1[/C][C]9.0172397753499[/C][C]-1.9172397753499[/C][/ROW]
[ROW][C]12[/C][C]7.8[/C][C]12.8674106701886[/C][C]-5.06741067018856[/C][/ROW]
[ROW][C]13[/C][C]20.8[/C][C]17.8253553607477[/C][C]2.97464463925229[/C][/ROW]
[ROW][C]14[/C][C]21.2[/C][C]25.0509120093389[/C][C]-3.8509120093389[/C][/ROW]
[ROW][C]15[/C][C]22.1[/C][C]24.0839261930635[/C][C]-1.98392619306349[/C][/ROW]
[ROW][C]16[/C][C]20.9[/C][C]22.974522973426[/C][C]-2.07452297342601[/C][/ROW]
[ROW][C]17[/C][C]29[/C][C]23.5383160426835[/C][C]5.46168395731649[/C][/ROW]
[ROW][C]18[/C][C]22.9[/C][C]19.4482119736127[/C][C]3.45178802638735[/C][/ROW]
[ROW][C]19[/C][C]16[/C][C]16.7412889924041[/C][C]-0.741288992404074[/C][/ROW]
[ROW][C]20[/C][C]16.5[/C][C]23.1708745480026[/C][C]-6.67087454800263[/C][/ROW]
[ROW][C]21[/C][C]19.1[/C][C]21.1090526029561[/C][C]-2.00905260295613[/C][/ROW]
[ROW][C]22[/C][C]15.2[/C][C]19.8877007794151[/C][C]-4.68770077941515[/C][/ROW]
[ROW][C]23[/C][C]15.6[/C][C]9.55142001673523[/C][C]6.04857998326477[/C][/ROW]
[ROW][C]24[/C][C]17.7[/C][C]11.1210173638967[/C][C]6.57898263610333[/C][/ROW]
[ROW][C]25[/C][C]14[/C][C]8.13272944733555[/C][C]5.86727055266445[/C][/ROW]
[ROW][C]26[/C][C]3.7[/C][C]8.50909673551517[/C][C]-4.80909673551517[/C][/ROW]
[ROW][C]27[/C][C]7.9[/C][C]9.10335612465817[/C][C]-1.20335612465817[/C][/ROW]
[ROW][C]28[/C][C]22.9[/C][C]17.9549559240456[/C][C]4.94504407595442[/C][/ROW]
[ROW][C]29[/C][C]3.7[/C][C]6.36291763406911[/C][C]-2.66291763406911[/C][/ROW]
[ROW][C]30[/C][C]8.8[/C][C]11.6265136518852[/C][C]-2.82651365188516[/C][/ROW]
[ROW][C]31[/C][C]11.9[/C][C]14.6030169839567[/C][C]-2.7030169839567[/C][/ROW]
[ROW][C]32[/C][C]5.7[/C][C]11.0311632144958[/C][C]-5.33116321449585[/C][/ROW]
[ROW][C]33[/C][C]11.8[/C][C]6.13512290331984[/C][C]5.66487709668016[/C][/ROW]
[ROW][C]34[/C][C]21.3[/C][C]23.8185171226594[/C][C]-2.51851712265942[/C][/ROW]
[ROW][C]35[/C][C]32.3[/C][C]32.270251629979[/C][C]0.0297483700210498[/C][/ROW]
[ROW][C]36[/C][C]40.1[/C][C]37.5795849138025[/C][C]2.52041508619753[/C][/ROW]
[ROW][C]37[/C][C]24.2[/C][C]24.1199576401647[/C][C]0.0800423598352868[/C][/ROW]
[ROW][C]38[/C][C]28.4[/C][C]21.9034111736215[/C][C]6.49658882637849[/C][/ROW]
[ROW][C]39[/C][C]35.2[/C][C]44.0348892206514[/C][C]-8.8348892206514[/C][/ROW]
[ROW][C]40[/C][C]32.6[/C][C]32.5253234873826[/C][C]0.0746765126174193[/C][/ROW]
[ROW][C]41[/C][C]34.5[/C][C]36.6759455720518[/C][C]-2.17594557205179[/C][/ROW]
[ROW][C]42[/C][C]32.9[/C][C]32.534837730462[/C][C]0.36516226953798[/C][/ROW]
[ROW][C]43[/C][C]31.6[/C][C]34.2348802376012[/C][C]-2.63488023760119[/C][/ROW]
[ROW][C]44[/C][C]32[/C][C]26.3752707892707[/C][C]5.62472921072933[/C][/ROW]
[ROW][C]45[/C][C]7.7[/C][C]10.9041158347347[/C][C]-3.20411583473465[/C][/ROW]
[ROW][C]46[/C][C]13.9[/C][C]9.95654610857628[/C][C]3.94345389142372[/C][/ROW]
[ROW][C]47[/C][C]10.8[/C][C]7.77130190782924[/C][C]3.02869809217076[/C][/ROW]
[ROW][C]48[/C][C]5.6[/C][C]9.54087987928135[/C][C]-3.94087987928135[/C][/ROW]
[ROW][C]49[/C][C]13.6[/C][C]17.8087240189123[/C][C]-4.20872401891228[/C][/ROW]
[ROW][C]50[/C][C]4[/C][C]5.52042426159203[/C][C]-1.52042426159203[/C][/ROW]
[ROW][C]51[/C][C]10.2[/C][C]14.7376710858701[/C][C]-4.5376710858701[/C][/ROW]
[ROW][C]52[/C][C]6.6[/C][C]9.49173918261154[/C][C]-2.89173918261154[/C][/ROW]
[ROW][C]53[/C][C]8[/C][C]14.2232161490253[/C][C]-6.22321614902531[/C][/ROW]
[ROW][C]54[/C][C]6.3[/C][C]10.7942358851282[/C][C]-4.49423588512817[/C][/ROW]
[ROW][C]55[/C][C]3.9[/C][C]7.67501483428857[/C][C]-3.77501483428857[/C][/ROW]
[ROW][C]56[/C][C]22.6[/C][C]23.5568277520263[/C][C]-0.956827752026322[/C][/ROW]
[ROW][C]57[/C][C]20.4[/C][C]25.8571231872631[/C][C]-5.45712318726308[/C][/ROW]
[ROW][C]58[/C][C]28[/C][C]27.6803234657295[/C][C]0.319676534270531[/C][/ROW]
[ROW][C]59[/C][C]31.5[/C][C]28.6335301315892[/C][C]2.86646986841075[/C][/ROW]
[ROW][C]60[/C][C]24.6[/C][C]26.2675867967314[/C][C]-1.66758679673135[/C][/ROW]
[ROW][C]61[/C][C]26.1[/C][C]25.3583613773373[/C][C]0.741638622662733[/C][/ROW]
[ROW][C]62[/C][C]29.8[/C][C]23.5185986747457[/C][C]6.28140132525435[/C][/ROW]
[ROW][C]63[/C][C]30.7[/C][C]27.4819304361293[/C][C]3.21806956387069[/C][/ROW]
[ROW][C]64[/C][C]25.8[/C][C]27.238220569014[/C][C]-1.43822056901398[/C][/ROW]
[ROW][C]65[/C][C]32.3[/C][C]30.0937699487517[/C][C]2.20623005124832[/C][/ROW]
[ROW][C]66[/C][C]30[/C][C]26.2143659822871[/C][C]3.78563401771288[/C][/ROW]
[ROW][C]67[/C][C]21.5[/C][C]15.4317550835511[/C][C]6.06824491644888[/C][/ROW]
[ROW][C]68[/C][C]13.8[/C][C]15.6908050845803[/C][C]-1.89080508458028[/C][/ROW]
[ROW][C]69[/C][C]6.3[/C][C]8.72373308212155[/C][C]-2.42373308212155[/C][/ROW]
[ROW][C]70[/C][C]12.9[/C][C]13.8422665868639[/C][C]-0.942266586863908[/C][/ROW]
[ROW][C]71[/C][C]24.3[/C][C]19.5211929410977[/C][C]4.77880705890229[/C][/ROW]
[ROW][C]72[/C][C]8.8[/C][C]12.7974020670645[/C][C]-3.99740206706452[/C][/ROW]
[ROW][C]73[/C][C]8.5[/C][C]11.0593887554809[/C][C]-2.55938875548086[/C][/ROW]
[ROW][C]74[/C][C]13.5[/C][C]11.6052405516314[/C][C]1.89475944836864[/C][/ROW]
[ROW][C]75[/C][C]11.8[/C][C]16.7956358731265[/C][C]-4.99563587312649[/C][/ROW]
[ROW][C]76[/C][C]18.5[/C][C]12.1113244702206[/C][C]6.38867552977937[/C][/ROW]
[ROW][C]77[/C][C]8.8[/C][C]8.9622133190289[/C][C]-0.1622133190289[/C][/ROW]
[ROW][C]78[/C][C]22.2[/C][C]19.3690191542168[/C][C]2.83098084578324[/C][/ROW]
[ROW][C]79[/C][C]21.5[/C][C]23.1809993587453[/C][C]-1.68099935874531[/C][/ROW]
[ROW][C]80[/C][C]18.8[/C][C]24.8105847410993[/C][C]-6.01058474109935[/C][/ROW]
[ROW][C]81[/C][C]31.4[/C][C]22.1734533713676[/C][C]9.22654662863235[/C][/ROW]
[ROW][C]82[/C][C]26.8[/C][C]17.915296817829[/C][C]8.88470318217095[/C][/ROW]
[ROW][C]83[/C][C]18.4[/C][C]22.9669182866307[/C][C]-4.56691828663072[/C][/ROW]
[ROW][C]84[/C][C]27[/C][C]21.2964142716412[/C][C]5.7035857283588[/C][/ROW]
[ROW][C]85[/C][C]27[/C][C]27.1762996837945[/C][C]-0.17629968379453[/C][/ROW]
[ROW][C]86[/C][C]26.6[/C][C]20.9091399423399[/C][C]5.69086005766009[/C][/ROW]
[ROW][C]87[/C][C]14.9[/C][C]17.5685386181121[/C][C]-2.66853861811206[/C][/ROW]
[ROW][C]88[/C][C]23.1[/C][C]21.8244498195397[/C][C]1.27555018046026[/C][/ROW]
[ROW][C]89[/C][C]8.3[/C][C]12.6768186686851[/C][C]-4.3768186686851[/C][/ROW]
[ROW][C]90[/C][C]14.1[/C][C]14.1726277485466[/C][C]-0.0726277485466366[/C][/ROW]
[ROW][C]91[/C][C]20.5[/C][C]21.7048262542423[/C][C]-1.20482625424235[/C][/ROW]
[ROW][C]92[/C][C]18.2[/C][C]17.6395286050088[/C][C]0.560471394991212[/C][/ROW]
[ROW][C]93[/C][C]8.5[/C][C]11.0409841057249[/C][C]-2.54098410572493[/C][/ROW]
[ROW][C]94[/C][C]24.9[/C][C]21.6946234526603[/C][C]3.2053765473397[/C][/ROW]
[ROW][C]95[/C][C]9[/C][C]14.7619819523051[/C][C]-5.76198195230511[/C][/ROW]
[ROW][C]96[/C][C]17.4[/C][C]16.2814693633775[/C][C]1.11853063662254[/C][/ROW]
[ROW][C]97[/C][C]9.6[/C][C]16.8286594768529[/C][C]-7.22865947685293[/C][/ROW]
[ROW][C]98[/C][C]11.3[/C][C]16.0886489423768[/C][C]-4.7886489423768[/C][/ROW]
[ROW][C]99[/C][C]17.8[/C][C]17.83201518129[/C][C]-0.0320151812899643[/C][/ROW]
[ROW][C]100[/C][C]22.2[/C][C]19.1323573861095[/C][C]3.06764261389052[/C][/ROW]
[ROW][C]101[/C][C]21.2[/C][C]18.4947082022095[/C][C]2.70529179779049[/C][/ROW]
[ROW][C]102[/C][C]20.4[/C][C]19.9181559590088[/C][C]0.481844040991178[/C][/ROW]
[ROW][C]103[/C][C]20.1[/C][C]17.2921848917938[/C][C]2.80781510820625[/C][/ROW]
[ROW][C]104[/C][C]22.3[/C][C]17.1715268119271[/C][C]5.12847318807287[/C][/ROW]
[ROW][C]105[/C][C]25.4[/C][C]23.8832302188857[/C][C]1.51676978111433[/C][/ROW]
[ROW][C]106[/C][C]18[/C][C]17.7991025878039[/C][C]0.200897412196126[/C][/ROW]
[ROW][C]107[/C][C]19.3[/C][C]25.855505521198[/C][C]-6.55550552119796[/C][/ROW]
[ROW][C]108[/C][C]18.3[/C][C]22.2486916414326[/C][C]-3.94869164143261[/C][/ROW]
[ROW][C]109[/C][C]17.3[/C][C]12.4586798226311[/C][C]4.84132017736893[/C][/ROW]
[ROW][C]110[/C][C]21.4[/C][C]21.0413278180696[/C][C]0.358672181930379[/C][/ROW]
[ROW][C]111[/C][C]19.7[/C][C]19.2374863421416[/C][C]0.462513657858414[/C][/ROW]
[ROW][C]112[/C][C]28[/C][C]32.4479213825049[/C][C]-4.44792138250494[/C][/ROW]
[ROW][C]113[/C][C]22.1[/C][C]20.8647753370022[/C][C]1.23522466299777[/C][/ROW]
[ROW][C]114[/C][C]21.3[/C][C]19.8654581100321[/C][C]1.43454188996792[/C][/ROW]
[ROW][C]115[/C][C]26.7[/C][C]20.1282218802149[/C][C]6.57177811978511[/C][/ROW]
[ROW][C]116[/C][C]16.7[/C][C]16.4296732842605[/C][C]0.270326715739459[/C][/ROW]
[ROW][C]117[/C][C]20.1[/C][C]16.8700960335713[/C][C]3.22990396642873[/C][/ROW]
[ROW][C]118[/C][C]13.9[/C][C]14.3870160368787[/C][C]-0.487016036878727[/C][/ROW]
[ROW][C]119[/C][C]25.8[/C][C]18.1758899152996[/C][C]7.62411008470042[/C][/ROW]
[ROW][C]120[/C][C]18.1[/C][C]13.4601408816459[/C][C]4.63985911835407[/C][/ROW]
[ROW][C]121[/C][C]27.9[/C][C]20.3599924453783[/C][C]7.54000755462167[/C][/ROW]
[ROW][C]122[/C][C]25.3[/C][C]22.5354064531427[/C][C]2.76459354685733[/C][/ROW]
[ROW][C]123[/C][C]14.7[/C][C]14.0878701416476[/C][C]0.612129858352424[/C][/ROW]
[ROW][C]124[/C][C]16[/C][C]17.1093250592991[/C][C]-1.10932505929914[/C][/ROW]
[ROW][C]125[/C][C]13.8[/C][C]15.4686597586299[/C][C]-1.6686597586299[/C][/ROW]
[ROW][C]126[/C][C]17.5[/C][C]20.9649283178635[/C][C]-3.46492831786346[/C][/ROW]
[ROW][C]127[/C][C]27.2[/C][C]21.4814795451094[/C][C]5.71852045489058[/C][/ROW]
[ROW][C]128[/C][C]17.4[/C][C]8.99568501052695[/C][C]8.40431498947305[/C][/ROW]
[ROW][C]129[/C][C]20.8[/C][C]18.6554410256316[/C][C]2.14455897436839[/C][/ROW]
[ROW][C]130[/C][C]14.9[/C][C]14.9957824062943[/C][C]-0.0957824062942603[/C][/ROW]
[ROW][C]131[/C][C]18.1[/C][C]18.3249598860606[/C][C]-0.224959886060557[/C][/ROW]
[ROW][C]132[/C][C]22.7[/C][C]20.1683890756069[/C][C]2.53161092439306[/C][/ROW]
[ROW][C]133[/C][C]23.6[/C][C]24.7812259038293[/C][C]-1.18122590382932[/C][/ROW]
[ROW][C]134[/C][C]26.1[/C][C]21.065764851441[/C][C]5.03423514855899[/C][/ROW]
[ROW][C]135[/C][C]24.4[/C][C]16.0470727579408[/C][C]8.35292724205917[/C][/ROW]
[ROW][C]136[/C][C]27.1[/C][C]26.8328285689513[/C][C]0.267171431048742[/C][/ROW]
[ROW][C]137[/C][C]21.8[/C][C]16.6463875432494[/C][C]5.15361245675065[/C][/ROW]
[ROW][C]138[/C][C]29.4[/C][C]26.0494307457112[/C][C]3.35056925428877[/C][/ROW]
[ROW][C]139[/C][C]22.4[/C][C]17.9023849221525[/C][C]4.4976150778475[/C][/ROW]
[ROW][C]140[/C][C]20.4[/C][C]28.7693513231312[/C][C]-8.36935132313121[/C][/ROW]
[ROW][C]141[/C][C]24.9[/C][C]21.1901065486414[/C][C]3.70989345135857[/C][/ROW]
[ROW][C]142[/C][C]18.3[/C][C]21.2874832510073[/C][C]-2.98748325100727[/C][/ROW]
[ROW][C]143[/C][C]23.3[/C][C]18.8969112455707[/C][C]4.40308875442932[/C][/ROW]
[ROW][C]144[/C][C]9.4[/C][C]5.3879797177854[/C][C]4.0120202822146[/C][/ROW]
[ROW][C]145[/C][C]10.3[/C][C]9.29350172003732[/C][C]1.00649827996269[/C][/ROW]
[ROW][C]146[/C][C]14.2[/C][C]12.5257836007293[/C][C]1.67421639927069[/C][/ROW]
[ROW][C]147[/C][C]19.2[/C][C]22.4900682420478[/C][C]-3.29006824204783[/C][/ROW]
[ROW][C]148[/C][C]29.6[/C][C]22.9712437747845[/C][C]6.62875622521552[/C][/ROW]
[ROW][C]149[/C][C]5.3[/C][C]6.07669239355771[/C][C]-0.776692393557707[/C][/ROW]
[ROW][C]150[/C][C]25.2[/C][C]26.6853088533332[/C][C]-1.48530885333316[/C][/ROW]
[ROW][C]151[/C][C]9.4[/C][C]8.49938891475277[/C][C]0.900611085247233[/C][/ROW]
[ROW][C]152[/C][C]19.6[/C][C]21.8567929671057[/C][C]-2.25679296710571[/C][/ROW]
[ROW][C]153[/C][C]10.1[/C][C]4.08395329722268[/C][C]6.01604670277732[/C][/ROW]
[ROW][C]154[/C][C]16.5[/C][C]16.6070948700781[/C][C]-0.107094870078076[/C][/ROW]
[ROW][C]155[/C][C]21[/C][C]21.5373788453854[/C][C]-0.537378845385381[/C][/ROW]
[ROW][C]156[/C][C]17.3[/C][C]11.0810445274885[/C][C]6.21895547251153[/C][/ROW]
[ROW][C]157[/C][C]31.2[/C][C]28.5889127394687[/C][C]2.61108726053125[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]15.5828292017915[/C][C]-5.58282920179146[/C][/ROW]
[ROW][C]159[/C][C]12.5[/C][C]11.7476191632248[/C][C]0.75238083677518[/C][/ROW]
[ROW][C]160[/C][C]22.5[/C][C]18.8655545444495[/C][C]3.63444545555045[/C][/ROW]
[ROW][C]161[/C][C]9.4[/C][C]11.8135612648151[/C][C]-2.41356126481514[/C][/ROW]
[ROW][C]162[/C][C]14.6[/C][C]17.7093322453172[/C][C]-3.10933224531718[/C][/ROW]
[ROW][C]163[/C][C]13[/C][C]15.4787047695703[/C][C]-2.47870476957027[/C][/ROW]
[ROW][C]164[/C][C]15.1[/C][C]15.3029529201382[/C][C]-0.202952920138215[/C][/ROW]
[ROW][C]165[/C][C]27.3[/C][C]27.0150597699644[/C][C]0.284940230035648[/C][/ROW]
[ROW][C]166[/C][C]19.2[/C][C]17.9335253468734[/C][C]1.26647465312655[/C][/ROW]
[ROW][C]167[/C][C]21.8[/C][C]17.7445961026552[/C][C]4.05540389734483[/C][/ROW]
[ROW][C]168[/C][C]20.3[/C][C]19.0224532412961[/C][C]1.2775467587039[/C][/ROW]
[ROW][C]169[/C][C]34.3[/C][C]37.4647554582104[/C][C]-3.1647554582104[/C][/ROW]
[ROW][C]170[/C][C]16.5[/C][C]20.1749516327618[/C][C]-3.67495163276181[/C][/ROW]
[ROW][C]171[/C][C]3[/C][C]11.6614922824002[/C][C]-8.66149228240016[/C][/ROW]
[ROW][C]172[/C][C]0.7[/C][C]8.21931356392329[/C][C]-7.51931356392329[/C][/ROW]
[ROW][C]173[/C][C]20.5[/C][C]16.6604097717546[/C][C]3.83959022824537[/C][/ROW]
[ROW][C]174[/C][C]16.9[/C][C]16.5774245000356[/C][C]0.322575499964404[/C][/ROW]
[ROW][C]175[/C][C]25.3[/C][C]21.3619380224731[/C][C]3.93806197752688[/C][/ROW]
[ROW][C]176[/C][C]9.9[/C][C]11.1580427933185[/C][C]-1.25804279331849[/C][/ROW]
[ROW][C]177[/C][C]13.1[/C][C]15.9546758307041[/C][C]-2.85467583070406[/C][/ROW]
[ROW][C]178[/C][C]29.9[/C][C]28.0190753101463[/C][C]1.88092468985371[/C][/ROW]
[ROW][C]179[/C][C]22.5[/C][C]20.6750161404783[/C][C]1.82498385952166[/C][/ROW]
[ROW][C]180[/C][C]16.9[/C][C]23.5933458300709[/C][C]-6.69334583007093[/C][/ROW]
[ROW][C]181[/C][C]26.6[/C][C]25.0493748179193[/C][C]1.55062518208068[/C][/ROW]
[ROW][C]182[/C][C]0[/C][C]4.4835871175848[/C][C]-4.4835871175848[/C][/ROW]
[ROW][C]183[/C][C]11.5[/C][C]16.2857695563239[/C][C]-4.78576955632391[/C][/ROW]
[ROW][C]184[/C][C]12.1[/C][C]16.8986822108644[/C][C]-4.79868221086435[/C][/ROW]
[ROW][C]185[/C][C]17.5[/C][C]17.9262613450789[/C][C]-0.426261345078887[/C][/ROW]
[ROW][C]186[/C][C]8.6[/C][C]11.1726328869192[/C][C]-2.57263288691921[/C][/ROW]
[ROW][C]187[/C][C]23.6[/C][C]27.488218002501[/C][C]-3.88821800250099[/C][/ROW]
[ROW][C]188[/C][C]20.4[/C][C]21.9566805209941[/C][C]-1.5566805209941[/C][/ROW]
[ROW][C]189[/C][C]20.5[/C][C]22.654674809194[/C][C]-2.15467480919396[/C][/ROW]
[ROW][C]190[/C][C]24.4[/C][C]26.5249786689317[/C][C]-2.12497866893171[/C][/ROW]
[ROW][C]191[/C][C]11.4[/C][C]10.3675387306747[/C][C]1.03246126932527[/C][/ROW]
[ROW][C]192[/C][C]38.1[/C][C]30.2245077151199[/C][C]7.87549228488014[/C][/ROW]
[ROW][C]193[/C][C]15.9[/C][C]17.9412594155828[/C][C]-2.04125941558284[/C][/ROW]
[ROW][C]194[/C][C]24.7[/C][C]26.6476434872506[/C][C]-1.9476434872506[/C][/ROW]
[ROW][C]195[/C][C]22.8[/C][C]16.8020073817374[/C][C]5.99799261826257[/C][/ROW]
[ROW][C]196[/C][C]25.5[/C][C]22.7418451403148[/C][C]2.75815485968522[/C][/ROW]
[ROW][C]197[/C][C]22[/C][C]17.0983050413875[/C][C]4.9016949586125[/C][/ROW]
[ROW][C]198[/C][C]17.7[/C][C]19.8341699342606[/C][C]-2.13416993426056[/C][/ROW]
[ROW][C]199[/C][C]6.6[/C][C]5.78955390753603[/C][C]0.810446092463967[/C][/ROW]
[ROW][C]200[/C][C]23.6[/C][C]17.9888278940982[/C][C]5.61117210590176[/C][/ROW]
[ROW][C]201[/C][C]12.2[/C][C]15.5688310875904[/C][C]-3.36883108759042[/C][/ROW]
[ROW][C]202[/C][C]22.1[/C][C]16.0100965617249[/C][C]6.08990343827511[/C][/ROW]
[ROW][C]203[/C][C]28.7[/C][C]27.4592378817029[/C][C]1.24076211829707[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]15.0884068668999[/C][C]-9.08840686689985[/C][/ROW]
[ROW][C]205[/C][C]34.8[/C][C]35.7365826167461[/C][C]-0.936582616746097[/C][/ROW]
[ROW][C]206[/C][C]16.6[/C][C]15.0590908237717[/C][C]1.54090917622835[/C][/ROW]
[ROW][C]207[/C][C]32.9[/C][C]22.8932274765389[/C][C]10.0067725234611[/C][/ROW]
[ROW][C]208[/C][C]32.8[/C][C]26.7963129869015[/C][C]6.00368701309846[/C][/ROW]
[ROW][C]209[/C][C]9.6[/C][C]13.8041452455772[/C][C]-4.20414524557716[/C][/ROW]
[ROW][C]210[/C][C]10.8[/C][C]14.6218896493548[/C][C]-3.82188964935479[/C][/ROW]
[ROW][C]211[/C][C]7.1[/C][C]12.8146602256118[/C][C]-5.71466022561185[/C][/ROW]
[ROW][C]212[/C][C]27.2[/C][C]25.298109536207[/C][C]1.90189046379297[/C][/ROW]
[ROW][C]213[/C][C]19.5[/C][C]15.3975712122928[/C][C]4.10242878770724[/C][/ROW]
[ROW][C]214[/C][C]18.7[/C][C]21.4341933681247[/C][C]-2.73419336812471[/C][/ROW]
[ROW][C]215[/C][C]19.5[/C][C]14.2421542155849[/C][C]5.25784578441505[/C][/ROW]
[ROW][C]216[/C][C]47.5[/C][C]41.1360867068648[/C][C]6.36391329313517[/C][/ROW]
[ROW][C]217[/C][C]13.6[/C][C]11.5035407790987[/C][C]2.09645922090126[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]9.07253141426621[/C][C]-1.57253141426621[/C][/ROW]
[ROW][C]219[/C][C]24.5[/C][C]23.797876497438[/C][C]0.702123502561987[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]17.8976294290144[/C][C]-2.89762942901444[/C][/ROW]
[ROW][C]221[/C][C]12.4[/C][C]20.8570326854669[/C][C]-8.45703268546692[/C][/ROW]
[ROW][C]222[/C][C]26[/C][C]30.6249637849874[/C][C]-4.62496378498744[/C][/ROW]
[ROW][C]223[/C][C]11.5[/C][C]17.3142231577787[/C][C]-5.81422315777871[/C][/ROW]
[ROW][C]224[/C][C]5.2[/C][C]16.3686552410365[/C][C]-11.1686552410365[/C][/ROW]
[ROW][C]225[/C][C]10.9[/C][C]20.3067119847869[/C][C]-9.40671198478685[/C][/ROW]
[ROW][C]226[/C][C]12.5[/C][C]12.9175396179704[/C][C]-0.417539617970372[/C][/ROW]
[ROW][C]227[/C][C]14.8[/C][C]19.1049446781936[/C][C]-4.30494467819357[/C][/ROW]
[ROW][C]228[/C][C]25.2[/C][C]21.7713669680745[/C][C]3.42863303192551[/C][/ROW]
[ROW][C]229[/C][C]14.9[/C][C]17.236779698869[/C][C]-2.33677969886904[/C][/ROW]
[ROW][C]230[/C][C]17[/C][C]20.6198279340688[/C][C]-3.61982793406875[/C][/ROW]
[ROW][C]231[/C][C]10.6[/C][C]20.0202197764307[/C][C]-9.42021977643071[/C][/ROW]
[ROW][C]232[/C][C]16.1[/C][C]21.3502601958206[/C][C]-5.25026019582062[/C][/ROW]
[ROW][C]233[/C][C]15.4[/C][C]16.4603312044749[/C][C]-1.06033120447488[/C][/ROW]
[ROW][C]234[/C][C]26.7[/C][C]23.391925051944[/C][C]3.30807494805601[/C][/ROW]
[ROW][C]235[/C][C]25.8[/C][C]21.1456332741339[/C][C]4.65436672586607[/C][/ROW]
[ROW][C]236[/C][C]18.6[/C][C]22.438752950964[/C][C]-3.83875295096397[/C][/ROW]
[ROW][C]237[/C][C]24.8[/C][C]21.5126943162467[/C][C]3.28730568375334[/C][/ROW]
[ROW][C]238[/C][C]27.3[/C][C]34.4781054582083[/C][C]-7.17810545820826[/C][/ROW]
[ROW][C]239[/C][C]12.4[/C][C]14.2821370584909[/C][C]-1.88213705849092[/C][/ROW]
[ROW][C]240[/C][C]29.9[/C][C]25.9331965050411[/C][C]3.9668034949589[/C][/ROW]
[ROW][C]241[/C][C]17[/C][C]14.9833192464073[/C][C]2.01668075359274[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]36.7603624407249[/C][C]-1.76036244072494[/C][/ROW]
[ROW][C]243[/C][C]30.4[/C][C]27.9757388228863[/C][C]2.42426117711371[/C][/ROW]
[ROW][C]244[/C][C]32.6[/C][C]32.9378648641109[/C][C]-0.337864864110928[/C][/ROW]
[ROW][C]245[/C][C]29[/C][C]29.4170182341806[/C][C]-0.417018234180571[/C][/ROW]
[ROW][C]246[/C][C]15.2[/C][C]13.9357603743344[/C][C]1.26423962566557[/C][/ROW]
[ROW][C]247[/C][C]30.2[/C][C]30.74713168204[/C][C]-0.547131682040026[/C][/ROW]
[ROW][C]248[/C][C]11[/C][C]14.7250283731179[/C][C]-3.72502837311793[/C][/ROW]
[ROW][C]249[/C][C]33.6[/C][C]25.8534188596453[/C][C]7.74658114035471[/C][/ROW]
[ROW][C]250[/C][C]29.3[/C][C]36.9192667885211[/C][C]-7.6192667885211[/C][/ROW]
[ROW][C]251[/C][C]26[/C][C]24.5811687082071[/C][C]1.41883129179286[/C][/ROW]
[ROW][C]252[/C][C]31.9[/C][C]27.3994554001923[/C][C]4.50054459980766[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190472&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190472&T=4

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.3	16.1527808735027	-3.8527808735027
2	6.1	8.84370385843499	-2.74370385843499
3	25.3	18.5567680591844	6.74323194081556
4	10.4	11.9214552413727	-1.52145524137271
5	28.7	27.291078276092	1.40892172390801
6	20.9	16.9403379002368	3.9596620997632
7	19.2	16.7388495527999	2.46115044720013
8	12.4	13.9159145832453	-1.51591458324533
9	4.1	9.67746577513297	-5.57746577513297
10	11.7	10.1835718161123	1.51642818388769
11	7.1	9.0172397753499	-1.9172397753499
12	7.8	12.8674106701886	-5.06741067018856
13	20.8	17.8253553607477	2.97464463925229
14	21.2	25.0509120093389	-3.8509120093389
15	22.1	24.0839261930635	-1.98392619306349
16	20.9	22.974522973426	-2.07452297342601
17	29	23.5383160426835	5.46168395731649
18	22.9	19.4482119736127	3.45178802638735
19	16	16.7412889924041	-0.741288992404074
20	16.5	23.1708745480026	-6.67087454800263
21	19.1	21.1090526029561	-2.00905260295613
22	15.2	19.8877007794151	-4.68770077941515
23	15.6	9.55142001673523	6.04857998326477
24	17.7	11.1210173638967	6.57898263610333
25	14	8.13272944733555	5.86727055266445
26	3.7	8.50909673551517	-4.80909673551517
27	7.9	9.10335612465817	-1.20335612465817
28	22.9	17.9549559240456	4.94504407595442
29	3.7	6.36291763406911	-2.66291763406911
30	8.8	11.6265136518852	-2.82651365188516
31	11.9	14.6030169839567	-2.7030169839567
32	5.7	11.0311632144958	-5.33116321449585
33	11.8	6.13512290331984	5.66487709668016
34	21.3	23.8185171226594	-2.51851712265942
35	32.3	32.270251629979	0.0297483700210498
36	40.1	37.5795849138025	2.52041508619753
37	24.2	24.1199576401647	0.0800423598352868
38	28.4	21.9034111736215	6.49658882637849
39	35.2	44.0348892206514	-8.8348892206514
40	32.6	32.5253234873826	0.0746765126174193
41	34.5	36.6759455720518	-2.17594557205179
42	32.9	32.534837730462	0.36516226953798
43	31.6	34.2348802376012	-2.63488023760119
44	32	26.3752707892707	5.62472921072933
45	7.7	10.9041158347347	-3.20411583473465
46	13.9	9.95654610857628	3.94345389142372
47	10.8	7.77130190782924	3.02869809217076
48	5.6	9.54087987928135	-3.94087987928135
49	13.6	17.8087240189123	-4.20872401891228
50	4	5.52042426159203	-1.52042426159203
51	10.2	14.7376710858701	-4.5376710858701
52	6.6	9.49173918261154	-2.89173918261154
53	8	14.2232161490253	-6.22321614902531
54	6.3	10.7942358851282	-4.49423588512817
55	3.9	7.67501483428857	-3.77501483428857
56	22.6	23.5568277520263	-0.956827752026322
57	20.4	25.8571231872631	-5.45712318726308
58	28	27.6803234657295	0.319676534270531
59	31.5	28.6335301315892	2.86646986841075
60	24.6	26.2675867967314	-1.66758679673135
61	26.1	25.3583613773373	0.741638622662733
62	29.8	23.5185986747457	6.28140132525435
63	30.7	27.4819304361293	3.21806956387069
64	25.8	27.238220569014	-1.43822056901398
65	32.3	30.0937699487517	2.20623005124832
66	30	26.2143659822871	3.78563401771288
67	21.5	15.4317550835511	6.06824491644888
68	13.8	15.6908050845803	-1.89080508458028
69	6.3	8.72373308212155	-2.42373308212155
70	12.9	13.8422665868639	-0.942266586863908
71	24.3	19.5211929410977	4.77880705890229
72	8.8	12.7974020670645	-3.99740206706452
73	8.5	11.0593887554809	-2.55938875548086
74	13.5	11.6052405516314	1.89475944836864
75	11.8	16.7956358731265	-4.99563587312649
76	18.5	12.1113244702206	6.38867552977937
77	8.8	8.9622133190289	-0.1622133190289
78	22.2	19.3690191542168	2.83098084578324
79	21.5	23.1809993587453	-1.68099935874531
80	18.8	24.8105847410993	-6.01058474109935
81	31.4	22.1734533713676	9.22654662863235
82	26.8	17.915296817829	8.88470318217095
83	18.4	22.9669182866307	-4.56691828663072
84	27	21.2964142716412	5.7035857283588
85	27	27.1762996837945	-0.17629968379453
86	26.6	20.9091399423399	5.69086005766009
87	14.9	17.5685386181121	-2.66853861811206
88	23.1	21.8244498195397	1.27555018046026
89	8.3	12.6768186686851	-4.3768186686851
90	14.1	14.1726277485466	-0.0726277485466366
91	20.5	21.7048262542423	-1.20482625424235
92	18.2	17.6395286050088	0.560471394991212
93	8.5	11.0409841057249	-2.54098410572493
94	24.9	21.6946234526603	3.2053765473397
95	9	14.7619819523051	-5.76198195230511
96	17.4	16.2814693633775	1.11853063662254
97	9.6	16.8286594768529	-7.22865947685293
98	11.3	16.0886489423768	-4.7886489423768
99	17.8	17.83201518129	-0.0320151812899643
100	22.2	19.1323573861095	3.06764261389052
101	21.2	18.4947082022095	2.70529179779049
102	20.4	19.9181559590088	0.481844040991178
103	20.1	17.2921848917938	2.80781510820625
104	22.3	17.1715268119271	5.12847318807287
105	25.4	23.8832302188857	1.51676978111433
106	18	17.7991025878039	0.200897412196126
107	19.3	25.855505521198	-6.55550552119796
108	18.3	22.2486916414326	-3.94869164143261
109	17.3	12.4586798226311	4.84132017736893
110	21.4	21.0413278180696	0.358672181930379
111	19.7	19.2374863421416	0.462513657858414
112	28	32.4479213825049	-4.44792138250494
113	22.1	20.8647753370022	1.23522466299777
114	21.3	19.8654581100321	1.43454188996792
115	26.7	20.1282218802149	6.57177811978511
116	16.7	16.4296732842605	0.270326715739459
117	20.1	16.8700960335713	3.22990396642873
118	13.9	14.3870160368787	-0.487016036878727
119	25.8	18.1758899152996	7.62411008470042
120	18.1	13.4601408816459	4.63985911835407
121	27.9	20.3599924453783	7.54000755462167
122	25.3	22.5354064531427	2.76459354685733
123	14.7	14.0878701416476	0.612129858352424
124	16	17.1093250592991	-1.10932505929914
125	13.8	15.4686597586299	-1.6686597586299
126	17.5	20.9649283178635	-3.46492831786346
127	27.2	21.4814795451094	5.71852045489058
128	17.4	8.99568501052695	8.40431498947305
129	20.8	18.6554410256316	2.14455897436839
130	14.9	14.9957824062943	-0.0957824062942603
131	18.1	18.3249598860606	-0.224959886060557
132	22.7	20.1683890756069	2.53161092439306
133	23.6	24.7812259038293	-1.18122590382932
134	26.1	21.065764851441	5.03423514855899
135	24.4	16.0470727579408	8.35292724205917
136	27.1	26.8328285689513	0.267171431048742
137	21.8	16.6463875432494	5.15361245675065
138	29.4	26.0494307457112	3.35056925428877
139	22.4	17.9023849221525	4.4976150778475
140	20.4	28.7693513231312	-8.36935132313121
141	24.9	21.1901065486414	3.70989345135857
142	18.3	21.2874832510073	-2.98748325100727
143	23.3	18.8969112455707	4.40308875442932
144	9.4	5.3879797177854	4.0120202822146
145	10.3	9.29350172003732	1.00649827996269
146	14.2	12.5257836007293	1.67421639927069
147	19.2	22.4900682420478	-3.29006824204783
148	29.6	22.9712437747845	6.62875622521552
149	5.3	6.07669239355771	-0.776692393557707
150	25.2	26.6853088533332	-1.48530885333316
151	9.4	8.49938891475277	0.900611085247233
152	19.6	21.8567929671057	-2.25679296710571
153	10.1	4.08395329722268	6.01604670277732
154	16.5	16.6070948700781	-0.107094870078076
155	21	21.5373788453854	-0.537378845385381
156	17.3	11.0810445274885	6.21895547251153
157	31.2	28.5889127394687	2.61108726053125
158	10	15.5828292017915	-5.58282920179146
159	12.5	11.7476191632248	0.75238083677518
160	22.5	18.8655545444495	3.63444545555045
161	9.4	11.8135612648151	-2.41356126481514
162	14.6	17.7093322453172	-3.10933224531718
163	13	15.4787047695703	-2.47870476957027
164	15.1	15.3029529201382	-0.202952920138215
165	27.3	27.0150597699644	0.284940230035648
166	19.2	17.9335253468734	1.26647465312655
167	21.8	17.7445961026552	4.05540389734483
168	20.3	19.0224532412961	1.2775467587039
169	34.3	37.4647554582104	-3.1647554582104
170	16.5	20.1749516327618	-3.67495163276181
171	3	11.6614922824002	-8.66149228240016
172	0.7	8.21931356392329	-7.51931356392329
173	20.5	16.6604097717546	3.83959022824537
174	16.9	16.5774245000356	0.322575499964404
175	25.3	21.3619380224731	3.93806197752688
176	9.9	11.1580427933185	-1.25804279331849
177	13.1	15.9546758307041	-2.85467583070406
178	29.9	28.0190753101463	1.88092468985371
179	22.5	20.6750161404783	1.82498385952166
180	16.9	23.5933458300709	-6.69334583007093
181	26.6	25.0493748179193	1.55062518208068
182	0	4.4835871175848	-4.4835871175848
183	11.5	16.2857695563239	-4.78576955632391
184	12.1	16.8986822108644	-4.79868221086435
185	17.5	17.9262613450789	-0.426261345078887
186	8.6	11.1726328869192	-2.57263288691921
187	23.6	27.488218002501	-3.88821800250099
188	20.4	21.9566805209941	-1.5566805209941
189	20.5	22.654674809194	-2.15467480919396
190	24.4	26.5249786689317	-2.12497866893171
191	11.4	10.3675387306747	1.03246126932527
192	38.1	30.2245077151199	7.87549228488014
193	15.9	17.9412594155828	-2.04125941558284
194	24.7	26.6476434872506	-1.9476434872506
195	22.8	16.8020073817374	5.99799261826257
196	25.5	22.7418451403148	2.75815485968522
197	22	17.0983050413875	4.9016949586125
198	17.7	19.8341699342606	-2.13416993426056
199	6.6	5.78955390753603	0.810446092463967
200	23.6	17.9888278940982	5.61117210590176
201	12.2	15.5688310875904	-3.36883108759042
202	22.1	16.0100965617249	6.08990343827511
203	28.7	27.4592378817029	1.24076211829707
204	6	15.0884068668999	-9.08840686689985
205	34.8	35.7365826167461	-0.936582616746097
206	16.6	15.0590908237717	1.54090917622835
207	32.9	22.8932274765389	10.0067725234611
208	32.8	26.7963129869015	6.00368701309846
209	9.6	13.8041452455772	-4.20414524557716
210	10.8	14.6218896493548	-3.82188964935479
211	7.1	12.8146602256118	-5.71466022561185
212	27.2	25.298109536207	1.90189046379297
213	19.5	15.3975712122928	4.10242878770724
214	18.7	21.4341933681247	-2.73419336812471
215	19.5	14.2421542155849	5.25784578441505
216	47.5	41.1360867068648	6.36391329313517
217	13.6	11.5035407790987	2.09645922090126
218	7.5	9.07253141426621	-1.57253141426621
219	24.5	23.797876497438	0.702123502561987
220	15	17.8976294290144	-2.89762942901444
221	12.4	20.8570326854669	-8.45703268546692
222	26	30.6249637849874	-4.62496378498744
223	11.5	17.3142231577787	-5.81422315777871
224	5.2	16.3686552410365	-11.1686552410365
225	10.9	20.3067119847869	-9.40671198478685
226	12.5	12.9175396179704	-0.417539617970372
227	14.8	19.1049446781936	-4.30494467819357
228	25.2	21.7713669680745	3.42863303192551
229	14.9	17.236779698869	-2.33677969886904
230	17	20.6198279340688	-3.61982793406875
231	10.6	20.0202197764307	-9.42021977643071
232	16.1	21.3502601958206	-5.25026019582062
233	15.4	16.4603312044749	-1.06033120447488
234	26.7	23.391925051944	3.30807494805601
235	25.8	21.1456332741339	4.65436672586607
236	18.6	22.438752950964	-3.83875295096397
237	24.8	21.5126943162467	3.28730568375334
238	27.3	34.4781054582083	-7.17810545820826
239	12.4	14.2821370584909	-1.88213705849092
240	29.9	25.9331965050411	3.9668034949589
241	17	14.9833192464073	2.01668075359274
242	35	36.7603624407249	-1.76036244072494
243	30.4	27.9757388228863	2.42426117711371
244	32.6	32.9378648641109	-0.337864864110928
245	29	29.4170182341806	-0.417018234180571
246	15.2	13.9357603743344	1.26423962566557
247	30.2	30.74713168204	-0.547131682040026
248	11	14.7250283731179	-3.72502837311793
249	33.6	25.8534188596453	7.74658114035471
250	29.3	36.9192667885211	-7.6192667885211
251	26	24.5811687082071	1.41883129179286
252	31.9	27.3994554001923	4.50054459980766

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
17	0.0875608272989696	0.175121654597939	0.91243917270103
18	0.282106937241268	0.564213874482536	0.717893062758732
19	0.223581484759997	0.447162969519994	0.776418515240003
20	0.254220148570916	0.508440297141832	0.745779851429084
21	0.190438483090145	0.38087696618029	0.809561516909855
22	0.532662560846844	0.934674878306312	0.467337439153156
23	0.562507113283741	0.874985773432518	0.437492886716259
24	0.562892516385805	0.87421496722839	0.437107483614195
25	0.478428651312634	0.956857302625268	0.521571348687366
26	0.591250476191283	0.817499047617434	0.408749523808717
27	0.517031783125763	0.965936433748473	0.482968216874237
28	0.613372758960775	0.773254482078451	0.386627241039225
29	0.565768542050577	0.868462915898847	0.434231457949423
30	0.548448906241801	0.903102187516398	0.451551093758199
31	0.493656031404474	0.987312062808948	0.506343968595526
32	0.582271584439543	0.835456831120914	0.417728415560457
33	0.56759574207652	0.86480851584696	0.43240425792348
34	0.569092785968105	0.861814428063789	0.430907214031895
35	0.505080250572285	0.98983949885543	0.494919749427715
36	0.464960648580599	0.929921297161198	0.535039351419401
37	0.417162569738874	0.834325139477747	0.582837430261127
38	0.384951077351747	0.769902154703493	0.615048922648253
39	0.512197880937745	0.97560423812451	0.487802119062255
40	0.452500605698638	0.905001211397275	0.547499394301362
41	0.405249131518417	0.810498263036834	0.594750868481583
42	0.438156894770931	0.876313789541862	0.561843105229069
43	0.408501101828578	0.817002203657155	0.591498898171422
44	0.456591779959702	0.913183559919404	0.543408220040298
45	0.446625117853909	0.893250235707818	0.553374882146091
46	0.409654451500503	0.819308903001006	0.590345548499497
47	0.365651400127452	0.731302800254904	0.634348599872548
48	0.358133741208017	0.716267482416033	0.641866258791983
49	0.347080679638731	0.694161359277463	0.652919320361269
50	0.327298415305346	0.654596830610691	0.672701584694654
51	0.348437216225556	0.696874432451113	0.651562783774444
52	0.313643518632375	0.627287037264749	0.686356481367626
53	0.295808354905858	0.591616709811717	0.704191645094142
54	0.301900719711694	0.603801439423388	0.698099280288306
55	0.283561781289988	0.567123562579977	0.716438218710012
56	0.285115422129288	0.570230844258576	0.714884577870712
57	0.304742752884724	0.609485505769449	0.695257247115276
58	0.28302689384604	0.56605378769208	0.71697310615396
59	0.270084611287896	0.540169222575792	0.729915388712104
60	0.235777259595732	0.471554519191464	0.764222740404268
61	0.212094914305745	0.424189828611489	0.787905085694255
62	0.230175573662175	0.460351147324349	0.769824426337825
63	0.210157861318919	0.420315722637837	0.789842138681081
64	0.184443440959128	0.368886881918256	0.815556559040872
65	0.15706335871021	0.31412671742042	0.84293664128979
66	0.14397290692389	0.287945813847781	0.85602709307611
67	0.162569116093629	0.325138232187258	0.837430883906371
68	0.138087747606039	0.276175495212077	0.861912252393961
69	0.121712306743581	0.243424613487162	0.878287693256419
70	0.101627535052303	0.203255070104606	0.898372464947697
71	0.114281916163938	0.228563832327875	0.885718083836062
72	0.124476202244355	0.248952404488711	0.875523797755645
73	0.108351811388254	0.216703622776509	0.891648188611746
74	0.0961097724236941	0.192219544847388	0.903890227576306
75	0.123863808459142	0.247727616918284	0.876136191540858
76	0.157226386844115	0.314452773688229	0.842773613155885
77	0.137077226229854	0.274154452459707	0.862922773770146
78	0.14215557113224	0.284311142264479	0.85784442886776
79	0.122166365202121	0.244332730404243	0.877833634797879
80	0.155354620655096	0.310709241310191	0.844645379344904
81	0.279570046544095	0.55914009308819	0.720429953455905
82	0.406072138535853	0.812144277071707	0.593927861464147
83	0.410949919662445	0.821899839324889	0.589050080337555
84	0.425683286336286	0.851366572672572	0.574316713663714
85	0.391411701879736	0.782823403759472	0.608588298120264
86	0.396281328653869	0.792562657307738	0.603718671346131
87	0.386268060332757	0.772536120665513	0.613731939667243
88	0.38472856767204	0.76945713534408	0.61527143232796
89	0.409363338032589	0.818726676065177	0.590636661967411
90	0.380521496325609	0.761042992651218	0.619478503674391
91	0.345948841615279	0.691897683230558	0.654051158384721
92	0.310900718721392	0.621801437442783	0.689099281278608
93	0.288863493203198	0.577726986406395	0.711136506796803
94	0.27841616370193	0.55683232740386	0.72158383629807
95	0.299351273637264	0.598702547274529	0.700648726362736
96	0.276350786701147	0.552701573402295	0.723649213298853
97	0.337666022783023	0.675332045566046	0.662333977216977
98	0.37627423782725	0.752548475654499	0.62372576217275
99	0.339824993690515	0.679649987381031	0.660175006309485
100	0.328612390541984	0.657224781083967	0.671387609458016
101	0.310935010929757	0.621870021859514	0.689064989070243
102	0.277961832556004	0.555923665112008	0.722038167443996
103	0.258763471439029	0.517526942878057	0.741236528560971
104	0.273061251504288	0.546122503008576	0.726938748495712
105	0.245682048424628	0.491364096849255	0.754317951575372
106	0.216934280867781	0.433868561735562	0.783065719132219
107	0.257717461627106	0.515434923254212	0.742282538372894
108	0.253174408847887	0.506348817695774	0.746825591152113
109	0.264079737290579	0.528159474581157	0.735920262709421
110	0.236694604389379	0.473389208778757	0.763305395610621
111	0.208627560408974	0.417255120817948	0.791372439591026
112	0.211644189886584	0.423288379773169	0.788355810113415
113	0.188403086030407	0.376806172060814	0.811596913969593
114	0.166582415903985	0.333164831807971	0.833417584096015
115	0.205124111341278	0.410248222682556	0.794875888658722
116	0.179512853245672	0.359025706491344	0.820487146754328
117	0.168957953878318	0.337915907756637	0.831042046121682
118	0.146280010586183	0.292560021172367	0.853719989413817
119	0.20099741835479	0.401994836709579	0.79900258164521
120	0.205715578216519	0.411431156433038	0.794284421783481
121	0.267269987072646	0.534539974145293	0.732730012927354
122	0.249597166503272	0.499194333006543	0.750402833496728
123	0.221458421990017	0.442916843980035	0.778541578009983
124	0.196626684388149	0.393253368776297	0.803373315611851
125	0.175403869509043	0.350807739018087	0.824596130490957
126	0.168136723012548	0.336273446025096	0.831863276987452
127	0.183619568523219	0.367239137046439	0.816380431476781
128	0.260208584627282	0.520417169254565	0.739791415372718
129	0.235767315905588	0.471534631811175	0.764232684094412
130	0.207651204653826	0.415302409307652	0.792348795346174
131	0.182897441541156	0.365794883082312	0.817102558458844
132	0.167230138068033	0.334460276136065	0.832769861931967
133	0.147599616348673	0.295199232697347	0.852400383651327
134	0.154467187918553	0.308934375837107	0.845532812081446
135	0.220642857543353	0.441285715086707	0.779357142456647
136	0.193597461014966	0.387194922029931	0.806402538985034
137	0.206519333700572	0.413038667401143	0.793480666299428
138	0.202238268267051	0.404476536534102	0.797761731732949
139	0.209154764122716	0.418309528245431	0.790845235877284
140	0.291289218070134	0.582578436140267	0.708710781929866
141	0.276879165862588	0.553758331725177	0.723120834137412
142	0.259539384208689	0.519078768417378	0.740460615791311
143	0.26605059426673	0.532101188533459	0.73394940573327
144	0.2676050051957	0.5352100103914	0.7323949948043
145	0.238554933905224	0.477109867810448	0.761445066094776
146	0.215348402928567	0.430696805857134	0.784651597071433
147	0.201397823556532	0.402795647113064	0.798602176443468
148	0.250455828587229	0.500911657174459	0.749544171412771
149	0.221590861622753	0.443181723245506	0.778409138377247
150	0.198390947166996	0.396781894333991	0.801609052833004
151	0.174853507240884	0.349707014481767	0.825146492759116
152	0.161953625514898	0.323907251029796	0.838046374485102
153	0.206645042538106	0.413290085076211	0.793354957461895
154	0.18044087486882	0.36088174973764	0.81955912513118
155	0.158853838790637	0.317707677581274	0.841146161209363
156	0.181143468374797	0.362286936749594	0.818856531625203
157	0.170978159639621	0.341956319279242	0.829021840360379
158	0.180211636402779	0.360423272805559	0.819788363597221
159	0.177912448145475	0.35582489629095	0.822087551854525
160	0.186717440687796	0.373434881375591	0.813282559312204
161	0.167428750633697	0.334857501267395	0.832571249366303
162	0.152831664513891	0.305663329027781	0.847168335486109
163	0.1382569927338	0.2765139854676	0.8617430072662
164	0.117860450459271	0.235720900918542	0.882139549540729
165	0.0993841546286103	0.198768309257221	0.90061584537139
166	0.0883537262316658	0.176707452463332	0.911646273768334
167	0.0915625544508629	0.183125108901726	0.908437445549137
168	0.0769741146497626	0.153948229299525	0.923025885350237
169	0.0693229213350126	0.138645842670025	0.930677078664987
170	0.0631599049879288	0.126319809975858	0.936840095012071
171	0.0994522449809676	0.198904489961935	0.900547755019032
172	0.121916247378268	0.243832494756537	0.878083752621732
173	0.118318419191081	0.236636838382161	0.881681580808919
174	0.099384112907176	0.198768225814352	0.900615887092824
175	0.104436134732465	0.20887226946493	0.895563865267535
176	0.0901627706307275	0.180325541261455	0.909837229369272
177	0.0810741989271214	0.162148397854243	0.918925801072879
178	0.0670919937086403	0.134183987417281	0.93290800629136
179	0.0615937513306581	0.123187502661316	0.938406248669342
180	0.085985341200015	0.17197068240003	0.914014658799985
181	0.0721547475541638	0.144309495108328	0.927845252445836
182	0.0700396417867803	0.140079283573561	0.92996035821322
183	0.0654495079702405	0.130899015940481	0.934550492029759
184	0.0705612017101714	0.141122403420343	0.929438798289829
185	0.0574509767544793	0.114901953508959	0.942549023245521
186	0.0636931136676713	0.127386227335343	0.936306886332329
187	0.0610615023844239	0.122123004768848	0.938938497615576
188	0.0526514965137009	0.105302993027402	0.947348503486299
189	0.0430604868367685	0.0861209736735371	0.956939513163231
190	0.044027454535193	0.088054909070386	0.955972545464807
191	0.0346479625077369	0.0692959250154737	0.965352037492263
192	0.0411501224457151	0.0823002448914301	0.958849877554285
193	0.0340197474943351	0.0680394949886702	0.965980252505665
194	0.0293819800837546	0.0587639601675091	0.970618019916245
195	0.0379530489212947	0.0759060978425894	0.962046951078705
196	0.0313489198067978	0.0626978396135957	0.968651080193202
197	0.0527616256386792	0.105523251277358	0.947238374361321
198	0.0441222929612166	0.0882445859224332	0.955877707038783
199	0.0348929353282485	0.069785870656497	0.965107064671752
200	0.0936016809706487	0.187203361941297	0.906398319029351
201	0.078337363326737	0.156674726653474	0.921662636673263
202	0.100650208872228	0.201300417744457	0.899349791127771
203	0.113112595189423	0.226225190378846	0.886887404810577
204	0.198096603815308	0.396193207630616	0.801903396184692
205	0.165595848058	0.331191696116001	0.834404151942
206	0.191086568023615	0.382173136047231	0.808913431976385
207	0.508687653528392	0.982624692943215	0.491312346471608
208	0.612182963246249	0.775634073507502	0.387817036753751
209	0.567770077806846	0.864459844386308	0.432229922193154
210	0.517642559899437	0.964714880201126	0.482357440100563
211	0.476431580130227	0.952863160260453	0.523568419869773
212	0.428179948228018	0.856359896456035	0.571820051771982
213	0.428350747254406	0.856701494508812	0.571649252745594
214	0.385864812858538	0.771729625717076	0.614135187141462
215	0.448036914349905	0.89607382869981	0.551963085650095
216	0.705578386672887	0.588843226654227	0.294421613327113
217	0.653631976671445	0.692736046657111	0.346368023328555
218	0.591838467494697	0.816323065010606	0.408161532505303
219	0.561599211543044	0.876801576913912	0.438400788456956
220	0.53100072943507	0.93799854112986	0.46899927056493
221	0.492963299074752	0.985926598149503	0.507036700925248
222	0.437712778287463	0.875425556574925	0.562287221712537
223	0.421111557776988	0.842223115553976	0.578888442223012
224	0.618304597770255	0.763390804459491	0.381695402229745
225	0.712317837603984	0.575364324792033	0.287682162396016
226	0.640806339158418	0.718387321683164	0.359193660841582
227	0.561619156977362	0.876761686045277	0.438380843022639
228	0.707950011879156	0.584099976241689	0.292049988120844
229	0.664424471345979	0.671151057308042	0.335575528654021
230	0.568701930557582	0.862596138884835	0.431298069442418
231	0.476056966344436	0.952113932688873	0.523943033655564
232	0.367216093178731	0.734432186357462	0.632783906821269
233	0.270937609662818	0.541875219325635	0.729062390337182
234	0.631735814951489	0.736528370097022	0.368264185048511
235	0.603028854506466	0.793942290987068	0.396971145493534

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
17 & 0.0875608272989696 & 0.175121654597939 & 0.91243917270103 \tabularnewline
18 & 0.282106937241268 & 0.564213874482536 & 0.717893062758732 \tabularnewline
19 & 0.223581484759997 & 0.447162969519994 & 0.776418515240003 \tabularnewline
20 & 0.254220148570916 & 0.508440297141832 & 0.745779851429084 \tabularnewline
21 & 0.190438483090145 & 0.38087696618029 & 0.809561516909855 \tabularnewline
22 & 0.532662560846844 & 0.934674878306312 & 0.467337439153156 \tabularnewline
23 & 0.562507113283741 & 0.874985773432518 & 0.437492886716259 \tabularnewline
24 & 0.562892516385805 & 0.87421496722839 & 0.437107483614195 \tabularnewline
25 & 0.478428651312634 & 0.956857302625268 & 0.521571348687366 \tabularnewline
26 & 0.591250476191283 & 0.817499047617434 & 0.408749523808717 \tabularnewline
27 & 0.517031783125763 & 0.965936433748473 & 0.482968216874237 \tabularnewline
28 & 0.613372758960775 & 0.773254482078451 & 0.386627241039225 \tabularnewline
29 & 0.565768542050577 & 0.868462915898847 & 0.434231457949423 \tabularnewline
30 & 0.548448906241801 & 0.903102187516398 & 0.451551093758199 \tabularnewline
31 & 0.493656031404474 & 0.987312062808948 & 0.506343968595526 \tabularnewline
32 & 0.582271584439543 & 0.835456831120914 & 0.417728415560457 \tabularnewline
33 & 0.56759574207652 & 0.86480851584696 & 0.43240425792348 \tabularnewline
34 & 0.569092785968105 & 0.861814428063789 & 0.430907214031895 \tabularnewline
35 & 0.505080250572285 & 0.98983949885543 & 0.494919749427715 \tabularnewline
36 & 0.464960648580599 & 0.929921297161198 & 0.535039351419401 \tabularnewline
37 & 0.417162569738874 & 0.834325139477747 & 0.582837430261127 \tabularnewline
38 & 0.384951077351747 & 0.769902154703493 & 0.615048922648253 \tabularnewline
39 & 0.512197880937745 & 0.97560423812451 & 0.487802119062255 \tabularnewline
40 & 0.452500605698638 & 0.905001211397275 & 0.547499394301362 \tabularnewline
41 & 0.405249131518417 & 0.810498263036834 & 0.594750868481583 \tabularnewline
42 & 0.438156894770931 & 0.876313789541862 & 0.561843105229069 \tabularnewline
43 & 0.408501101828578 & 0.817002203657155 & 0.591498898171422 \tabularnewline
44 & 0.456591779959702 & 0.913183559919404 & 0.543408220040298 \tabularnewline
45 & 0.446625117853909 & 0.893250235707818 & 0.553374882146091 \tabularnewline
46 & 0.409654451500503 & 0.819308903001006 & 0.590345548499497 \tabularnewline
47 & 0.365651400127452 & 0.731302800254904 & 0.634348599872548 \tabularnewline
48 & 0.358133741208017 & 0.716267482416033 & 0.641866258791983 \tabularnewline
49 & 0.347080679638731 & 0.694161359277463 & 0.652919320361269 \tabularnewline
50 & 0.327298415305346 & 0.654596830610691 & 0.672701584694654 \tabularnewline
51 & 0.348437216225556 & 0.696874432451113 & 0.651562783774444 \tabularnewline
52 & 0.313643518632375 & 0.627287037264749 & 0.686356481367626 \tabularnewline
53 & 0.295808354905858 & 0.591616709811717 & 0.704191645094142 \tabularnewline
54 & 0.301900719711694 & 0.603801439423388 & 0.698099280288306 \tabularnewline
55 & 0.283561781289988 & 0.567123562579977 & 0.716438218710012 \tabularnewline
56 & 0.285115422129288 & 0.570230844258576 & 0.714884577870712 \tabularnewline
57 & 0.304742752884724 & 0.609485505769449 & 0.695257247115276 \tabularnewline
58 & 0.28302689384604 & 0.56605378769208 & 0.71697310615396 \tabularnewline
59 & 0.270084611287896 & 0.540169222575792 & 0.729915388712104 \tabularnewline
60 & 0.235777259595732 & 0.471554519191464 & 0.764222740404268 \tabularnewline
61 & 0.212094914305745 & 0.424189828611489 & 0.787905085694255 \tabularnewline
62 & 0.230175573662175 & 0.460351147324349 & 0.769824426337825 \tabularnewline
63 & 0.210157861318919 & 0.420315722637837 & 0.789842138681081 \tabularnewline
64 & 0.184443440959128 & 0.368886881918256 & 0.815556559040872 \tabularnewline
65 & 0.15706335871021 & 0.31412671742042 & 0.84293664128979 \tabularnewline
66 & 0.14397290692389 & 0.287945813847781 & 0.85602709307611 \tabularnewline
67 & 0.162569116093629 & 0.325138232187258 & 0.837430883906371 \tabularnewline
68 & 0.138087747606039 & 0.276175495212077 & 0.861912252393961 \tabularnewline
69 & 0.121712306743581 & 0.243424613487162 & 0.878287693256419 \tabularnewline
70 & 0.101627535052303 & 0.203255070104606 & 0.898372464947697 \tabularnewline
71 & 0.114281916163938 & 0.228563832327875 & 0.885718083836062 \tabularnewline
72 & 0.124476202244355 & 0.248952404488711 & 0.875523797755645 \tabularnewline
73 & 0.108351811388254 & 0.216703622776509 & 0.891648188611746 \tabularnewline
74 & 0.0961097724236941 & 0.192219544847388 & 0.903890227576306 \tabularnewline
75 & 0.123863808459142 & 0.247727616918284 & 0.876136191540858 \tabularnewline
76 & 0.157226386844115 & 0.314452773688229 & 0.842773613155885 \tabularnewline
77 & 0.137077226229854 & 0.274154452459707 & 0.862922773770146 \tabularnewline
78 & 0.14215557113224 & 0.284311142264479 & 0.85784442886776 \tabularnewline
79 & 0.122166365202121 & 0.244332730404243 & 0.877833634797879 \tabularnewline
80 & 0.155354620655096 & 0.310709241310191 & 0.844645379344904 \tabularnewline
81 & 0.279570046544095 & 0.55914009308819 & 0.720429953455905 \tabularnewline
82 & 0.406072138535853 & 0.812144277071707 & 0.593927861464147 \tabularnewline
83 & 0.410949919662445 & 0.821899839324889 & 0.589050080337555 \tabularnewline
84 & 0.425683286336286 & 0.851366572672572 & 0.574316713663714 \tabularnewline
85 & 0.391411701879736 & 0.782823403759472 & 0.608588298120264 \tabularnewline
86 & 0.396281328653869 & 0.792562657307738 & 0.603718671346131 \tabularnewline
87 & 0.386268060332757 & 0.772536120665513 & 0.613731939667243 \tabularnewline
88 & 0.38472856767204 & 0.76945713534408 & 0.61527143232796 \tabularnewline
89 & 0.409363338032589 & 0.818726676065177 & 0.590636661967411 \tabularnewline
90 & 0.380521496325609 & 0.761042992651218 & 0.619478503674391 \tabularnewline
91 & 0.345948841615279 & 0.691897683230558 & 0.654051158384721 \tabularnewline
92 & 0.310900718721392 & 0.621801437442783 & 0.689099281278608 \tabularnewline
93 & 0.288863493203198 & 0.577726986406395 & 0.711136506796803 \tabularnewline
94 & 0.27841616370193 & 0.55683232740386 & 0.72158383629807 \tabularnewline
95 & 0.299351273637264 & 0.598702547274529 & 0.700648726362736 \tabularnewline
96 & 0.276350786701147 & 0.552701573402295 & 0.723649213298853 \tabularnewline
97 & 0.337666022783023 & 0.675332045566046 & 0.662333977216977 \tabularnewline
98 & 0.37627423782725 & 0.752548475654499 & 0.62372576217275 \tabularnewline
99 & 0.339824993690515 & 0.679649987381031 & 0.660175006309485 \tabularnewline
100 & 0.328612390541984 & 0.657224781083967 & 0.671387609458016 \tabularnewline
101 & 0.310935010929757 & 0.621870021859514 & 0.689064989070243 \tabularnewline
102 & 0.277961832556004 & 0.555923665112008 & 0.722038167443996 \tabularnewline
103 & 0.258763471439029 & 0.517526942878057 & 0.741236528560971 \tabularnewline
104 & 0.273061251504288 & 0.546122503008576 & 0.726938748495712 \tabularnewline
105 & 0.245682048424628 & 0.491364096849255 & 0.754317951575372 \tabularnewline
106 & 0.216934280867781 & 0.433868561735562 & 0.783065719132219 \tabularnewline
107 & 0.257717461627106 & 0.515434923254212 & 0.742282538372894 \tabularnewline
108 & 0.253174408847887 & 0.506348817695774 & 0.746825591152113 \tabularnewline
109 & 0.264079737290579 & 0.528159474581157 & 0.735920262709421 \tabularnewline
110 & 0.236694604389379 & 0.473389208778757 & 0.763305395610621 \tabularnewline
111 & 0.208627560408974 & 0.417255120817948 & 0.791372439591026 \tabularnewline
112 & 0.211644189886584 & 0.423288379773169 & 0.788355810113415 \tabularnewline
113 & 0.188403086030407 & 0.376806172060814 & 0.811596913969593 \tabularnewline
114 & 0.166582415903985 & 0.333164831807971 & 0.833417584096015 \tabularnewline
115 & 0.205124111341278 & 0.410248222682556 & 0.794875888658722 \tabularnewline
116 & 0.179512853245672 & 0.359025706491344 & 0.820487146754328 \tabularnewline
117 & 0.168957953878318 & 0.337915907756637 & 0.831042046121682 \tabularnewline
118 & 0.146280010586183 & 0.292560021172367 & 0.853719989413817 \tabularnewline
119 & 0.20099741835479 & 0.401994836709579 & 0.79900258164521 \tabularnewline
120 & 0.205715578216519 & 0.411431156433038 & 0.794284421783481 \tabularnewline
121 & 0.267269987072646 & 0.534539974145293 & 0.732730012927354 \tabularnewline
122 & 0.249597166503272 & 0.499194333006543 & 0.750402833496728 \tabularnewline
123 & 0.221458421990017 & 0.442916843980035 & 0.778541578009983 \tabularnewline
124 & 0.196626684388149 & 0.393253368776297 & 0.803373315611851 \tabularnewline
125 & 0.175403869509043 & 0.350807739018087 & 0.824596130490957 \tabularnewline
126 & 0.168136723012548 & 0.336273446025096 & 0.831863276987452 \tabularnewline
127 & 0.183619568523219 & 0.367239137046439 & 0.816380431476781 \tabularnewline
128 & 0.260208584627282 & 0.520417169254565 & 0.739791415372718 \tabularnewline
129 & 0.235767315905588 & 0.471534631811175 & 0.764232684094412 \tabularnewline
130 & 0.207651204653826 & 0.415302409307652 & 0.792348795346174 \tabularnewline
131 & 0.182897441541156 & 0.365794883082312 & 0.817102558458844 \tabularnewline
132 & 0.167230138068033 & 0.334460276136065 & 0.832769861931967 \tabularnewline
133 & 0.147599616348673 & 0.295199232697347 & 0.852400383651327 \tabularnewline
134 & 0.154467187918553 & 0.308934375837107 & 0.845532812081446 \tabularnewline
135 & 0.220642857543353 & 0.441285715086707 & 0.779357142456647 \tabularnewline
136 & 0.193597461014966 & 0.387194922029931 & 0.806402538985034 \tabularnewline
137 & 0.206519333700572 & 0.413038667401143 & 0.793480666299428 \tabularnewline
138 & 0.202238268267051 & 0.404476536534102 & 0.797761731732949 \tabularnewline
139 & 0.209154764122716 & 0.418309528245431 & 0.790845235877284 \tabularnewline
140 & 0.291289218070134 & 0.582578436140267 & 0.708710781929866 \tabularnewline
141 & 0.276879165862588 & 0.553758331725177 & 0.723120834137412 \tabularnewline
142 & 0.259539384208689 & 0.519078768417378 & 0.740460615791311 \tabularnewline
143 & 0.26605059426673 & 0.532101188533459 & 0.73394940573327 \tabularnewline
144 & 0.2676050051957 & 0.5352100103914 & 0.7323949948043 \tabularnewline
145 & 0.238554933905224 & 0.477109867810448 & 0.761445066094776 \tabularnewline
146 & 0.215348402928567 & 0.430696805857134 & 0.784651597071433 \tabularnewline
147 & 0.201397823556532 & 0.402795647113064 & 0.798602176443468 \tabularnewline
148 & 0.250455828587229 & 0.500911657174459 & 0.749544171412771 \tabularnewline
149 & 0.221590861622753 & 0.443181723245506 & 0.778409138377247 \tabularnewline
150 & 0.198390947166996 & 0.396781894333991 & 0.801609052833004 \tabularnewline
151 & 0.174853507240884 & 0.349707014481767 & 0.825146492759116 \tabularnewline
152 & 0.161953625514898 & 0.323907251029796 & 0.838046374485102 \tabularnewline
153 & 0.206645042538106 & 0.413290085076211 & 0.793354957461895 \tabularnewline
154 & 0.18044087486882 & 0.36088174973764 & 0.81955912513118 \tabularnewline
155 & 0.158853838790637 & 0.317707677581274 & 0.841146161209363 \tabularnewline
156 & 0.181143468374797 & 0.362286936749594 & 0.818856531625203 \tabularnewline
157 & 0.170978159639621 & 0.341956319279242 & 0.829021840360379 \tabularnewline
158 & 0.180211636402779 & 0.360423272805559 & 0.819788363597221 \tabularnewline
159 & 0.177912448145475 & 0.35582489629095 & 0.822087551854525 \tabularnewline
160 & 0.186717440687796 & 0.373434881375591 & 0.813282559312204 \tabularnewline
161 & 0.167428750633697 & 0.334857501267395 & 0.832571249366303 \tabularnewline
162 & 0.152831664513891 & 0.305663329027781 & 0.847168335486109 \tabularnewline
163 & 0.1382569927338 & 0.2765139854676 & 0.8617430072662 \tabularnewline
164 & 0.117860450459271 & 0.235720900918542 & 0.882139549540729 \tabularnewline
165 & 0.0993841546286103 & 0.198768309257221 & 0.90061584537139 \tabularnewline
166 & 0.0883537262316658 & 0.176707452463332 & 0.911646273768334 \tabularnewline
167 & 0.0915625544508629 & 0.183125108901726 & 0.908437445549137 \tabularnewline
168 & 0.0769741146497626 & 0.153948229299525 & 0.923025885350237 \tabularnewline
169 & 0.0693229213350126 & 0.138645842670025 & 0.930677078664987 \tabularnewline
170 & 0.0631599049879288 & 0.126319809975858 & 0.936840095012071 \tabularnewline
171 & 0.0994522449809676 & 0.198904489961935 & 0.900547755019032 \tabularnewline
172 & 0.121916247378268 & 0.243832494756537 & 0.878083752621732 \tabularnewline
173 & 0.118318419191081 & 0.236636838382161 & 0.881681580808919 \tabularnewline
174 & 0.099384112907176 & 0.198768225814352 & 0.900615887092824 \tabularnewline
175 & 0.104436134732465 & 0.20887226946493 & 0.895563865267535 \tabularnewline
176 & 0.0901627706307275 & 0.180325541261455 & 0.909837229369272 \tabularnewline
177 & 0.0810741989271214 & 0.162148397854243 & 0.918925801072879 \tabularnewline
178 & 0.0670919937086403 & 0.134183987417281 & 0.93290800629136 \tabularnewline
179 & 0.0615937513306581 & 0.123187502661316 & 0.938406248669342 \tabularnewline
180 & 0.085985341200015 & 0.17197068240003 & 0.914014658799985 \tabularnewline
181 & 0.0721547475541638 & 0.144309495108328 & 0.927845252445836 \tabularnewline
182 & 0.0700396417867803 & 0.140079283573561 & 0.92996035821322 \tabularnewline
183 & 0.0654495079702405 & 0.130899015940481 & 0.934550492029759 \tabularnewline
184 & 0.0705612017101714 & 0.141122403420343 & 0.929438798289829 \tabularnewline
185 & 0.0574509767544793 & 0.114901953508959 & 0.942549023245521 \tabularnewline
186 & 0.0636931136676713 & 0.127386227335343 & 0.936306886332329 \tabularnewline
187 & 0.0610615023844239 & 0.122123004768848 & 0.938938497615576 \tabularnewline
188 & 0.0526514965137009 & 0.105302993027402 & 0.947348503486299 \tabularnewline
189 & 0.0430604868367685 & 0.0861209736735371 & 0.956939513163231 \tabularnewline
190 & 0.044027454535193 & 0.088054909070386 & 0.955972545464807 \tabularnewline
191 & 0.0346479625077369 & 0.0692959250154737 & 0.965352037492263 \tabularnewline
192 & 0.0411501224457151 & 0.0823002448914301 & 0.958849877554285 \tabularnewline
193 & 0.0340197474943351 & 0.0680394949886702 & 0.965980252505665 \tabularnewline
194 & 0.0293819800837546 & 0.0587639601675091 & 0.970618019916245 \tabularnewline
195 & 0.0379530489212947 & 0.0759060978425894 & 0.962046951078705 \tabularnewline
196 & 0.0313489198067978 & 0.0626978396135957 & 0.968651080193202 \tabularnewline
197 & 0.0527616256386792 & 0.105523251277358 & 0.947238374361321 \tabularnewline
198 & 0.0441222929612166 & 0.0882445859224332 & 0.955877707038783 \tabularnewline
199 & 0.0348929353282485 & 0.069785870656497 & 0.965107064671752 \tabularnewline
200 & 0.0936016809706487 & 0.187203361941297 & 0.906398319029351 \tabularnewline
201 & 0.078337363326737 & 0.156674726653474 & 0.921662636673263 \tabularnewline
202 & 0.100650208872228 & 0.201300417744457 & 0.899349791127771 \tabularnewline
203 & 0.113112595189423 & 0.226225190378846 & 0.886887404810577 \tabularnewline
204 & 0.198096603815308 & 0.396193207630616 & 0.801903396184692 \tabularnewline
205 & 0.165595848058 & 0.331191696116001 & 0.834404151942 \tabularnewline
206 & 0.191086568023615 & 0.382173136047231 & 0.808913431976385 \tabularnewline
207 & 0.508687653528392 & 0.982624692943215 & 0.491312346471608 \tabularnewline
208 & 0.612182963246249 & 0.775634073507502 & 0.387817036753751 \tabularnewline
209 & 0.567770077806846 & 0.864459844386308 & 0.432229922193154 \tabularnewline
210 & 0.517642559899437 & 0.964714880201126 & 0.482357440100563 \tabularnewline
211 & 0.476431580130227 & 0.952863160260453 & 0.523568419869773 \tabularnewline
212 & 0.428179948228018 & 0.856359896456035 & 0.571820051771982 \tabularnewline
213 & 0.428350747254406 & 0.856701494508812 & 0.571649252745594 \tabularnewline
214 & 0.385864812858538 & 0.771729625717076 & 0.614135187141462 \tabularnewline
215 & 0.448036914349905 & 0.89607382869981 & 0.551963085650095 \tabularnewline
216 & 0.705578386672887 & 0.588843226654227 & 0.294421613327113 \tabularnewline
217 & 0.653631976671445 & 0.692736046657111 & 0.346368023328555 \tabularnewline
218 & 0.591838467494697 & 0.816323065010606 & 0.408161532505303 \tabularnewline
219 & 0.561599211543044 & 0.876801576913912 & 0.438400788456956 \tabularnewline
220 & 0.53100072943507 & 0.93799854112986 & 0.46899927056493 \tabularnewline
221 & 0.492963299074752 & 0.985926598149503 & 0.507036700925248 \tabularnewline
222 & 0.437712778287463 & 0.875425556574925 & 0.562287221712537 \tabularnewline
223 & 0.421111557776988 & 0.842223115553976 & 0.578888442223012 \tabularnewline
224 & 0.618304597770255 & 0.763390804459491 & 0.381695402229745 \tabularnewline
225 & 0.712317837603984 & 0.575364324792033 & 0.287682162396016 \tabularnewline
226 & 0.640806339158418 & 0.718387321683164 & 0.359193660841582 \tabularnewline
227 & 0.561619156977362 & 0.876761686045277 & 0.438380843022639 \tabularnewline
228 & 0.707950011879156 & 0.584099976241689 & 0.292049988120844 \tabularnewline
229 & 0.664424471345979 & 0.671151057308042 & 0.335575528654021 \tabularnewline
230 & 0.568701930557582 & 0.862596138884835 & 0.431298069442418 \tabularnewline
231 & 0.476056966344436 & 0.952113932688873 & 0.523943033655564 \tabularnewline
232 & 0.367216093178731 & 0.734432186357462 & 0.632783906821269 \tabularnewline
233 & 0.270937609662818 & 0.541875219325635 & 0.729062390337182 \tabularnewline
234 & 0.631735814951489 & 0.736528370097022 & 0.368264185048511 \tabularnewline
235 & 0.603028854506466 & 0.793942290987068 & 0.396971145493534 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190472&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]17[/C][C]0.0875608272989696[/C][C]0.175121654597939[/C][C]0.91243917270103[/C][/ROW]
[ROW][C]18[/C][C]0.282106937241268[/C][C]0.564213874482536[/C][C]0.717893062758732[/C][/ROW]
[ROW][C]19[/C][C]0.223581484759997[/C][C]0.447162969519994[/C][C]0.776418515240003[/C][/ROW]
[ROW][C]20[/C][C]0.254220148570916[/C][C]0.508440297141832[/C][C]0.745779851429084[/C][/ROW]
[ROW][C]21[/C][C]0.190438483090145[/C][C]0.38087696618029[/C][C]0.809561516909855[/C][/ROW]
[ROW][C]22[/C][C]0.532662560846844[/C][C]0.934674878306312[/C][C]0.467337439153156[/C][/ROW]
[ROW][C]23[/C][C]0.562507113283741[/C][C]0.874985773432518[/C][C]0.437492886716259[/C][/ROW]
[ROW][C]24[/C][C]0.562892516385805[/C][C]0.87421496722839[/C][C]0.437107483614195[/C][/ROW]
[ROW][C]25[/C][C]0.478428651312634[/C][C]0.956857302625268[/C][C]0.521571348687366[/C][/ROW]
[ROW][C]26[/C][C]0.591250476191283[/C][C]0.817499047617434[/C][C]0.408749523808717[/C][/ROW]
[ROW][C]27[/C][C]0.517031783125763[/C][C]0.965936433748473[/C][C]0.482968216874237[/C][/ROW]
[ROW][C]28[/C][C]0.613372758960775[/C][C]0.773254482078451[/C][C]0.386627241039225[/C][/ROW]
[ROW][C]29[/C][C]0.565768542050577[/C][C]0.868462915898847[/C][C]0.434231457949423[/C][/ROW]
[ROW][C]30[/C][C]0.548448906241801[/C][C]0.903102187516398[/C][C]0.451551093758199[/C][/ROW]
[ROW][C]31[/C][C]0.493656031404474[/C][C]0.987312062808948[/C][C]0.506343968595526[/C][/ROW]
[ROW][C]32[/C][C]0.582271584439543[/C][C]0.835456831120914[/C][C]0.417728415560457[/C][/ROW]
[ROW][C]33[/C][C]0.56759574207652[/C][C]0.86480851584696[/C][C]0.43240425792348[/C][/ROW]
[ROW][C]34[/C][C]0.569092785968105[/C][C]0.861814428063789[/C][C]0.430907214031895[/C][/ROW]
[ROW][C]35[/C][C]0.505080250572285[/C][C]0.98983949885543[/C][C]0.494919749427715[/C][/ROW]
[ROW][C]36[/C][C]0.464960648580599[/C][C]0.929921297161198[/C][C]0.535039351419401[/C][/ROW]
[ROW][C]37[/C][C]0.417162569738874[/C][C]0.834325139477747[/C][C]0.582837430261127[/C][/ROW]
[ROW][C]38[/C][C]0.384951077351747[/C][C]0.769902154703493[/C][C]0.615048922648253[/C][/ROW]
[ROW][C]39[/C][C]0.512197880937745[/C][C]0.97560423812451[/C][C]0.487802119062255[/C][/ROW]
[ROW][C]40[/C][C]0.452500605698638[/C][C]0.905001211397275[/C][C]0.547499394301362[/C][/ROW]
[ROW][C]41[/C][C]0.405249131518417[/C][C]0.810498263036834[/C][C]0.594750868481583[/C][/ROW]
[ROW][C]42[/C][C]0.438156894770931[/C][C]0.876313789541862[/C][C]0.561843105229069[/C][/ROW]
[ROW][C]43[/C][C]0.408501101828578[/C][C]0.817002203657155[/C][C]0.591498898171422[/C][/ROW]
[ROW][C]44[/C][C]0.456591779959702[/C][C]0.913183559919404[/C][C]0.543408220040298[/C][/ROW]
[ROW][C]45[/C][C]0.446625117853909[/C][C]0.893250235707818[/C][C]0.553374882146091[/C][/ROW]
[ROW][C]46[/C][C]0.409654451500503[/C][C]0.819308903001006[/C][C]0.590345548499497[/C][/ROW]
[ROW][C]47[/C][C]0.365651400127452[/C][C]0.731302800254904[/C][C]0.634348599872548[/C][/ROW]
[ROW][C]48[/C][C]0.358133741208017[/C][C]0.716267482416033[/C][C]0.641866258791983[/C][/ROW]
[ROW][C]49[/C][C]0.347080679638731[/C][C]0.694161359277463[/C][C]0.652919320361269[/C][/ROW]
[ROW][C]50[/C][C]0.327298415305346[/C][C]0.654596830610691[/C][C]0.672701584694654[/C][/ROW]
[ROW][C]51[/C][C]0.348437216225556[/C][C]0.696874432451113[/C][C]0.651562783774444[/C][/ROW]
[ROW][C]52[/C][C]0.313643518632375[/C][C]0.627287037264749[/C][C]0.686356481367626[/C][/ROW]
[ROW][C]53[/C][C]0.295808354905858[/C][C]0.591616709811717[/C][C]0.704191645094142[/C][/ROW]
[ROW][C]54[/C][C]0.301900719711694[/C][C]0.603801439423388[/C][C]0.698099280288306[/C][/ROW]
[ROW][C]55[/C][C]0.283561781289988[/C][C]0.567123562579977[/C][C]0.716438218710012[/C][/ROW]
[ROW][C]56[/C][C]0.285115422129288[/C][C]0.570230844258576[/C][C]0.714884577870712[/C][/ROW]
[ROW][C]57[/C][C]0.304742752884724[/C][C]0.609485505769449[/C][C]0.695257247115276[/C][/ROW]
[ROW][C]58[/C][C]0.28302689384604[/C][C]0.56605378769208[/C][C]0.71697310615396[/C][/ROW]
[ROW][C]59[/C][C]0.270084611287896[/C][C]0.540169222575792[/C][C]0.729915388712104[/C][/ROW]
[ROW][C]60[/C][C]0.235777259595732[/C][C]0.471554519191464[/C][C]0.764222740404268[/C][/ROW]
[ROW][C]61[/C][C]0.212094914305745[/C][C]0.424189828611489[/C][C]0.787905085694255[/C][/ROW]
[ROW][C]62[/C][C]0.230175573662175[/C][C]0.460351147324349[/C][C]0.769824426337825[/C][/ROW]
[ROW][C]63[/C][C]0.210157861318919[/C][C]0.420315722637837[/C][C]0.789842138681081[/C][/ROW]
[ROW][C]64[/C][C]0.184443440959128[/C][C]0.368886881918256[/C][C]0.815556559040872[/C][/ROW]
[ROW][C]65[/C][C]0.15706335871021[/C][C]0.31412671742042[/C][C]0.84293664128979[/C][/ROW]
[ROW][C]66[/C][C]0.14397290692389[/C][C]0.287945813847781[/C][C]0.85602709307611[/C][/ROW]
[ROW][C]67[/C][C]0.162569116093629[/C][C]0.325138232187258[/C][C]0.837430883906371[/C][/ROW]
[ROW][C]68[/C][C]0.138087747606039[/C][C]0.276175495212077[/C][C]0.861912252393961[/C][/ROW]
[ROW][C]69[/C][C]0.121712306743581[/C][C]0.243424613487162[/C][C]0.878287693256419[/C][/ROW]
[ROW][C]70[/C][C]0.101627535052303[/C][C]0.203255070104606[/C][C]0.898372464947697[/C][/ROW]
[ROW][C]71[/C][C]0.114281916163938[/C][C]0.228563832327875[/C][C]0.885718083836062[/C][/ROW]
[ROW][C]72[/C][C]0.124476202244355[/C][C]0.248952404488711[/C][C]0.875523797755645[/C][/ROW]
[ROW][C]73[/C][C]0.108351811388254[/C][C]0.216703622776509[/C][C]0.891648188611746[/C][/ROW]
[ROW][C]74[/C][C]0.0961097724236941[/C][C]0.192219544847388[/C][C]0.903890227576306[/C][/ROW]
[ROW][C]75[/C][C]0.123863808459142[/C][C]0.247727616918284[/C][C]0.876136191540858[/C][/ROW]
[ROW][C]76[/C][C]0.157226386844115[/C][C]0.314452773688229[/C][C]0.842773613155885[/C][/ROW]
[ROW][C]77[/C][C]0.137077226229854[/C][C]0.274154452459707[/C][C]0.862922773770146[/C][/ROW]
[ROW][C]78[/C][C]0.14215557113224[/C][C]0.284311142264479[/C][C]0.85784442886776[/C][/ROW]
[ROW][C]79[/C][C]0.122166365202121[/C][C]0.244332730404243[/C][C]0.877833634797879[/C][/ROW]
[ROW][C]80[/C][C]0.155354620655096[/C][C]0.310709241310191[/C][C]0.844645379344904[/C][/ROW]
[ROW][C]81[/C][C]0.279570046544095[/C][C]0.55914009308819[/C][C]0.720429953455905[/C][/ROW]
[ROW][C]82[/C][C]0.406072138535853[/C][C]0.812144277071707[/C][C]0.593927861464147[/C][/ROW]
[ROW][C]83[/C][C]0.410949919662445[/C][C]0.821899839324889[/C][C]0.589050080337555[/C][/ROW]
[ROW][C]84[/C][C]0.425683286336286[/C][C]0.851366572672572[/C][C]0.574316713663714[/C][/ROW]
[ROW][C]85[/C][C]0.391411701879736[/C][C]0.782823403759472[/C][C]0.608588298120264[/C][/ROW]
[ROW][C]86[/C][C]0.396281328653869[/C][C]0.792562657307738[/C][C]0.603718671346131[/C][/ROW]
[ROW][C]87[/C][C]0.386268060332757[/C][C]0.772536120665513[/C][C]0.613731939667243[/C][/ROW]
[ROW][C]88[/C][C]0.38472856767204[/C][C]0.76945713534408[/C][C]0.61527143232796[/C][/ROW]
[ROW][C]89[/C][C]0.409363338032589[/C][C]0.818726676065177[/C][C]0.590636661967411[/C][/ROW]
[ROW][C]90[/C][C]0.380521496325609[/C][C]0.761042992651218[/C][C]0.619478503674391[/C][/ROW]
[ROW][C]91[/C][C]0.345948841615279[/C][C]0.691897683230558[/C][C]0.654051158384721[/C][/ROW]
[ROW][C]92[/C][C]0.310900718721392[/C][C]0.621801437442783[/C][C]0.689099281278608[/C][/ROW]
[ROW][C]93[/C][C]0.288863493203198[/C][C]0.577726986406395[/C][C]0.711136506796803[/C][/ROW]
[ROW][C]94[/C][C]0.27841616370193[/C][C]0.55683232740386[/C][C]0.72158383629807[/C][/ROW]
[ROW][C]95[/C][C]0.299351273637264[/C][C]0.598702547274529[/C][C]0.700648726362736[/C][/ROW]
[ROW][C]96[/C][C]0.276350786701147[/C][C]0.552701573402295[/C][C]0.723649213298853[/C][/ROW]
[ROW][C]97[/C][C]0.337666022783023[/C][C]0.675332045566046[/C][C]0.662333977216977[/C][/ROW]
[ROW][C]98[/C][C]0.37627423782725[/C][C]0.752548475654499[/C][C]0.62372576217275[/C][/ROW]
[ROW][C]99[/C][C]0.339824993690515[/C][C]0.679649987381031[/C][C]0.660175006309485[/C][/ROW]
[ROW][C]100[/C][C]0.328612390541984[/C][C]0.657224781083967[/C][C]0.671387609458016[/C][/ROW]
[ROW][C]101[/C][C]0.310935010929757[/C][C]0.621870021859514[/C][C]0.689064989070243[/C][/ROW]
[ROW][C]102[/C][C]0.277961832556004[/C][C]0.555923665112008[/C][C]0.722038167443996[/C][/ROW]
[ROW][C]103[/C][C]0.258763471439029[/C][C]0.517526942878057[/C][C]0.741236528560971[/C][/ROW]
[ROW][C]104[/C][C]0.273061251504288[/C][C]0.546122503008576[/C][C]0.726938748495712[/C][/ROW]
[ROW][C]105[/C][C]0.245682048424628[/C][C]0.491364096849255[/C][C]0.754317951575372[/C][/ROW]
[ROW][C]106[/C][C]0.216934280867781[/C][C]0.433868561735562[/C][C]0.783065719132219[/C][/ROW]
[ROW][C]107[/C][C]0.257717461627106[/C][C]0.515434923254212[/C][C]0.742282538372894[/C][/ROW]
[ROW][C]108[/C][C]0.253174408847887[/C][C]0.506348817695774[/C][C]0.746825591152113[/C][/ROW]
[ROW][C]109[/C][C]0.264079737290579[/C][C]0.528159474581157[/C][C]0.735920262709421[/C][/ROW]
[ROW][C]110[/C][C]0.236694604389379[/C][C]0.473389208778757[/C][C]0.763305395610621[/C][/ROW]
[ROW][C]111[/C][C]0.208627560408974[/C][C]0.417255120817948[/C][C]0.791372439591026[/C][/ROW]
[ROW][C]112[/C][C]0.211644189886584[/C][C]0.423288379773169[/C][C]0.788355810113415[/C][/ROW]
[ROW][C]113[/C][C]0.188403086030407[/C][C]0.376806172060814[/C][C]0.811596913969593[/C][/ROW]
[ROW][C]114[/C][C]0.166582415903985[/C][C]0.333164831807971[/C][C]0.833417584096015[/C][/ROW]
[ROW][C]115[/C][C]0.205124111341278[/C][C]0.410248222682556[/C][C]0.794875888658722[/C][/ROW]
[ROW][C]116[/C][C]0.179512853245672[/C][C]0.359025706491344[/C][C]0.820487146754328[/C][/ROW]
[ROW][C]117[/C][C]0.168957953878318[/C][C]0.337915907756637[/C][C]0.831042046121682[/C][/ROW]
[ROW][C]118[/C][C]0.146280010586183[/C][C]0.292560021172367[/C][C]0.853719989413817[/C][/ROW]
[ROW][C]119[/C][C]0.20099741835479[/C][C]0.401994836709579[/C][C]0.79900258164521[/C][/ROW]
[ROW][C]120[/C][C]0.205715578216519[/C][C]0.411431156433038[/C][C]0.794284421783481[/C][/ROW]
[ROW][C]121[/C][C]0.267269987072646[/C][C]0.534539974145293[/C][C]0.732730012927354[/C][/ROW]
[ROW][C]122[/C][C]0.249597166503272[/C][C]0.499194333006543[/C][C]0.750402833496728[/C][/ROW]
[ROW][C]123[/C][C]0.221458421990017[/C][C]0.442916843980035[/C][C]0.778541578009983[/C][/ROW]
[ROW][C]124[/C][C]0.196626684388149[/C][C]0.393253368776297[/C][C]0.803373315611851[/C][/ROW]
[ROW][C]125[/C][C]0.175403869509043[/C][C]0.350807739018087[/C][C]0.824596130490957[/C][/ROW]
[ROW][C]126[/C][C]0.168136723012548[/C][C]0.336273446025096[/C][C]0.831863276987452[/C][/ROW]
[ROW][C]127[/C][C]0.183619568523219[/C][C]0.367239137046439[/C][C]0.816380431476781[/C][/ROW]
[ROW][C]128[/C][C]0.260208584627282[/C][C]0.520417169254565[/C][C]0.739791415372718[/C][/ROW]
[ROW][C]129[/C][C]0.235767315905588[/C][C]0.471534631811175[/C][C]0.764232684094412[/C][/ROW]
[ROW][C]130[/C][C]0.207651204653826[/C][C]0.415302409307652[/C][C]0.792348795346174[/C][/ROW]
[ROW][C]131[/C][C]0.182897441541156[/C][C]0.365794883082312[/C][C]0.817102558458844[/C][/ROW]
[ROW][C]132[/C][C]0.167230138068033[/C][C]0.334460276136065[/C][C]0.832769861931967[/C][/ROW]
[ROW][C]133[/C][C]0.147599616348673[/C][C]0.295199232697347[/C][C]0.852400383651327[/C][/ROW]
[ROW][C]134[/C][C]0.154467187918553[/C][C]0.308934375837107[/C][C]0.845532812081446[/C][/ROW]
[ROW][C]135[/C][C]0.220642857543353[/C][C]0.441285715086707[/C][C]0.779357142456647[/C][/ROW]
[ROW][C]136[/C][C]0.193597461014966[/C][C]0.387194922029931[/C][C]0.806402538985034[/C][/ROW]
[ROW][C]137[/C][C]0.206519333700572[/C][C]0.413038667401143[/C][C]0.793480666299428[/C][/ROW]
[ROW][C]138[/C][C]0.202238268267051[/C][C]0.404476536534102[/C][C]0.797761731732949[/C][/ROW]
[ROW][C]139[/C][C]0.209154764122716[/C][C]0.418309528245431[/C][C]0.790845235877284[/C][/ROW]
[ROW][C]140[/C][C]0.291289218070134[/C][C]0.582578436140267[/C][C]0.708710781929866[/C][/ROW]
[ROW][C]141[/C][C]0.276879165862588[/C][C]0.553758331725177[/C][C]0.723120834137412[/C][/ROW]
[ROW][C]142[/C][C]0.259539384208689[/C][C]0.519078768417378[/C][C]0.740460615791311[/C][/ROW]
[ROW][C]143[/C][C]0.26605059426673[/C][C]0.532101188533459[/C][C]0.73394940573327[/C][/ROW]
[ROW][C]144[/C][C]0.2676050051957[/C][C]0.5352100103914[/C][C]0.7323949948043[/C][/ROW]
[ROW][C]145[/C][C]0.238554933905224[/C][C]0.477109867810448[/C][C]0.761445066094776[/C][/ROW]
[ROW][C]146[/C][C]0.215348402928567[/C][C]0.430696805857134[/C][C]0.784651597071433[/C][/ROW]
[ROW][C]147[/C][C]0.201397823556532[/C][C]0.402795647113064[/C][C]0.798602176443468[/C][/ROW]
[ROW][C]148[/C][C]0.250455828587229[/C][C]0.500911657174459[/C][C]0.749544171412771[/C][/ROW]
[ROW][C]149[/C][C]0.221590861622753[/C][C]0.443181723245506[/C][C]0.778409138377247[/C][/ROW]
[ROW][C]150[/C][C]0.198390947166996[/C][C]0.396781894333991[/C][C]0.801609052833004[/C][/ROW]
[ROW][C]151[/C][C]0.174853507240884[/C][C]0.349707014481767[/C][C]0.825146492759116[/C][/ROW]
[ROW][C]152[/C][C]0.161953625514898[/C][C]0.323907251029796[/C][C]0.838046374485102[/C][/ROW]
[ROW][C]153[/C][C]0.206645042538106[/C][C]0.413290085076211[/C][C]0.793354957461895[/C][/ROW]
[ROW][C]154[/C][C]0.18044087486882[/C][C]0.36088174973764[/C][C]0.81955912513118[/C][/ROW]
[ROW][C]155[/C][C]0.158853838790637[/C][C]0.317707677581274[/C][C]0.841146161209363[/C][/ROW]
[ROW][C]156[/C][C]0.181143468374797[/C][C]0.362286936749594[/C][C]0.818856531625203[/C][/ROW]
[ROW][C]157[/C][C]0.170978159639621[/C][C]0.341956319279242[/C][C]0.829021840360379[/C][/ROW]
[ROW][C]158[/C][C]0.180211636402779[/C][C]0.360423272805559[/C][C]0.819788363597221[/C][/ROW]
[ROW][C]159[/C][C]0.177912448145475[/C][C]0.35582489629095[/C][C]0.822087551854525[/C][/ROW]
[ROW][C]160[/C][C]0.186717440687796[/C][C]0.373434881375591[/C][C]0.813282559312204[/C][/ROW]
[ROW][C]161[/C][C]0.167428750633697[/C][C]0.334857501267395[/C][C]0.832571249366303[/C][/ROW]
[ROW][C]162[/C][C]0.152831664513891[/C][C]0.305663329027781[/C][C]0.847168335486109[/C][/ROW]
[ROW][C]163[/C][C]0.1382569927338[/C][C]0.2765139854676[/C][C]0.8617430072662[/C][/ROW]
[ROW][C]164[/C][C]0.117860450459271[/C][C]0.235720900918542[/C][C]0.882139549540729[/C][/ROW]
[ROW][C]165[/C][C]0.0993841546286103[/C][C]0.198768309257221[/C][C]0.90061584537139[/C][/ROW]
[ROW][C]166[/C][C]0.0883537262316658[/C][C]0.176707452463332[/C][C]0.911646273768334[/C][/ROW]
[ROW][C]167[/C][C]0.0915625544508629[/C][C]0.183125108901726[/C][C]0.908437445549137[/C][/ROW]
[ROW][C]168[/C][C]0.0769741146497626[/C][C]0.153948229299525[/C][C]0.923025885350237[/C][/ROW]
[ROW][C]169[/C][C]0.0693229213350126[/C][C]0.138645842670025[/C][C]0.930677078664987[/C][/ROW]
[ROW][C]170[/C][C]0.0631599049879288[/C][C]0.126319809975858[/C][C]0.936840095012071[/C][/ROW]
[ROW][C]171[/C][C]0.0994522449809676[/C][C]0.198904489961935[/C][C]0.900547755019032[/C][/ROW]
[ROW][C]172[/C][C]0.121916247378268[/C][C]0.243832494756537[/C][C]0.878083752621732[/C][/ROW]
[ROW][C]173[/C][C]0.118318419191081[/C][C]0.236636838382161[/C][C]0.881681580808919[/C][/ROW]
[ROW][C]174[/C][C]0.099384112907176[/C][C]0.198768225814352[/C][C]0.900615887092824[/C][/ROW]
[ROW][C]175[/C][C]0.104436134732465[/C][C]0.20887226946493[/C][C]0.895563865267535[/C][/ROW]
[ROW][C]176[/C][C]0.0901627706307275[/C][C]0.180325541261455[/C][C]0.909837229369272[/C][/ROW]
[ROW][C]177[/C][C]0.0810741989271214[/C][C]0.162148397854243[/C][C]0.918925801072879[/C][/ROW]
[ROW][C]178[/C][C]0.0670919937086403[/C][C]0.134183987417281[/C][C]0.93290800629136[/C][/ROW]
[ROW][C]179[/C][C]0.0615937513306581[/C][C]0.123187502661316[/C][C]0.938406248669342[/C][/ROW]
[ROW][C]180[/C][C]0.085985341200015[/C][C]0.17197068240003[/C][C]0.914014658799985[/C][/ROW]
[ROW][C]181[/C][C]0.0721547475541638[/C][C]0.144309495108328[/C][C]0.927845252445836[/C][/ROW]
[ROW][C]182[/C][C]0.0700396417867803[/C][C]0.140079283573561[/C][C]0.92996035821322[/C][/ROW]
[ROW][C]183[/C][C]0.0654495079702405[/C][C]0.130899015940481[/C][C]0.934550492029759[/C][/ROW]
[ROW][C]184[/C][C]0.0705612017101714[/C][C]0.141122403420343[/C][C]0.929438798289829[/C][/ROW]
[ROW][C]185[/C][C]0.0574509767544793[/C][C]0.114901953508959[/C][C]0.942549023245521[/C][/ROW]
[ROW][C]186[/C][C]0.0636931136676713[/C][C]0.127386227335343[/C][C]0.936306886332329[/C][/ROW]
[ROW][C]187[/C][C]0.0610615023844239[/C][C]0.122123004768848[/C][C]0.938938497615576[/C][/ROW]
[ROW][C]188[/C][C]0.0526514965137009[/C][C]0.105302993027402[/C][C]0.947348503486299[/C][/ROW]
[ROW][C]189[/C][C]0.0430604868367685[/C][C]0.0861209736735371[/C][C]0.956939513163231[/C][/ROW]
[ROW][C]190[/C][C]0.044027454535193[/C][C]0.088054909070386[/C][C]0.955972545464807[/C][/ROW]
[ROW][C]191[/C][C]0.0346479625077369[/C][C]0.0692959250154737[/C][C]0.965352037492263[/C][/ROW]
[ROW][C]192[/C][C]0.0411501224457151[/C][C]0.0823002448914301[/C][C]0.958849877554285[/C][/ROW]
[ROW][C]193[/C][C]0.0340197474943351[/C][C]0.0680394949886702[/C][C]0.965980252505665[/C][/ROW]
[ROW][C]194[/C][C]0.0293819800837546[/C][C]0.0587639601675091[/C][C]0.970618019916245[/C][/ROW]
[ROW][C]195[/C][C]0.0379530489212947[/C][C]0.0759060978425894[/C][C]0.962046951078705[/C][/ROW]
[ROW][C]196[/C][C]0.0313489198067978[/C][C]0.0626978396135957[/C][C]0.968651080193202[/C][/ROW]
[ROW][C]197[/C][C]0.0527616256386792[/C][C]0.105523251277358[/C][C]0.947238374361321[/C][/ROW]
[ROW][C]198[/C][C]0.0441222929612166[/C][C]0.0882445859224332[/C][C]0.955877707038783[/C][/ROW]
[ROW][C]199[/C][C]0.0348929353282485[/C][C]0.069785870656497[/C][C]0.965107064671752[/C][/ROW]
[ROW][C]200[/C][C]0.0936016809706487[/C][C]0.187203361941297[/C][C]0.906398319029351[/C][/ROW]
[ROW][C]201[/C][C]0.078337363326737[/C][C]0.156674726653474[/C][C]0.921662636673263[/C][/ROW]
[ROW][C]202[/C][C]0.100650208872228[/C][C]0.201300417744457[/C][C]0.899349791127771[/C][/ROW]
[ROW][C]203[/C][C]0.113112595189423[/C][C]0.226225190378846[/C][C]0.886887404810577[/C][/ROW]
[ROW][C]204[/C][C]0.198096603815308[/C][C]0.396193207630616[/C][C]0.801903396184692[/C][/ROW]
[ROW][C]205[/C][C]0.165595848058[/C][C]0.331191696116001[/C][C]0.834404151942[/C][/ROW]
[ROW][C]206[/C][C]0.191086568023615[/C][C]0.382173136047231[/C][C]0.808913431976385[/C][/ROW]
[ROW][C]207[/C][C]0.508687653528392[/C][C]0.982624692943215[/C][C]0.491312346471608[/C][/ROW]
[ROW][C]208[/C][C]0.612182963246249[/C][C]0.775634073507502[/C][C]0.387817036753751[/C][/ROW]
[ROW][C]209[/C][C]0.567770077806846[/C][C]0.864459844386308[/C][C]0.432229922193154[/C][/ROW]
[ROW][C]210[/C][C]0.517642559899437[/C][C]0.964714880201126[/C][C]0.482357440100563[/C][/ROW]
[ROW][C]211[/C][C]0.476431580130227[/C][C]0.952863160260453[/C][C]0.523568419869773[/C][/ROW]
[ROW][C]212[/C][C]0.428179948228018[/C][C]0.856359896456035[/C][C]0.571820051771982[/C][/ROW]
[ROW][C]213[/C][C]0.428350747254406[/C][C]0.856701494508812[/C][C]0.571649252745594[/C][/ROW]
[ROW][C]214[/C][C]0.385864812858538[/C][C]0.771729625717076[/C][C]0.614135187141462[/C][/ROW]
[ROW][C]215[/C][C]0.448036914349905[/C][C]0.89607382869981[/C][C]0.551963085650095[/C][/ROW]
[ROW][C]216[/C][C]0.705578386672887[/C][C]0.588843226654227[/C][C]0.294421613327113[/C][/ROW]
[ROW][C]217[/C][C]0.653631976671445[/C][C]0.692736046657111[/C][C]0.346368023328555[/C][/ROW]
[ROW][C]218[/C][C]0.591838467494697[/C][C]0.816323065010606[/C][C]0.408161532505303[/C][/ROW]
[ROW][C]219[/C][C]0.561599211543044[/C][C]0.876801576913912[/C][C]0.438400788456956[/C][/ROW]
[ROW][C]220[/C][C]0.53100072943507[/C][C]0.93799854112986[/C][C]0.46899927056493[/C][/ROW]
[ROW][C]221[/C][C]0.492963299074752[/C][C]0.985926598149503[/C][C]0.507036700925248[/C][/ROW]
[ROW][C]222[/C][C]0.437712778287463[/C][C]0.875425556574925[/C][C]0.562287221712537[/C][/ROW]
[ROW][C]223[/C][C]0.421111557776988[/C][C]0.842223115553976[/C][C]0.578888442223012[/C][/ROW]
[ROW][C]224[/C][C]0.618304597770255[/C][C]0.763390804459491[/C][C]0.381695402229745[/C][/ROW]
[ROW][C]225[/C][C]0.712317837603984[/C][C]0.575364324792033[/C][C]0.287682162396016[/C][/ROW]
[ROW][C]226[/C][C]0.640806339158418[/C][C]0.718387321683164[/C][C]0.359193660841582[/C][/ROW]
[ROW][C]227[/C][C]0.561619156977362[/C][C]0.876761686045277[/C][C]0.438380843022639[/C][/ROW]
[ROW][C]228[/C][C]0.707950011879156[/C][C]0.584099976241689[/C][C]0.292049988120844[/C][/ROW]
[ROW][C]229[/C][C]0.664424471345979[/C][C]0.671151057308042[/C][C]0.335575528654021[/C][/ROW]
[ROW][C]230[/C][C]0.568701930557582[/C][C]0.862596138884835[/C][C]0.431298069442418[/C][/ROW]
[ROW][C]231[/C][C]0.476056966344436[/C][C]0.952113932688873[/C][C]0.523943033655564[/C][/ROW]
[ROW][C]232[/C][C]0.367216093178731[/C][C]0.734432186357462[/C][C]0.632783906821269[/C][/ROW]
[ROW][C]233[/C][C]0.270937609662818[/C][C]0.541875219325635[/C][C]0.729062390337182[/C][/ROW]
[ROW][C]234[/C][C]0.631735814951489[/C][C]0.736528370097022[/C][C]0.368264185048511[/C][/ROW]
[ROW][C]235[/C][C]0.603028854506466[/C][C]0.793942290987068[/C][C]0.396971145493534[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190472&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190472&T=5

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
17	0.0875608272989696	0.175121654597939	0.91243917270103
18	0.282106937241268	0.564213874482536	0.717893062758732
19	0.223581484759997	0.447162969519994	0.776418515240003
20	0.254220148570916	0.508440297141832	0.745779851429084
21	0.190438483090145	0.38087696618029	0.809561516909855
22	0.532662560846844	0.934674878306312	0.467337439153156
23	0.562507113283741	0.874985773432518	0.437492886716259
24	0.562892516385805	0.87421496722839	0.437107483614195
25	0.478428651312634	0.956857302625268	0.521571348687366
26	0.591250476191283	0.817499047617434	0.408749523808717
27	0.517031783125763	0.965936433748473	0.482968216874237
28	0.613372758960775	0.773254482078451	0.386627241039225
29	0.565768542050577	0.868462915898847	0.434231457949423
30	0.548448906241801	0.903102187516398	0.451551093758199
31	0.493656031404474	0.987312062808948	0.506343968595526
32	0.582271584439543	0.835456831120914	0.417728415560457
33	0.56759574207652	0.86480851584696	0.43240425792348
34	0.569092785968105	0.861814428063789	0.430907214031895
35	0.505080250572285	0.98983949885543	0.494919749427715
36	0.464960648580599	0.929921297161198	0.535039351419401
37	0.417162569738874	0.834325139477747	0.582837430261127
38	0.384951077351747	0.769902154703493	0.615048922648253
39	0.512197880937745	0.97560423812451	0.487802119062255
40	0.452500605698638	0.905001211397275	0.547499394301362
41	0.405249131518417	0.810498263036834	0.594750868481583
42	0.438156894770931	0.876313789541862	0.561843105229069
43	0.408501101828578	0.817002203657155	0.591498898171422
44	0.456591779959702	0.913183559919404	0.543408220040298
45	0.446625117853909	0.893250235707818	0.553374882146091
46	0.409654451500503	0.819308903001006	0.590345548499497
47	0.365651400127452	0.731302800254904	0.634348599872548
48	0.358133741208017	0.716267482416033	0.641866258791983
49	0.347080679638731	0.694161359277463	0.652919320361269
50	0.327298415305346	0.654596830610691	0.672701584694654
51	0.348437216225556	0.696874432451113	0.651562783774444
52	0.313643518632375	0.627287037264749	0.686356481367626
53	0.295808354905858	0.591616709811717	0.704191645094142
54	0.301900719711694	0.603801439423388	0.698099280288306
55	0.283561781289988	0.567123562579977	0.716438218710012
56	0.285115422129288	0.570230844258576	0.714884577870712
57	0.304742752884724	0.609485505769449	0.695257247115276
58	0.28302689384604	0.56605378769208	0.71697310615396
59	0.270084611287896	0.540169222575792	0.729915388712104
60	0.235777259595732	0.471554519191464	0.764222740404268
61	0.212094914305745	0.424189828611489	0.787905085694255
62	0.230175573662175	0.460351147324349	0.769824426337825
63	0.210157861318919	0.420315722637837	0.789842138681081
64	0.184443440959128	0.368886881918256	0.815556559040872
65	0.15706335871021	0.31412671742042	0.84293664128979
66	0.14397290692389	0.287945813847781	0.85602709307611
67	0.162569116093629	0.325138232187258	0.837430883906371
68	0.138087747606039	0.276175495212077	0.861912252393961
69	0.121712306743581	0.243424613487162	0.878287693256419
70	0.101627535052303	0.203255070104606	0.898372464947697
71	0.114281916163938	0.228563832327875	0.885718083836062
72	0.124476202244355	0.248952404488711	0.875523797755645
73	0.108351811388254	0.216703622776509	0.891648188611746
74	0.0961097724236941	0.192219544847388	0.903890227576306
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197	0.0527616256386792	0.105523251277358	0.947238374361321
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199	0.0348929353282485	0.069785870656497	0.965107064671752
200	0.0936016809706487	0.187203361941297	0.906398319029351
201	0.078337363326737	0.156674726653474	0.921662636673263
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203	0.113112595189423	0.226225190378846	0.886887404810577
204	0.198096603815308	0.396193207630616	0.801903396184692
205	0.165595848058	0.331191696116001	0.834404151942
206	0.191086568023615	0.382173136047231	0.808913431976385
207	0.508687653528392	0.982624692943215	0.491312346471608
208	0.612182963246249	0.775634073507502	0.387817036753751
209	0.567770077806846	0.864459844386308	0.432229922193154
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224	0.618304597770255	0.763390804459491	0.381695402229745
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226	0.640806339158418	0.718387321683164	0.359193660841582
227	0.561619156977362	0.876761686045277	0.438380843022639
228	0.707950011879156	0.584099976241689	0.292049988120844
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230	0.568701930557582	0.862596138884835	0.431298069442418
231	0.476056966344436	0.952113932688873	0.523943033655564
232	0.367216093178731	0.734432186357462	0.632783906821269
233	0.270937609662818	0.541875219325635	0.729062390337182
234	0.631735814951489	0.736528370097022	0.368264185048511
235	0.603028854506466	0.793942290987068	0.396971145493534

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	0	0	OK
10% type I error level	10	0.045662100456621	OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 10 & 0.045662100456621 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190472&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]10[/C][C]0.045662100456621[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190472&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190472&T=6

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	0	0	OK
10% type I error level	10	0.045662100456621	OK

Figure 1

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code