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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 24 Nov 2011 12:30:31 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/24/t1322155878rrdq1mz5eeie9x9.htm/, Retrieved Thu, 31 Oct 2024 23:10:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147113, Retrieved Thu, 31 Oct 2024 23:10:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [MLS 1] [2011-11-24 13:53:28] [9c3137400ced3280b419f1e434c29e1d]
-   PD    [Multiple Regression] [MLS 2] [2011-11-24 17:30:31] [e5e604418bec6ffe5109fb01f8a59ccb] [Current]
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Dataseries X:
61	80	41	568	10173
81	111	50	1110	10083
87	122	46	338	10258
87	131	36	555	10154
136	192	67	281	10207
147	188	104	571	10133
168	216	115	322	10197
185	238	125	503	10184
137	173	97	1078	10163
125	160	88	582	10104
64	93	27	926	10127
45	67	19	491	10164
35	60	9	504	10219
-4	32	-47	314	10177
88	126	46	269	10138
85	131	36	252	10164
95	134	51	342	10223
128	162	90	1464	10122
186	230	142	921	10161
182	232	119	115	10199
151	200	92	789	10160
106	143	70	495	10157
60	85	30	1279	10113
44	66	19	391	10276
30	54	2	352	10303
54	81	21	340	10232
72	100	41	715	10140
88	126	46	425	10121
153	204	94	413	10188
168	218	114	935	10164
181	227	130	680	10165
180	220	141	1472	10121
149	220	109	767	10166
84	120	46	1215	10091
85	110	58	1113	10121
42	67	17	711	10180
54	81	22	742	10197
30	52	5	225	10289
96	106	17	107	10220
110	156	57	457	10106
141	187	91	448	10141
159	204	106	385	10165
164	204	125	1518	10152
155	196	111	495	10188
135	204	99	1283	10110
93	124	63	751	10144
28	53	3	674	10206
56	77	30	1705	10045
56	77	30	894	10100
22	50	-9	309	10147
76	105	42	745	10149
83	125	38	806	10116
121	165	73	423	10138
151	194	102	506	10183
208	263	149	148	10174
179	225	132	494	10143
139	263	108	1794	10120
99	140	58	1329	10143
103	127	66	289	10181
57	86	24	1213	10161
44	71	15	1263	10121
70	95	43	910	10095
58	95	17	934	10114
91	133	47	228	10173
126	178	63	366	10164
146	160	101	45	10174
199	250	142	459	10155
194	251	131	253	10182
145	250	107	999	10109
131	173	85	182	10198
74	103	38	483	10167
-3	21	-36	401	10178
7	29	-15	47	10143
10	39	-21	665	10127
34	71	-3	102	10183
94	148	35	22	10178
105	144	62	445	10142
151	199	91	378	10207
162	206	110	419	10176
175	224	127	1046	10145
128	206	79	531	10172
115	152	76	809	10157
62	88	32	1416	10086
11	35	-18	369	10151
-7	23	-39	20	10236
64	92	30	882	10160
80	117	43	262	10233
77	120	26	186	10212
127	173	74	763	10150
158	202	111	1038	10100
173	217	123	558	10178
206	256	151	335	10161
147	217	95	242	10217
103	143	59	898	10173
73	95	47	498	10067
52	77	21	757	10117
52	76	23	843	10149
68	100	33	133	10238
77	108	39	1035	10211
94	132	61	1117	10030
147	195	91	341	10165
160	198	123	1304	10142
166	204	124	566	10126
167	212	112	756	10176
155	204	122	1761	10095
104	129	70	1469	10105
44	73	11	1370	10172
53	77	29	795	10180
56	80	26	920	10126
36	64	2	754	10154
76	109	38	1034	10107
99	138	58	617	10133
142	185	92	706	10158
150	198	97	832	10173
190	237	138	393	10171
176	223	127	1551	10130
175	237	136	675	10105
112	146	80	1225	10154
73	102	38	737	10206
52	77	23	1444	10078
48	70	22	452	10233
61	86	30	1157	10179
68	98	32	718	10197
97	141	55	419	10075
146	195	96	898	10147
160	205	110	417	10195
155	191	117	1207	10129
175	226	125	163	10175
163	191	127	643	10128
117	147	86	1333	10099
82	100	62	1625	10015
55	74	33	970	10079
32	56	6	787	10112
48	77	17	995	10170
53	80	24	669	10048
82	120	44	861	10119
139	186	85	247	10180
150	196	95	349	10168
184	229	140	994	10141
185	229	139	1213	10149
138	229	104	2540	10117
147	176	117	388	10140
77	104	42	907	10216
32	61	-4	778	10227
48	72	23	729	10209
72	99	42	1428	10097
76	113	34	462	10176
94	140	44	528	10158
133	174	89	325	10132
164	209	116	777	10154
174	205	133	686	10145
187	229	141	1464	10153
149	215	104	438	10199
102	136	63	792	10111
86	113	52	1089	10071
35	57	13	920	10151
31	55	2	680	10148
28	66	-10	206	10206
75	125	23	177	10235
102	149	45	438	10170
133	176	83	800	10164
178	230	114	278	10161
190	238	137	396	10155
190	245	132	101	10181
147	238	87	785	10200
83	124	39	724	10133
83	111	52	556	10139
46	72	18	905	10169
40	63	12	1199	10080
50	78	19	688	10191
61	100	18	443	10202
102	149	49	710	10128
117	166	61	273	10160
158	201	105	752	10170
170	214	123	852	10158
190	231	150	1838	10110
155	214	113	765	10181
117	151	84	453	10093
68	97	33	792	10206
40	68	7	490	10180
56	81	30	562	10202
28	55	-2	731	10193
66	99	28	315	10158
103	146	57	623	10139
122	170	68	423	10167
166	218	111	726	10188
176	218	132	1137	10147
164	207	115	773	10173
160	218	114	971	10180
139	178	102	547	10166
75	105	40	1004	10149
44	67	16	538	10167
22	47	-7	149	10243
32	55	11	504	10148
42	73	7	619	10105
86	124	47	176	10144
140	185	93	908	10136
163	213	104	290	10208
222	278	159	155	10192
166	205	129	2681	10111
183	278	140	179	10139
140	171	100	1243	10112
98	125	67	973	10147
69	92	44	860	10205
75	96	49	1029	10154
63	92	32	772	10087
81	118	40	805	10151
126	185	63	3	10217
139	183	92	1237	10106
171	215	133	939	10117
170	207	134	1799	10115
173	214	126	534	10148
144	207	102	1042	10191
105	142	64	270	10238
75	102	43	724	10183
41	66	16	783	10206
68	87	43	648	10138
53	90	11	465	10238
61	90	26	1292	10052
87	133	40	318	10110
155	205	94	747	10156
159	201	113	298	10160
180	220	137	1145	10141
175	210	140	1456	10116
138	220	93	612	10176
105	136	67	1136	10146
73	95	44	903	1125
26	52	-3	609	10180
12	40	-14	532	10133
35	60	4	672	10141
64	100	25	568	10141
115	169	57	234	10140
138	184	87	778	10187
138	202	107	436	10169
182	226	140	795	10128
191	239	136	298	10164
155	226	112	284	10208
113	149	70	852	10165
98	121	72	1307	10036
29	50	3	1166	10064




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147113&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147113&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147113&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Temp[t] = + 16.9454597836053 + 0.338432075748612Max[t] + 0.691690738780124Min[t] -0.00592888756759133Neerslag[t] -4.2192403224102e-05Luchtdruk[t] -0.00555729391263462t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Temp[t] =  +  16.9454597836053 +  0.338432075748612Max[t] +  0.691690738780124Min[t] -0.00592888756759133Neerslag[t] -4.2192403224102e-05Luchtdruk[t] -0.00555729391263462t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147113&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Temp[t] =  +  16.9454597836053 +  0.338432075748612Max[t] +  0.691690738780124Min[t] -0.00592888756759133Neerslag[t] -4.2192403224102e-05Luchtdruk[t] -0.00555729391263462t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147113&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147113&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
Temp[t] = + 16.9454597836053 + 0.338432075748612Max[t] + 0.691690738780124Min[t] -0.00592888756759133Neerslag[t] -4.2192403224102e-05Luchtdruk[t] -0.00555729391263462t + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)16.94545978360536.4650022.62110.0093390.004669
Max0.3384320757486120.02111516.027800
Min0.6916907387801240.02924423.652300
Neerslag-0.005928887567591330.000907-6.538100
Luchtdruk-4.2192403224102e-050.000617-0.06830.9455720.472786
t-0.005557293912634620.005201-1.06840.2864380.143219

\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) & 16.9454597836053 & 6.465002 & 2.6211 & 0.009339 & 0.004669 \tabularnewline
Max & 0.338432075748612 & 0.021115 & 16.0278 & 0 & 0 \tabularnewline
Min & 0.691690738780124 & 0.029244 & 23.6523 & 0 & 0 \tabularnewline
Neerslag & -0.00592888756759133 & 0.000907 & -6.5381 & 0 & 0 \tabularnewline
Luchtdruk & -4.2192403224102e-05 & 0.000617 & -0.0683 & 0.945572 & 0.472786 \tabularnewline
t & -0.00555729391263462 & 0.005201 & -1.0684 & 0.286438 & 0.143219 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147113&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]16.9454597836053[/C][C]6.465002[/C][C]2.6211[/C][C]0.009339[/C][C]0.004669[/C][/ROW]
[ROW][C]Max[/C][C]0.338432075748612[/C][C]0.021115[/C][C]16.0278[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Min[/C][C]0.691690738780124[/C][C]0.029244[/C][C]23.6523[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Neerslag[/C][C]-0.00592888756759133[/C][C]0.000907[/C][C]-6.5381[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Luchtdruk[/C][C]-4.2192403224102e-05[/C][C]0.000617[/C][C]-0.0683[/C][C]0.945572[/C][C]0.472786[/C][/ROW]
[ROW][C]t[/C][C]-0.00555729391263462[/C][C]0.005201[/C][C]-1.0684[/C][C]0.286438[/C][C]0.143219[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147113&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147113&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
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)16.94545978360536.4650022.62110.0093390.004669
Max0.3384320757486120.02111516.027800
Min0.6916907387801240.02924423.652300
Neerslag-0.005928887567591330.000907-6.538100
Luchtdruk-4.2192403224102e-050.000617-0.06830.9455720.472786
t-0.005557293912634620.005201-1.06840.2864380.143219







Multiple Linear Regression - Regression Statistics
Multiple R0.994697259804353
R-squared0.989422638662289
Adjusted R-squared0.989196626667893
F-TEST (value)4377.7439392474
F-TEST (DF numerator)5
F-TEST (DF denominator)234
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation5.51961460989642
Sum Squared Residuals7129.078033377

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.994697259804353 \tabularnewline
R-squared & 0.989422638662289 \tabularnewline
Adjusted R-squared & 0.989196626667893 \tabularnewline
F-TEST (value) & 4377.7439392474 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 234 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 5.51961460989642 \tabularnewline
Sum Squared Residuals & 7129.078033377 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147113&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.994697259804353[/C][/ROW]
[ROW][C]R-squared[/C][C]0.989422638662289[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.989196626667893[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4377.7439392474[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]234[/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]5.51961460989642[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]7129.078033377[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147113&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147113&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 R0.994697259804353
R-squared0.989422638662289
Adjusted R-squared0.989196626667893
F-TEST (value)4377.7439392474
F-TEST (DF numerator)5
F-TEST (DF denominator)234
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation5.51961460989642
Sum Squared Residuals7129.078033377







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
16168.576957383176-7.57695738317595
28182.078351341147-1.07835134114697
38787.598501456965-0.598501456964982
48782.43974486475664.5602551352434
5136126.1432360898429.85676391015773
6147148.660252671037-1.66025267103686
7168167.2129843151910.787015684809387
8185180.4972599270574.50274007294344
9137135.7180527127431.28194728725662
10125128.030879370393-3.03087937039321
116461.11673018721052.88326981278954
124549.3559179865759-4.35591798657587
133539.9850326540657-4.9850326540657
14-4-7.103043413717233.10304341371723
158889.2996985635585-1.2996985635585
168584.16908834675290.830911653247088
179595.0180991289145-0.0180991289145289
18128124.8166283502763.18337164972398
19186187.010111069312-1.01011106931177
20182176.549611003115.4503889968904
21151143.0441526213477.95584737865276
22106110.273990278683-4.27399027868253
236058.32535165289571.67464834710428
244449.5389615914737-5.53896159147368
253033.9435642495646-3.9435642495646
265456.2919393491268-2.29193934912684
277274.3309551332902-2.33095513329018
288888.3032645530048-0.303264553004813
29153147.9648843887255.03511561127508
30168163.437324238294.56267576170997
31181179.0565315839291.94346841607055
32180179.5967253985670.403274601432579
33149161.635031540698-12.6350315406976
348481.55677292873692.44322707126309
358587.0706645024972-2.07066450249724
364246.5341311117907-4.53413111179071
375454.5405637868091-0.540563786809115
383036.0230869082727-6.02308690827274
399663.295670578944932.7043294210551
40110105.8090459089784.19095409102165
41141139.8642513357921.13574866420763
42159156.3599077103892.64009228961114
43164162.779593340461.22040665954048
44155156.446642152766-1.44664215276612
45135146.17958020367-11.1795802036704
469397.3513238980333-4.35132389803334
472832.2695533128665-4.26955331286649
485652.95612567871633.04387432128371
495657.7565756199429-1.7565756199429
502225.1038296524823-3.10382965248232
517676.4031848382534-0.403184838253374
528380.03923631187582.9607636881242
53121120.0499736107290.950026389271479
54151149.4239816118941.57601838810595
55208207.4026237481280.597376251871839
56179180.72781788262-1.72781788261952
57139169.275518323837-30.2755183238366
589995.81424106749433.18575893250567
59103103.107032458063-0.107032458063203
605754.69730076530242.30269923469762
614443.09528900388890.90471099611115
627072.6734365276299-2.67343652762993
635854.54082506815063.45917493184937
649192.3297140870182-1.32971408701821
65126117.8028452695768.19715473042351
66146139.8925096709986.10749032900187
67199196.2514016871242.74859831287592
68194190.1958899864153.80411001358454
69145168.831452806043-23.8314528060435
70131132.38957544516-1.38957544516018
717474.4010209328339-0.401020932833858
72-3-4.055376578087071.05537657808707
73715.272331181412-8.27233118141196
741010.8375727739848-0.837572773984845
753437.4478761280434-3.44787612804338
769490.2603587078423.73964129215802
77105105.070322543423-0.0703225434231767
78151144.1320538011276.86794619887317
79162159.3958686485062.60413135149447
80175173.524726736951.4752732630498
81128137.278474520539-9.27847452053909
82115115.274915062119-0.274915062119025
836259.57947332107082.42052667892924
841113.2572818505341-2.25728185053408
85-7-3.26937045992917-3.73062954007083
866462.69605198802221.30394801197775
878083.8161064384378-3.81610643843778
887773.51858430811353.48141569188648
89127121.2327302928235.76726970717705
90158155.0059260695582.99407393044177
91173171.2197138022291.78028619777139
92206205.1032073467830.896792653217018
93147153.713141496193-6.713141496193
9410399.87525022220063.12474977779941
957377.7006918487714-4.70069184877139
965252.0817064829332-0.0817064829331611
975252.6098641031161-0.609864103116138
986871.8493390640743-3.84933906407432
997773.3546654177513.645334582249
1009496.2101422394088-2.21014223940884
101147142.8716486590784.12835134092192
102160160.306942931059-0.306942931058943
103166167.399862933752-1.39986293375209
104167160.6728751224636.32712487753669
105155158.921654189595-3.92165418959488
10610499.29658604367444.70341395632564
1074440.11321189798773.88678810201231
1085357.3205890172509-4.32058901725095
1095655.5164231780690.483576821931038
1103634.47838889038551.52161110961455
1117672.94503612527083.05496387472923
1129999.0590729168721-0.059072916872108
113142137.9485824980724.0514175019278
114150145.0534231632274.94657683677273
115190189.2089031404750.791096859525384
116176169.9927767447616.00722325523852
117175186.145245479641-11.1452454796411
118112113.344732330985-1.34473233098468
1197372.28825580338480.711744196615154
1205249.26021265138072.73978734861933
1214852.0688567329985-4.0688567329985
1226158.83415121592692.16584878407314
1236866.87518248747241.12481751252763
1249799.108976298596-2.10897629859604
125146142.8950963871853.10490361281487
126160158.8072998783371.19270012166298
127155154.224492215620.775507784379675
128175177.785401253167-2.78540125316713
129163164.474219796121-1.47421979612103
130117117.12862203734-0.128622037339885
1318282.8884884446537-0.888488444653683
1325557.9053867996195-2.90538679961953
1333234.2159962707314-2.21599627073136
1344847.69045492067490.309545079325063
1355355.4799938456971-2.47999384569712
1368281.7041922837250.295807716275016
137139136.032235509112.96776449088979
138150145.7236661374294.2763338625707
139184184.189457302117-0.189457302117071
140185182.1934453528962.80655464710398
141138150.112428556389-12.1124285563885
142147153.919946472123-6.91994647212346
1437774.59017504557662.40982495442343
1443228.97862689037183.02137310962825
1454851.6627473308272-3.6627473308272
1467269.79741325836422.20258674163581
1477674.72035130512971.27964869487035
1489490.37882032802783.62117967197223
149133134.210698033378-1.21069803337838
150164162.0451279243081.95487207569171
151174172.9844933869431.01550661305686
152187182.0218197544264.97818024557367
153149157.766753858969-8.76675385896895
154102100.5706290234871.4293709765127
1558683.41334394932962.58665605067043
1563538.4782582077349-3.47825820773486
1573131.6102982291752-0.610298229175225
1582829.8350504507871-1.83505045078713
1597572.79349416555332.20650583444668
16010294.58280579383837.41719420616168
161133127.8531584737345.14684152626581
162178170.6603520599237.33964794007722
163190188.5717827853851.42821721461455
164190189.2247211577680.7752788422319
165147151.667895336616-4.66789533661588
1668380.24441497855462.75558502144535
1678385.8270202609877-2.82702026098767
1684647.0346793611689-1.03467936116887
1694038.09375113185311.90624886814692
1705051.0314883359118-1.03148833591178
1716159.23185930731291.76814069268711
17210295.67199588455786.32800411544223
173117112.3096464538674.69035354613274
174158151.7432452485736.256754751427
175170167.9953557895142.0046442104859
176190186.5749358241013.42506417589908
177155161.582176606994-6.58217660699388
178117122.049892968867-5.04989296886734
1796866.47811527976561.52188472023443
1804040.4656896287564-0.46568962875638
1815660.340828173781-4.34082817378104
1822828.4003310021466-0.400331002146627
1836666.5044011668075-0.504401166807453
184103100.6388871425462.36111285745371
185122117.548893919414.45110608059031
186166161.7334390555284.26656094447213
187176173.818344374252.18165562575001
188164160.488309759963.51169024004007
189160162.339599475296-2.33959947529625
190139143.010909308382-4.01090930838152
1917572.70620033291812.29379966708187
1924446.0017485730748-2.0017485730748
1932225.6217934133951-3.62179341339508
1943238.6733792153249-6.67337921532493
1954241.31282853283240.687171467167553
1968688.8597883420212-2.85978834202118
197140136.9767534924093.0232465075915
198163157.7169071097785.28309289022234
199222218.5535002725083.44649972749198
200166158.1187268744687.88127312553153
201183205.260204543609-22.2602045436091
202140135.067588416364.93241158364008
2039898.2676841674039-0.26768416740387
2046971.852498517595-2.85249851759502
2057575.6592930342189-0.659293034218945
2066364.0678158739368-1.06781587393674
2078178.19666485619222.80333514380785
208126121.5271267599754.47287324002519
209139133.5921728375395.40782716246129
210171174.542106636273-3.54210663627349
211170167.422024551832.57797544817002
212173171.7506163016131.24938369838673
213144149.761767589062-5.76176758906236
214105106.048995457074-1.04899545707423
2157575.2912552453254-0.291255245325384
2164144.0757184856373-3.07571848563734
2176870.656153634553-2.65615363455296
2185350.6125561114692.387443888531
2196156.08701766785994.91298233214012
2208786.08999930550620.910000694493756
221155145.2574177425759.74258225742465
222159159.702157930726-0.702157930726228
223180177.7064216926722.2935783073284
224175174.5487866341730.451213365827084
225138150.419534937934-12.4195349379342
226105100.8962527595344.10374724046616
2277372.86814184071870.131858159281319
2282627.1615813006275-1.16158130062753
2291215.9447483568063-3.94474835680626
2303534.32788407721950.672115922780495
2316463.00171963466340.998280365336565
232115110.4623698483484.5376301516523
233138133.0567179743474.94328202565326
234138155.005191830886-17.0051918308859
235182183.821057986451-1.8210579864509
236191188.3934929167272.60650708327345
237155167.468888867563-12.4688888675634
238113108.9872568471894.01274315281077
2399898.1967818866376-0.196781886637568
2402927.27067799848511.72932200151494

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 61 & 68.576957383176 & -7.57695738317595 \tabularnewline
2 & 81 & 82.078351341147 & -1.07835134114697 \tabularnewline
3 & 87 & 87.598501456965 & -0.598501456964982 \tabularnewline
4 & 87 & 82.4397448647566 & 4.5602551352434 \tabularnewline
5 & 136 & 126.143236089842 & 9.85676391015773 \tabularnewline
6 & 147 & 148.660252671037 & -1.66025267103686 \tabularnewline
7 & 168 & 167.212984315191 & 0.787015684809387 \tabularnewline
8 & 185 & 180.497259927057 & 4.50274007294344 \tabularnewline
9 & 137 & 135.718052712743 & 1.28194728725662 \tabularnewline
10 & 125 & 128.030879370393 & -3.03087937039321 \tabularnewline
11 & 64 & 61.1167301872105 & 2.88326981278954 \tabularnewline
12 & 45 & 49.3559179865759 & -4.35591798657587 \tabularnewline
13 & 35 & 39.9850326540657 & -4.9850326540657 \tabularnewline
14 & -4 & -7.10304341371723 & 3.10304341371723 \tabularnewline
15 & 88 & 89.2996985635585 & -1.2996985635585 \tabularnewline
16 & 85 & 84.1690883467529 & 0.830911653247088 \tabularnewline
17 & 95 & 95.0180991289145 & -0.0180991289145289 \tabularnewline
18 & 128 & 124.816628350276 & 3.18337164972398 \tabularnewline
19 & 186 & 187.010111069312 & -1.01011106931177 \tabularnewline
20 & 182 & 176.54961100311 & 5.4503889968904 \tabularnewline
21 & 151 & 143.044152621347 & 7.95584737865276 \tabularnewline
22 & 106 & 110.273990278683 & -4.27399027868253 \tabularnewline
23 & 60 & 58.3253516528957 & 1.67464834710428 \tabularnewline
24 & 44 & 49.5389615914737 & -5.53896159147368 \tabularnewline
25 & 30 & 33.9435642495646 & -3.9435642495646 \tabularnewline
26 & 54 & 56.2919393491268 & -2.29193934912684 \tabularnewline
27 & 72 & 74.3309551332902 & -2.33095513329018 \tabularnewline
28 & 88 & 88.3032645530048 & -0.303264553004813 \tabularnewline
29 & 153 & 147.964884388725 & 5.03511561127508 \tabularnewline
30 & 168 & 163.43732423829 & 4.56267576170997 \tabularnewline
31 & 181 & 179.056531583929 & 1.94346841607055 \tabularnewline
32 & 180 & 179.596725398567 & 0.403274601432579 \tabularnewline
33 & 149 & 161.635031540698 & -12.6350315406976 \tabularnewline
34 & 84 & 81.5567729287369 & 2.44322707126309 \tabularnewline
35 & 85 & 87.0706645024972 & -2.07066450249724 \tabularnewline
36 & 42 & 46.5341311117907 & -4.53413111179071 \tabularnewline
37 & 54 & 54.5405637868091 & -0.540563786809115 \tabularnewline
38 & 30 & 36.0230869082727 & -6.02308690827274 \tabularnewline
39 & 96 & 63.2956705789449 & 32.7043294210551 \tabularnewline
40 & 110 & 105.809045908978 & 4.19095409102165 \tabularnewline
41 & 141 & 139.864251335792 & 1.13574866420763 \tabularnewline
42 & 159 & 156.359907710389 & 2.64009228961114 \tabularnewline
43 & 164 & 162.77959334046 & 1.22040665954048 \tabularnewline
44 & 155 & 156.446642152766 & -1.44664215276612 \tabularnewline
45 & 135 & 146.17958020367 & -11.1795802036704 \tabularnewline
46 & 93 & 97.3513238980333 & -4.35132389803334 \tabularnewline
47 & 28 & 32.2695533128665 & -4.26955331286649 \tabularnewline
48 & 56 & 52.9561256787163 & 3.04387432128371 \tabularnewline
49 & 56 & 57.7565756199429 & -1.7565756199429 \tabularnewline
50 & 22 & 25.1038296524823 & -3.10382965248232 \tabularnewline
51 & 76 & 76.4031848382534 & -0.403184838253374 \tabularnewline
52 & 83 & 80.0392363118758 & 2.9607636881242 \tabularnewline
53 & 121 & 120.049973610729 & 0.950026389271479 \tabularnewline
54 & 151 & 149.423981611894 & 1.57601838810595 \tabularnewline
55 & 208 & 207.402623748128 & 0.597376251871839 \tabularnewline
56 & 179 & 180.72781788262 & -1.72781788261952 \tabularnewline
57 & 139 & 169.275518323837 & -30.2755183238366 \tabularnewline
58 & 99 & 95.8142410674943 & 3.18575893250567 \tabularnewline
59 & 103 & 103.107032458063 & -0.107032458063203 \tabularnewline
60 & 57 & 54.6973007653024 & 2.30269923469762 \tabularnewline
61 & 44 & 43.0952890038889 & 0.90471099611115 \tabularnewline
62 & 70 & 72.6734365276299 & -2.67343652762993 \tabularnewline
63 & 58 & 54.5408250681506 & 3.45917493184937 \tabularnewline
64 & 91 & 92.3297140870182 & -1.32971408701821 \tabularnewline
65 & 126 & 117.802845269576 & 8.19715473042351 \tabularnewline
66 & 146 & 139.892509670998 & 6.10749032900187 \tabularnewline
67 & 199 & 196.251401687124 & 2.74859831287592 \tabularnewline
68 & 194 & 190.195889986415 & 3.80411001358454 \tabularnewline
69 & 145 & 168.831452806043 & -23.8314528060435 \tabularnewline
70 & 131 & 132.38957544516 & -1.38957544516018 \tabularnewline
71 & 74 & 74.4010209328339 & -0.401020932833858 \tabularnewline
72 & -3 & -4.05537657808707 & 1.05537657808707 \tabularnewline
73 & 7 & 15.272331181412 & -8.27233118141196 \tabularnewline
74 & 10 & 10.8375727739848 & -0.837572773984845 \tabularnewline
75 & 34 & 37.4478761280434 & -3.44787612804338 \tabularnewline
76 & 94 & 90.260358707842 & 3.73964129215802 \tabularnewline
77 & 105 & 105.070322543423 & -0.0703225434231767 \tabularnewline
78 & 151 & 144.132053801127 & 6.86794619887317 \tabularnewline
79 & 162 & 159.395868648506 & 2.60413135149447 \tabularnewline
80 & 175 & 173.52472673695 & 1.4752732630498 \tabularnewline
81 & 128 & 137.278474520539 & -9.27847452053909 \tabularnewline
82 & 115 & 115.274915062119 & -0.274915062119025 \tabularnewline
83 & 62 & 59.5794733210708 & 2.42052667892924 \tabularnewline
84 & 11 & 13.2572818505341 & -2.25728185053408 \tabularnewline
85 & -7 & -3.26937045992917 & -3.73062954007083 \tabularnewline
86 & 64 & 62.6960519880222 & 1.30394801197775 \tabularnewline
87 & 80 & 83.8161064384378 & -3.81610643843778 \tabularnewline
88 & 77 & 73.5185843081135 & 3.48141569188648 \tabularnewline
89 & 127 & 121.232730292823 & 5.76726970717705 \tabularnewline
90 & 158 & 155.005926069558 & 2.99407393044177 \tabularnewline
91 & 173 & 171.219713802229 & 1.78028619777139 \tabularnewline
92 & 206 & 205.103207346783 & 0.896792653217018 \tabularnewline
93 & 147 & 153.713141496193 & -6.713141496193 \tabularnewline
94 & 103 & 99.8752502222006 & 3.12474977779941 \tabularnewline
95 & 73 & 77.7006918487714 & -4.70069184877139 \tabularnewline
96 & 52 & 52.0817064829332 & -0.0817064829331611 \tabularnewline
97 & 52 & 52.6098641031161 & -0.609864103116138 \tabularnewline
98 & 68 & 71.8493390640743 & -3.84933906407432 \tabularnewline
99 & 77 & 73.354665417751 & 3.645334582249 \tabularnewline
100 & 94 & 96.2101422394088 & -2.21014223940884 \tabularnewline
101 & 147 & 142.871648659078 & 4.12835134092192 \tabularnewline
102 & 160 & 160.306942931059 & -0.306942931058943 \tabularnewline
103 & 166 & 167.399862933752 & -1.39986293375209 \tabularnewline
104 & 167 & 160.672875122463 & 6.32712487753669 \tabularnewline
105 & 155 & 158.921654189595 & -3.92165418959488 \tabularnewline
106 & 104 & 99.2965860436744 & 4.70341395632564 \tabularnewline
107 & 44 & 40.1132118979877 & 3.88678810201231 \tabularnewline
108 & 53 & 57.3205890172509 & -4.32058901725095 \tabularnewline
109 & 56 & 55.516423178069 & 0.483576821931038 \tabularnewline
110 & 36 & 34.4783888903855 & 1.52161110961455 \tabularnewline
111 & 76 & 72.9450361252708 & 3.05496387472923 \tabularnewline
112 & 99 & 99.0590729168721 & -0.059072916872108 \tabularnewline
113 & 142 & 137.948582498072 & 4.0514175019278 \tabularnewline
114 & 150 & 145.053423163227 & 4.94657683677273 \tabularnewline
115 & 190 & 189.208903140475 & 0.791096859525384 \tabularnewline
116 & 176 & 169.992776744761 & 6.00722325523852 \tabularnewline
117 & 175 & 186.145245479641 & -11.1452454796411 \tabularnewline
118 & 112 & 113.344732330985 & -1.34473233098468 \tabularnewline
119 & 73 & 72.2882558033848 & 0.711744196615154 \tabularnewline
120 & 52 & 49.2602126513807 & 2.73978734861933 \tabularnewline
121 & 48 & 52.0688567329985 & -4.0688567329985 \tabularnewline
122 & 61 & 58.8341512159269 & 2.16584878407314 \tabularnewline
123 & 68 & 66.8751824874724 & 1.12481751252763 \tabularnewline
124 & 97 & 99.108976298596 & -2.10897629859604 \tabularnewline
125 & 146 & 142.895096387185 & 3.10490361281487 \tabularnewline
126 & 160 & 158.807299878337 & 1.19270012166298 \tabularnewline
127 & 155 & 154.22449221562 & 0.775507784379675 \tabularnewline
128 & 175 & 177.785401253167 & -2.78540125316713 \tabularnewline
129 & 163 & 164.474219796121 & -1.47421979612103 \tabularnewline
130 & 117 & 117.12862203734 & -0.128622037339885 \tabularnewline
131 & 82 & 82.8884884446537 & -0.888488444653683 \tabularnewline
132 & 55 & 57.9053867996195 & -2.90538679961953 \tabularnewline
133 & 32 & 34.2159962707314 & -2.21599627073136 \tabularnewline
134 & 48 & 47.6904549206749 & 0.309545079325063 \tabularnewline
135 & 53 & 55.4799938456971 & -2.47999384569712 \tabularnewline
136 & 82 & 81.704192283725 & 0.295807716275016 \tabularnewline
137 & 139 & 136.03223550911 & 2.96776449088979 \tabularnewline
138 & 150 & 145.723666137429 & 4.2763338625707 \tabularnewline
139 & 184 & 184.189457302117 & -0.189457302117071 \tabularnewline
140 & 185 & 182.193445352896 & 2.80655464710398 \tabularnewline
141 & 138 & 150.112428556389 & -12.1124285563885 \tabularnewline
142 & 147 & 153.919946472123 & -6.91994647212346 \tabularnewline
143 & 77 & 74.5901750455766 & 2.40982495442343 \tabularnewline
144 & 32 & 28.9786268903718 & 3.02137310962825 \tabularnewline
145 & 48 & 51.6627473308272 & -3.6627473308272 \tabularnewline
146 & 72 & 69.7974132583642 & 2.20258674163581 \tabularnewline
147 & 76 & 74.7203513051297 & 1.27964869487035 \tabularnewline
148 & 94 & 90.3788203280278 & 3.62117967197223 \tabularnewline
149 & 133 & 134.210698033378 & -1.21069803337838 \tabularnewline
150 & 164 & 162.045127924308 & 1.95487207569171 \tabularnewline
151 & 174 & 172.984493386943 & 1.01550661305686 \tabularnewline
152 & 187 & 182.021819754426 & 4.97818024557367 \tabularnewline
153 & 149 & 157.766753858969 & -8.76675385896895 \tabularnewline
154 & 102 & 100.570629023487 & 1.4293709765127 \tabularnewline
155 & 86 & 83.4133439493296 & 2.58665605067043 \tabularnewline
156 & 35 & 38.4782582077349 & -3.47825820773486 \tabularnewline
157 & 31 & 31.6102982291752 & -0.610298229175225 \tabularnewline
158 & 28 & 29.8350504507871 & -1.83505045078713 \tabularnewline
159 & 75 & 72.7934941655533 & 2.20650583444668 \tabularnewline
160 & 102 & 94.5828057938383 & 7.41719420616168 \tabularnewline
161 & 133 & 127.853158473734 & 5.14684152626581 \tabularnewline
162 & 178 & 170.660352059923 & 7.33964794007722 \tabularnewline
163 & 190 & 188.571782785385 & 1.42821721461455 \tabularnewline
164 & 190 & 189.224721157768 & 0.7752788422319 \tabularnewline
165 & 147 & 151.667895336616 & -4.66789533661588 \tabularnewline
166 & 83 & 80.2444149785546 & 2.75558502144535 \tabularnewline
167 & 83 & 85.8270202609877 & -2.82702026098767 \tabularnewline
168 & 46 & 47.0346793611689 & -1.03467936116887 \tabularnewline
169 & 40 & 38.0937511318531 & 1.90624886814692 \tabularnewline
170 & 50 & 51.0314883359118 & -1.03148833591178 \tabularnewline
171 & 61 & 59.2318593073129 & 1.76814069268711 \tabularnewline
172 & 102 & 95.6719958845578 & 6.32800411544223 \tabularnewline
173 & 117 & 112.309646453867 & 4.69035354613274 \tabularnewline
174 & 158 & 151.743245248573 & 6.256754751427 \tabularnewline
175 & 170 & 167.995355789514 & 2.0046442104859 \tabularnewline
176 & 190 & 186.574935824101 & 3.42506417589908 \tabularnewline
177 & 155 & 161.582176606994 & -6.58217660699388 \tabularnewline
178 & 117 & 122.049892968867 & -5.04989296886734 \tabularnewline
179 & 68 & 66.4781152797656 & 1.52188472023443 \tabularnewline
180 & 40 & 40.4656896287564 & -0.46568962875638 \tabularnewline
181 & 56 & 60.340828173781 & -4.34082817378104 \tabularnewline
182 & 28 & 28.4003310021466 & -0.400331002146627 \tabularnewline
183 & 66 & 66.5044011668075 & -0.504401166807453 \tabularnewline
184 & 103 & 100.638887142546 & 2.36111285745371 \tabularnewline
185 & 122 & 117.54889391941 & 4.45110608059031 \tabularnewline
186 & 166 & 161.733439055528 & 4.26656094447213 \tabularnewline
187 & 176 & 173.81834437425 & 2.18165562575001 \tabularnewline
188 & 164 & 160.48830975996 & 3.51169024004007 \tabularnewline
189 & 160 & 162.339599475296 & -2.33959947529625 \tabularnewline
190 & 139 & 143.010909308382 & -4.01090930838152 \tabularnewline
191 & 75 & 72.7062003329181 & 2.29379966708187 \tabularnewline
192 & 44 & 46.0017485730748 & -2.0017485730748 \tabularnewline
193 & 22 & 25.6217934133951 & -3.62179341339508 \tabularnewline
194 & 32 & 38.6733792153249 & -6.67337921532493 \tabularnewline
195 & 42 & 41.3128285328324 & 0.687171467167553 \tabularnewline
196 & 86 & 88.8597883420212 & -2.85978834202118 \tabularnewline
197 & 140 & 136.976753492409 & 3.0232465075915 \tabularnewline
198 & 163 & 157.716907109778 & 5.28309289022234 \tabularnewline
199 & 222 & 218.553500272508 & 3.44649972749198 \tabularnewline
200 & 166 & 158.118726874468 & 7.88127312553153 \tabularnewline
201 & 183 & 205.260204543609 & -22.2602045436091 \tabularnewline
202 & 140 & 135.06758841636 & 4.93241158364008 \tabularnewline
203 & 98 & 98.2676841674039 & -0.26768416740387 \tabularnewline
204 & 69 & 71.852498517595 & -2.85249851759502 \tabularnewline
205 & 75 & 75.6592930342189 & -0.659293034218945 \tabularnewline
206 & 63 & 64.0678158739368 & -1.06781587393674 \tabularnewline
207 & 81 & 78.1966648561922 & 2.80333514380785 \tabularnewline
208 & 126 & 121.527126759975 & 4.47287324002519 \tabularnewline
209 & 139 & 133.592172837539 & 5.40782716246129 \tabularnewline
210 & 171 & 174.542106636273 & -3.54210663627349 \tabularnewline
211 & 170 & 167.42202455183 & 2.57797544817002 \tabularnewline
212 & 173 & 171.750616301613 & 1.24938369838673 \tabularnewline
213 & 144 & 149.761767589062 & -5.76176758906236 \tabularnewline
214 & 105 & 106.048995457074 & -1.04899545707423 \tabularnewline
215 & 75 & 75.2912552453254 & -0.291255245325384 \tabularnewline
216 & 41 & 44.0757184856373 & -3.07571848563734 \tabularnewline
217 & 68 & 70.656153634553 & -2.65615363455296 \tabularnewline
218 & 53 & 50.612556111469 & 2.387443888531 \tabularnewline
219 & 61 & 56.0870176678599 & 4.91298233214012 \tabularnewline
220 & 87 & 86.0899993055062 & 0.910000694493756 \tabularnewline
221 & 155 & 145.257417742575 & 9.74258225742465 \tabularnewline
222 & 159 & 159.702157930726 & -0.702157930726228 \tabularnewline
223 & 180 & 177.706421692672 & 2.2935783073284 \tabularnewline
224 & 175 & 174.548786634173 & 0.451213365827084 \tabularnewline
225 & 138 & 150.419534937934 & -12.4195349379342 \tabularnewline
226 & 105 & 100.896252759534 & 4.10374724046616 \tabularnewline
227 & 73 & 72.8681418407187 & 0.131858159281319 \tabularnewline
228 & 26 & 27.1615813006275 & -1.16158130062753 \tabularnewline
229 & 12 & 15.9447483568063 & -3.94474835680626 \tabularnewline
230 & 35 & 34.3278840772195 & 0.672115922780495 \tabularnewline
231 & 64 & 63.0017196346634 & 0.998280365336565 \tabularnewline
232 & 115 & 110.462369848348 & 4.5376301516523 \tabularnewline
233 & 138 & 133.056717974347 & 4.94328202565326 \tabularnewline
234 & 138 & 155.005191830886 & -17.0051918308859 \tabularnewline
235 & 182 & 183.821057986451 & -1.8210579864509 \tabularnewline
236 & 191 & 188.393492916727 & 2.60650708327345 \tabularnewline
237 & 155 & 167.468888867563 & -12.4688888675634 \tabularnewline
238 & 113 & 108.987256847189 & 4.01274315281077 \tabularnewline
239 & 98 & 98.1967818866376 & -0.196781886637568 \tabularnewline
240 & 29 & 27.2706779984851 & 1.72932200151494 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147113&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]61[/C][C]68.576957383176[/C][C]-7.57695738317595[/C][/ROW]
[ROW][C]2[/C][C]81[/C][C]82.078351341147[/C][C]-1.07835134114697[/C][/ROW]
[ROW][C]3[/C][C]87[/C][C]87.598501456965[/C][C]-0.598501456964982[/C][/ROW]
[ROW][C]4[/C][C]87[/C][C]82.4397448647566[/C][C]4.5602551352434[/C][/ROW]
[ROW][C]5[/C][C]136[/C][C]126.143236089842[/C][C]9.85676391015773[/C][/ROW]
[ROW][C]6[/C][C]147[/C][C]148.660252671037[/C][C]-1.66025267103686[/C][/ROW]
[ROW][C]7[/C][C]168[/C][C]167.212984315191[/C][C]0.787015684809387[/C][/ROW]
[ROW][C]8[/C][C]185[/C][C]180.497259927057[/C][C]4.50274007294344[/C][/ROW]
[ROW][C]9[/C][C]137[/C][C]135.718052712743[/C][C]1.28194728725662[/C][/ROW]
[ROW][C]10[/C][C]125[/C][C]128.030879370393[/C][C]-3.03087937039321[/C][/ROW]
[ROW][C]11[/C][C]64[/C][C]61.1167301872105[/C][C]2.88326981278954[/C][/ROW]
[ROW][C]12[/C][C]45[/C][C]49.3559179865759[/C][C]-4.35591798657587[/C][/ROW]
[ROW][C]13[/C][C]35[/C][C]39.9850326540657[/C][C]-4.9850326540657[/C][/ROW]
[ROW][C]14[/C][C]-4[/C][C]-7.10304341371723[/C][C]3.10304341371723[/C][/ROW]
[ROW][C]15[/C][C]88[/C][C]89.2996985635585[/C][C]-1.2996985635585[/C][/ROW]
[ROW][C]16[/C][C]85[/C][C]84.1690883467529[/C][C]0.830911653247088[/C][/ROW]
[ROW][C]17[/C][C]95[/C][C]95.0180991289145[/C][C]-0.0180991289145289[/C][/ROW]
[ROW][C]18[/C][C]128[/C][C]124.816628350276[/C][C]3.18337164972398[/C][/ROW]
[ROW][C]19[/C][C]186[/C][C]187.010111069312[/C][C]-1.01011106931177[/C][/ROW]
[ROW][C]20[/C][C]182[/C][C]176.54961100311[/C][C]5.4503889968904[/C][/ROW]
[ROW][C]21[/C][C]151[/C][C]143.044152621347[/C][C]7.95584737865276[/C][/ROW]
[ROW][C]22[/C][C]106[/C][C]110.273990278683[/C][C]-4.27399027868253[/C][/ROW]
[ROW][C]23[/C][C]60[/C][C]58.3253516528957[/C][C]1.67464834710428[/C][/ROW]
[ROW][C]24[/C][C]44[/C][C]49.5389615914737[/C][C]-5.53896159147368[/C][/ROW]
[ROW][C]25[/C][C]30[/C][C]33.9435642495646[/C][C]-3.9435642495646[/C][/ROW]
[ROW][C]26[/C][C]54[/C][C]56.2919393491268[/C][C]-2.29193934912684[/C][/ROW]
[ROW][C]27[/C][C]72[/C][C]74.3309551332902[/C][C]-2.33095513329018[/C][/ROW]
[ROW][C]28[/C][C]88[/C][C]88.3032645530048[/C][C]-0.303264553004813[/C][/ROW]
[ROW][C]29[/C][C]153[/C][C]147.964884388725[/C][C]5.03511561127508[/C][/ROW]
[ROW][C]30[/C][C]168[/C][C]163.43732423829[/C][C]4.56267576170997[/C][/ROW]
[ROW][C]31[/C][C]181[/C][C]179.056531583929[/C][C]1.94346841607055[/C][/ROW]
[ROW][C]32[/C][C]180[/C][C]179.596725398567[/C][C]0.403274601432579[/C][/ROW]
[ROW][C]33[/C][C]149[/C][C]161.635031540698[/C][C]-12.6350315406976[/C][/ROW]
[ROW][C]34[/C][C]84[/C][C]81.5567729287369[/C][C]2.44322707126309[/C][/ROW]
[ROW][C]35[/C][C]85[/C][C]87.0706645024972[/C][C]-2.07066450249724[/C][/ROW]
[ROW][C]36[/C][C]42[/C][C]46.5341311117907[/C][C]-4.53413111179071[/C][/ROW]
[ROW][C]37[/C][C]54[/C][C]54.5405637868091[/C][C]-0.540563786809115[/C][/ROW]
[ROW][C]38[/C][C]30[/C][C]36.0230869082727[/C][C]-6.02308690827274[/C][/ROW]
[ROW][C]39[/C][C]96[/C][C]63.2956705789449[/C][C]32.7043294210551[/C][/ROW]
[ROW][C]40[/C][C]110[/C][C]105.809045908978[/C][C]4.19095409102165[/C][/ROW]
[ROW][C]41[/C][C]141[/C][C]139.864251335792[/C][C]1.13574866420763[/C][/ROW]
[ROW][C]42[/C][C]159[/C][C]156.359907710389[/C][C]2.64009228961114[/C][/ROW]
[ROW][C]43[/C][C]164[/C][C]162.77959334046[/C][C]1.22040665954048[/C][/ROW]
[ROW][C]44[/C][C]155[/C][C]156.446642152766[/C][C]-1.44664215276612[/C][/ROW]
[ROW][C]45[/C][C]135[/C][C]146.17958020367[/C][C]-11.1795802036704[/C][/ROW]
[ROW][C]46[/C][C]93[/C][C]97.3513238980333[/C][C]-4.35132389803334[/C][/ROW]
[ROW][C]47[/C][C]28[/C][C]32.2695533128665[/C][C]-4.26955331286649[/C][/ROW]
[ROW][C]48[/C][C]56[/C][C]52.9561256787163[/C][C]3.04387432128371[/C][/ROW]
[ROW][C]49[/C][C]56[/C][C]57.7565756199429[/C][C]-1.7565756199429[/C][/ROW]
[ROW][C]50[/C][C]22[/C][C]25.1038296524823[/C][C]-3.10382965248232[/C][/ROW]
[ROW][C]51[/C][C]76[/C][C]76.4031848382534[/C][C]-0.403184838253374[/C][/ROW]
[ROW][C]52[/C][C]83[/C][C]80.0392363118758[/C][C]2.9607636881242[/C][/ROW]
[ROW][C]53[/C][C]121[/C][C]120.049973610729[/C][C]0.950026389271479[/C][/ROW]
[ROW][C]54[/C][C]151[/C][C]149.423981611894[/C][C]1.57601838810595[/C][/ROW]
[ROW][C]55[/C][C]208[/C][C]207.402623748128[/C][C]0.597376251871839[/C][/ROW]
[ROW][C]56[/C][C]179[/C][C]180.72781788262[/C][C]-1.72781788261952[/C][/ROW]
[ROW][C]57[/C][C]139[/C][C]169.275518323837[/C][C]-30.2755183238366[/C][/ROW]
[ROW][C]58[/C][C]99[/C][C]95.8142410674943[/C][C]3.18575893250567[/C][/ROW]
[ROW][C]59[/C][C]103[/C][C]103.107032458063[/C][C]-0.107032458063203[/C][/ROW]
[ROW][C]60[/C][C]57[/C][C]54.6973007653024[/C][C]2.30269923469762[/C][/ROW]
[ROW][C]61[/C][C]44[/C][C]43.0952890038889[/C][C]0.90471099611115[/C][/ROW]
[ROW][C]62[/C][C]70[/C][C]72.6734365276299[/C][C]-2.67343652762993[/C][/ROW]
[ROW][C]63[/C][C]58[/C][C]54.5408250681506[/C][C]3.45917493184937[/C][/ROW]
[ROW][C]64[/C][C]91[/C][C]92.3297140870182[/C][C]-1.32971408701821[/C][/ROW]
[ROW][C]65[/C][C]126[/C][C]117.802845269576[/C][C]8.19715473042351[/C][/ROW]
[ROW][C]66[/C][C]146[/C][C]139.892509670998[/C][C]6.10749032900187[/C][/ROW]
[ROW][C]67[/C][C]199[/C][C]196.251401687124[/C][C]2.74859831287592[/C][/ROW]
[ROW][C]68[/C][C]194[/C][C]190.195889986415[/C][C]3.80411001358454[/C][/ROW]
[ROW][C]69[/C][C]145[/C][C]168.831452806043[/C][C]-23.8314528060435[/C][/ROW]
[ROW][C]70[/C][C]131[/C][C]132.38957544516[/C][C]-1.38957544516018[/C][/ROW]
[ROW][C]71[/C][C]74[/C][C]74.4010209328339[/C][C]-0.401020932833858[/C][/ROW]
[ROW][C]72[/C][C]-3[/C][C]-4.05537657808707[/C][C]1.05537657808707[/C][/ROW]
[ROW][C]73[/C][C]7[/C][C]15.272331181412[/C][C]-8.27233118141196[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]10.8375727739848[/C][C]-0.837572773984845[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]37.4478761280434[/C][C]-3.44787612804338[/C][/ROW]
[ROW][C]76[/C][C]94[/C][C]90.260358707842[/C][C]3.73964129215802[/C][/ROW]
[ROW][C]77[/C][C]105[/C][C]105.070322543423[/C][C]-0.0703225434231767[/C][/ROW]
[ROW][C]78[/C][C]151[/C][C]144.132053801127[/C][C]6.86794619887317[/C][/ROW]
[ROW][C]79[/C][C]162[/C][C]159.395868648506[/C][C]2.60413135149447[/C][/ROW]
[ROW][C]80[/C][C]175[/C][C]173.52472673695[/C][C]1.4752732630498[/C][/ROW]
[ROW][C]81[/C][C]128[/C][C]137.278474520539[/C][C]-9.27847452053909[/C][/ROW]
[ROW][C]82[/C][C]115[/C][C]115.274915062119[/C][C]-0.274915062119025[/C][/ROW]
[ROW][C]83[/C][C]62[/C][C]59.5794733210708[/C][C]2.42052667892924[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]13.2572818505341[/C][C]-2.25728185053408[/C][/ROW]
[ROW][C]85[/C][C]-7[/C][C]-3.26937045992917[/C][C]-3.73062954007083[/C][/ROW]
[ROW][C]86[/C][C]64[/C][C]62.6960519880222[/C][C]1.30394801197775[/C][/ROW]
[ROW][C]87[/C][C]80[/C][C]83.8161064384378[/C][C]-3.81610643843778[/C][/ROW]
[ROW][C]88[/C][C]77[/C][C]73.5185843081135[/C][C]3.48141569188648[/C][/ROW]
[ROW][C]89[/C][C]127[/C][C]121.232730292823[/C][C]5.76726970717705[/C][/ROW]
[ROW][C]90[/C][C]158[/C][C]155.005926069558[/C][C]2.99407393044177[/C][/ROW]
[ROW][C]91[/C][C]173[/C][C]171.219713802229[/C][C]1.78028619777139[/C][/ROW]
[ROW][C]92[/C][C]206[/C][C]205.103207346783[/C][C]0.896792653217018[/C][/ROW]
[ROW][C]93[/C][C]147[/C][C]153.713141496193[/C][C]-6.713141496193[/C][/ROW]
[ROW][C]94[/C][C]103[/C][C]99.8752502222006[/C][C]3.12474977779941[/C][/ROW]
[ROW][C]95[/C][C]73[/C][C]77.7006918487714[/C][C]-4.70069184877139[/C][/ROW]
[ROW][C]96[/C][C]52[/C][C]52.0817064829332[/C][C]-0.0817064829331611[/C][/ROW]
[ROW][C]97[/C][C]52[/C][C]52.6098641031161[/C][C]-0.609864103116138[/C][/ROW]
[ROW][C]98[/C][C]68[/C][C]71.8493390640743[/C][C]-3.84933906407432[/C][/ROW]
[ROW][C]99[/C][C]77[/C][C]73.354665417751[/C][C]3.645334582249[/C][/ROW]
[ROW][C]100[/C][C]94[/C][C]96.2101422394088[/C][C]-2.21014223940884[/C][/ROW]
[ROW][C]101[/C][C]147[/C][C]142.871648659078[/C][C]4.12835134092192[/C][/ROW]
[ROW][C]102[/C][C]160[/C][C]160.306942931059[/C][C]-0.306942931058943[/C][/ROW]
[ROW][C]103[/C][C]166[/C][C]167.399862933752[/C][C]-1.39986293375209[/C][/ROW]
[ROW][C]104[/C][C]167[/C][C]160.672875122463[/C][C]6.32712487753669[/C][/ROW]
[ROW][C]105[/C][C]155[/C][C]158.921654189595[/C][C]-3.92165418959488[/C][/ROW]
[ROW][C]106[/C][C]104[/C][C]99.2965860436744[/C][C]4.70341395632564[/C][/ROW]
[ROW][C]107[/C][C]44[/C][C]40.1132118979877[/C][C]3.88678810201231[/C][/ROW]
[ROW][C]108[/C][C]53[/C][C]57.3205890172509[/C][C]-4.32058901725095[/C][/ROW]
[ROW][C]109[/C][C]56[/C][C]55.516423178069[/C][C]0.483576821931038[/C][/ROW]
[ROW][C]110[/C][C]36[/C][C]34.4783888903855[/C][C]1.52161110961455[/C][/ROW]
[ROW][C]111[/C][C]76[/C][C]72.9450361252708[/C][C]3.05496387472923[/C][/ROW]
[ROW][C]112[/C][C]99[/C][C]99.0590729168721[/C][C]-0.059072916872108[/C][/ROW]
[ROW][C]113[/C][C]142[/C][C]137.948582498072[/C][C]4.0514175019278[/C][/ROW]
[ROW][C]114[/C][C]150[/C][C]145.053423163227[/C][C]4.94657683677273[/C][/ROW]
[ROW][C]115[/C][C]190[/C][C]189.208903140475[/C][C]0.791096859525384[/C][/ROW]
[ROW][C]116[/C][C]176[/C][C]169.992776744761[/C][C]6.00722325523852[/C][/ROW]
[ROW][C]117[/C][C]175[/C][C]186.145245479641[/C][C]-11.1452454796411[/C][/ROW]
[ROW][C]118[/C][C]112[/C][C]113.344732330985[/C][C]-1.34473233098468[/C][/ROW]
[ROW][C]119[/C][C]73[/C][C]72.2882558033848[/C][C]0.711744196615154[/C][/ROW]
[ROW][C]120[/C][C]52[/C][C]49.2602126513807[/C][C]2.73978734861933[/C][/ROW]
[ROW][C]121[/C][C]48[/C][C]52.0688567329985[/C][C]-4.0688567329985[/C][/ROW]
[ROW][C]122[/C][C]61[/C][C]58.8341512159269[/C][C]2.16584878407314[/C][/ROW]
[ROW][C]123[/C][C]68[/C][C]66.8751824874724[/C][C]1.12481751252763[/C][/ROW]
[ROW][C]124[/C][C]97[/C][C]99.108976298596[/C][C]-2.10897629859604[/C][/ROW]
[ROW][C]125[/C][C]146[/C][C]142.895096387185[/C][C]3.10490361281487[/C][/ROW]
[ROW][C]126[/C][C]160[/C][C]158.807299878337[/C][C]1.19270012166298[/C][/ROW]
[ROW][C]127[/C][C]155[/C][C]154.22449221562[/C][C]0.775507784379675[/C][/ROW]
[ROW][C]128[/C][C]175[/C][C]177.785401253167[/C][C]-2.78540125316713[/C][/ROW]
[ROW][C]129[/C][C]163[/C][C]164.474219796121[/C][C]-1.47421979612103[/C][/ROW]
[ROW][C]130[/C][C]117[/C][C]117.12862203734[/C][C]-0.128622037339885[/C][/ROW]
[ROW][C]131[/C][C]82[/C][C]82.8884884446537[/C][C]-0.888488444653683[/C][/ROW]
[ROW][C]132[/C][C]55[/C][C]57.9053867996195[/C][C]-2.90538679961953[/C][/ROW]
[ROW][C]133[/C][C]32[/C][C]34.2159962707314[/C][C]-2.21599627073136[/C][/ROW]
[ROW][C]134[/C][C]48[/C][C]47.6904549206749[/C][C]0.309545079325063[/C][/ROW]
[ROW][C]135[/C][C]53[/C][C]55.4799938456971[/C][C]-2.47999384569712[/C][/ROW]
[ROW][C]136[/C][C]82[/C][C]81.704192283725[/C][C]0.295807716275016[/C][/ROW]
[ROW][C]137[/C][C]139[/C][C]136.03223550911[/C][C]2.96776449088979[/C][/ROW]
[ROW][C]138[/C][C]150[/C][C]145.723666137429[/C][C]4.2763338625707[/C][/ROW]
[ROW][C]139[/C][C]184[/C][C]184.189457302117[/C][C]-0.189457302117071[/C][/ROW]
[ROW][C]140[/C][C]185[/C][C]182.193445352896[/C][C]2.80655464710398[/C][/ROW]
[ROW][C]141[/C][C]138[/C][C]150.112428556389[/C][C]-12.1124285563885[/C][/ROW]
[ROW][C]142[/C][C]147[/C][C]153.919946472123[/C][C]-6.91994647212346[/C][/ROW]
[ROW][C]143[/C][C]77[/C][C]74.5901750455766[/C][C]2.40982495442343[/C][/ROW]
[ROW][C]144[/C][C]32[/C][C]28.9786268903718[/C][C]3.02137310962825[/C][/ROW]
[ROW][C]145[/C][C]48[/C][C]51.6627473308272[/C][C]-3.6627473308272[/C][/ROW]
[ROW][C]146[/C][C]72[/C][C]69.7974132583642[/C][C]2.20258674163581[/C][/ROW]
[ROW][C]147[/C][C]76[/C][C]74.7203513051297[/C][C]1.27964869487035[/C][/ROW]
[ROW][C]148[/C][C]94[/C][C]90.3788203280278[/C][C]3.62117967197223[/C][/ROW]
[ROW][C]149[/C][C]133[/C][C]134.210698033378[/C][C]-1.21069803337838[/C][/ROW]
[ROW][C]150[/C][C]164[/C][C]162.045127924308[/C][C]1.95487207569171[/C][/ROW]
[ROW][C]151[/C][C]174[/C][C]172.984493386943[/C][C]1.01550661305686[/C][/ROW]
[ROW][C]152[/C][C]187[/C][C]182.021819754426[/C][C]4.97818024557367[/C][/ROW]
[ROW][C]153[/C][C]149[/C][C]157.766753858969[/C][C]-8.76675385896895[/C][/ROW]
[ROW][C]154[/C][C]102[/C][C]100.570629023487[/C][C]1.4293709765127[/C][/ROW]
[ROW][C]155[/C][C]86[/C][C]83.4133439493296[/C][C]2.58665605067043[/C][/ROW]
[ROW][C]156[/C][C]35[/C][C]38.4782582077349[/C][C]-3.47825820773486[/C][/ROW]
[ROW][C]157[/C][C]31[/C][C]31.6102982291752[/C][C]-0.610298229175225[/C][/ROW]
[ROW][C]158[/C][C]28[/C][C]29.8350504507871[/C][C]-1.83505045078713[/C][/ROW]
[ROW][C]159[/C][C]75[/C][C]72.7934941655533[/C][C]2.20650583444668[/C][/ROW]
[ROW][C]160[/C][C]102[/C][C]94.5828057938383[/C][C]7.41719420616168[/C][/ROW]
[ROW][C]161[/C][C]133[/C][C]127.853158473734[/C][C]5.14684152626581[/C][/ROW]
[ROW][C]162[/C][C]178[/C][C]170.660352059923[/C][C]7.33964794007722[/C][/ROW]
[ROW][C]163[/C][C]190[/C][C]188.571782785385[/C][C]1.42821721461455[/C][/ROW]
[ROW][C]164[/C][C]190[/C][C]189.224721157768[/C][C]0.7752788422319[/C][/ROW]
[ROW][C]165[/C][C]147[/C][C]151.667895336616[/C][C]-4.66789533661588[/C][/ROW]
[ROW][C]166[/C][C]83[/C][C]80.2444149785546[/C][C]2.75558502144535[/C][/ROW]
[ROW][C]167[/C][C]83[/C][C]85.8270202609877[/C][C]-2.82702026098767[/C][/ROW]
[ROW][C]168[/C][C]46[/C][C]47.0346793611689[/C][C]-1.03467936116887[/C][/ROW]
[ROW][C]169[/C][C]40[/C][C]38.0937511318531[/C][C]1.90624886814692[/C][/ROW]
[ROW][C]170[/C][C]50[/C][C]51.0314883359118[/C][C]-1.03148833591178[/C][/ROW]
[ROW][C]171[/C][C]61[/C][C]59.2318593073129[/C][C]1.76814069268711[/C][/ROW]
[ROW][C]172[/C][C]102[/C][C]95.6719958845578[/C][C]6.32800411544223[/C][/ROW]
[ROW][C]173[/C][C]117[/C][C]112.309646453867[/C][C]4.69035354613274[/C][/ROW]
[ROW][C]174[/C][C]158[/C][C]151.743245248573[/C][C]6.256754751427[/C][/ROW]
[ROW][C]175[/C][C]170[/C][C]167.995355789514[/C][C]2.0046442104859[/C][/ROW]
[ROW][C]176[/C][C]190[/C][C]186.574935824101[/C][C]3.42506417589908[/C][/ROW]
[ROW][C]177[/C][C]155[/C][C]161.582176606994[/C][C]-6.58217660699388[/C][/ROW]
[ROW][C]178[/C][C]117[/C][C]122.049892968867[/C][C]-5.04989296886734[/C][/ROW]
[ROW][C]179[/C][C]68[/C][C]66.4781152797656[/C][C]1.52188472023443[/C][/ROW]
[ROW][C]180[/C][C]40[/C][C]40.4656896287564[/C][C]-0.46568962875638[/C][/ROW]
[ROW][C]181[/C][C]56[/C][C]60.340828173781[/C][C]-4.34082817378104[/C][/ROW]
[ROW][C]182[/C][C]28[/C][C]28.4003310021466[/C][C]-0.400331002146627[/C][/ROW]
[ROW][C]183[/C][C]66[/C][C]66.5044011668075[/C][C]-0.504401166807453[/C][/ROW]
[ROW][C]184[/C][C]103[/C][C]100.638887142546[/C][C]2.36111285745371[/C][/ROW]
[ROW][C]185[/C][C]122[/C][C]117.54889391941[/C][C]4.45110608059031[/C][/ROW]
[ROW][C]186[/C][C]166[/C][C]161.733439055528[/C][C]4.26656094447213[/C][/ROW]
[ROW][C]187[/C][C]176[/C][C]173.81834437425[/C][C]2.18165562575001[/C][/ROW]
[ROW][C]188[/C][C]164[/C][C]160.48830975996[/C][C]3.51169024004007[/C][/ROW]
[ROW][C]189[/C][C]160[/C][C]162.339599475296[/C][C]-2.33959947529625[/C][/ROW]
[ROW][C]190[/C][C]139[/C][C]143.010909308382[/C][C]-4.01090930838152[/C][/ROW]
[ROW][C]191[/C][C]75[/C][C]72.7062003329181[/C][C]2.29379966708187[/C][/ROW]
[ROW][C]192[/C][C]44[/C][C]46.0017485730748[/C][C]-2.0017485730748[/C][/ROW]
[ROW][C]193[/C][C]22[/C][C]25.6217934133951[/C][C]-3.62179341339508[/C][/ROW]
[ROW][C]194[/C][C]32[/C][C]38.6733792153249[/C][C]-6.67337921532493[/C][/ROW]
[ROW][C]195[/C][C]42[/C][C]41.3128285328324[/C][C]0.687171467167553[/C][/ROW]
[ROW][C]196[/C][C]86[/C][C]88.8597883420212[/C][C]-2.85978834202118[/C][/ROW]
[ROW][C]197[/C][C]140[/C][C]136.976753492409[/C][C]3.0232465075915[/C][/ROW]
[ROW][C]198[/C][C]163[/C][C]157.716907109778[/C][C]5.28309289022234[/C][/ROW]
[ROW][C]199[/C][C]222[/C][C]218.553500272508[/C][C]3.44649972749198[/C][/ROW]
[ROW][C]200[/C][C]166[/C][C]158.118726874468[/C][C]7.88127312553153[/C][/ROW]
[ROW][C]201[/C][C]183[/C][C]205.260204543609[/C][C]-22.2602045436091[/C][/ROW]
[ROW][C]202[/C][C]140[/C][C]135.06758841636[/C][C]4.93241158364008[/C][/ROW]
[ROW][C]203[/C][C]98[/C][C]98.2676841674039[/C][C]-0.26768416740387[/C][/ROW]
[ROW][C]204[/C][C]69[/C][C]71.852498517595[/C][C]-2.85249851759502[/C][/ROW]
[ROW][C]205[/C][C]75[/C][C]75.6592930342189[/C][C]-0.659293034218945[/C][/ROW]
[ROW][C]206[/C][C]63[/C][C]64.0678158739368[/C][C]-1.06781587393674[/C][/ROW]
[ROW][C]207[/C][C]81[/C][C]78.1966648561922[/C][C]2.80333514380785[/C][/ROW]
[ROW][C]208[/C][C]126[/C][C]121.527126759975[/C][C]4.47287324002519[/C][/ROW]
[ROW][C]209[/C][C]139[/C][C]133.592172837539[/C][C]5.40782716246129[/C][/ROW]
[ROW][C]210[/C][C]171[/C][C]174.542106636273[/C][C]-3.54210663627349[/C][/ROW]
[ROW][C]211[/C][C]170[/C][C]167.42202455183[/C][C]2.57797544817002[/C][/ROW]
[ROW][C]212[/C][C]173[/C][C]171.750616301613[/C][C]1.24938369838673[/C][/ROW]
[ROW][C]213[/C][C]144[/C][C]149.761767589062[/C][C]-5.76176758906236[/C][/ROW]
[ROW][C]214[/C][C]105[/C][C]106.048995457074[/C][C]-1.04899545707423[/C][/ROW]
[ROW][C]215[/C][C]75[/C][C]75.2912552453254[/C][C]-0.291255245325384[/C][/ROW]
[ROW][C]216[/C][C]41[/C][C]44.0757184856373[/C][C]-3.07571848563734[/C][/ROW]
[ROW][C]217[/C][C]68[/C][C]70.656153634553[/C][C]-2.65615363455296[/C][/ROW]
[ROW][C]218[/C][C]53[/C][C]50.612556111469[/C][C]2.387443888531[/C][/ROW]
[ROW][C]219[/C][C]61[/C][C]56.0870176678599[/C][C]4.91298233214012[/C][/ROW]
[ROW][C]220[/C][C]87[/C][C]86.0899993055062[/C][C]0.910000694493756[/C][/ROW]
[ROW][C]221[/C][C]155[/C][C]145.257417742575[/C][C]9.74258225742465[/C][/ROW]
[ROW][C]222[/C][C]159[/C][C]159.702157930726[/C][C]-0.702157930726228[/C][/ROW]
[ROW][C]223[/C][C]180[/C][C]177.706421692672[/C][C]2.2935783073284[/C][/ROW]
[ROW][C]224[/C][C]175[/C][C]174.548786634173[/C][C]0.451213365827084[/C][/ROW]
[ROW][C]225[/C][C]138[/C][C]150.419534937934[/C][C]-12.4195349379342[/C][/ROW]
[ROW][C]226[/C][C]105[/C][C]100.896252759534[/C][C]4.10374724046616[/C][/ROW]
[ROW][C]227[/C][C]73[/C][C]72.8681418407187[/C][C]0.131858159281319[/C][/ROW]
[ROW][C]228[/C][C]26[/C][C]27.1615813006275[/C][C]-1.16158130062753[/C][/ROW]
[ROW][C]229[/C][C]12[/C][C]15.9447483568063[/C][C]-3.94474835680626[/C][/ROW]
[ROW][C]230[/C][C]35[/C][C]34.3278840772195[/C][C]0.672115922780495[/C][/ROW]
[ROW][C]231[/C][C]64[/C][C]63.0017196346634[/C][C]0.998280365336565[/C][/ROW]
[ROW][C]232[/C][C]115[/C][C]110.462369848348[/C][C]4.5376301516523[/C][/ROW]
[ROW][C]233[/C][C]138[/C][C]133.056717974347[/C][C]4.94328202565326[/C][/ROW]
[ROW][C]234[/C][C]138[/C][C]155.005191830886[/C][C]-17.0051918308859[/C][/ROW]
[ROW][C]235[/C][C]182[/C][C]183.821057986451[/C][C]-1.8210579864509[/C][/ROW]
[ROW][C]236[/C][C]191[/C][C]188.393492916727[/C][C]2.60650708327345[/C][/ROW]
[ROW][C]237[/C][C]155[/C][C]167.468888867563[/C][C]-12.4688888675634[/C][/ROW]
[ROW][C]238[/C][C]113[/C][C]108.987256847189[/C][C]4.01274315281077[/C][/ROW]
[ROW][C]239[/C][C]98[/C][C]98.1967818866376[/C][C]-0.196781886637568[/C][/ROW]
[ROW][C]240[/C][C]29[/C][C]27.2706779984851[/C][C]1.72932200151494[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147113&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147113&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 IndexActualsInterpolationForecastResidualsPrediction Error
16168.576957383176-7.57695738317595
28182.078351341147-1.07835134114697
38787.598501456965-0.598501456964982
48782.43974486475664.5602551352434
5136126.1432360898429.85676391015773
6147148.660252671037-1.66025267103686
7168167.2129843151910.787015684809387
8185180.4972599270574.50274007294344
9137135.7180527127431.28194728725662
10125128.030879370393-3.03087937039321
116461.11673018721052.88326981278954
124549.3559179865759-4.35591798657587
133539.9850326540657-4.9850326540657
14-4-7.103043413717233.10304341371723
158889.2996985635585-1.2996985635585
168584.16908834675290.830911653247088
179595.0180991289145-0.0180991289145289
18128124.8166283502763.18337164972398
19186187.010111069312-1.01011106931177
20182176.549611003115.4503889968904
21151143.0441526213477.95584737865276
22106110.273990278683-4.27399027868253
236058.32535165289571.67464834710428
244449.5389615914737-5.53896159147368
253033.9435642495646-3.9435642495646
265456.2919393491268-2.29193934912684
277274.3309551332902-2.33095513329018
288888.3032645530048-0.303264553004813
29153147.9648843887255.03511561127508
30168163.437324238294.56267576170997
31181179.0565315839291.94346841607055
32180179.5967253985670.403274601432579
33149161.635031540698-12.6350315406976
348481.55677292873692.44322707126309
358587.0706645024972-2.07066450249724
364246.5341311117907-4.53413111179071
375454.5405637868091-0.540563786809115
383036.0230869082727-6.02308690827274
399663.295670578944932.7043294210551
40110105.8090459089784.19095409102165
41141139.8642513357921.13574866420763
42159156.3599077103892.64009228961114
43164162.779593340461.22040665954048
44155156.446642152766-1.44664215276612
45135146.17958020367-11.1795802036704
469397.3513238980333-4.35132389803334
472832.2695533128665-4.26955331286649
485652.95612567871633.04387432128371
495657.7565756199429-1.7565756199429
502225.1038296524823-3.10382965248232
517676.4031848382534-0.403184838253374
528380.03923631187582.9607636881242
53121120.0499736107290.950026389271479
54151149.4239816118941.57601838810595
55208207.4026237481280.597376251871839
56179180.72781788262-1.72781788261952
57139169.275518323837-30.2755183238366
589995.81424106749433.18575893250567
59103103.107032458063-0.107032458063203
605754.69730076530242.30269923469762
614443.09528900388890.90471099611115
627072.6734365276299-2.67343652762993
635854.54082506815063.45917493184937
649192.3297140870182-1.32971408701821
65126117.8028452695768.19715473042351
66146139.8925096709986.10749032900187
67199196.2514016871242.74859831287592
68194190.1958899864153.80411001358454
69145168.831452806043-23.8314528060435
70131132.38957544516-1.38957544516018
717474.4010209328339-0.401020932833858
72-3-4.055376578087071.05537657808707
73715.272331181412-8.27233118141196
741010.8375727739848-0.837572773984845
753437.4478761280434-3.44787612804338
769490.2603587078423.73964129215802
77105105.070322543423-0.0703225434231767
78151144.1320538011276.86794619887317
79162159.3958686485062.60413135149447
80175173.524726736951.4752732630498
81128137.278474520539-9.27847452053909
82115115.274915062119-0.274915062119025
836259.57947332107082.42052667892924
841113.2572818505341-2.25728185053408
85-7-3.26937045992917-3.73062954007083
866462.69605198802221.30394801197775
878083.8161064384378-3.81610643843778
887773.51858430811353.48141569188648
89127121.2327302928235.76726970717705
90158155.0059260695582.99407393044177
91173171.2197138022291.78028619777139
92206205.1032073467830.896792653217018
93147153.713141496193-6.713141496193
9410399.87525022220063.12474977779941
957377.7006918487714-4.70069184877139
965252.0817064829332-0.0817064829331611
975252.6098641031161-0.609864103116138
986871.8493390640743-3.84933906407432
997773.3546654177513.645334582249
1009496.2101422394088-2.21014223940884
101147142.8716486590784.12835134092192
102160160.306942931059-0.306942931058943
103166167.399862933752-1.39986293375209
104167160.6728751224636.32712487753669
105155158.921654189595-3.92165418959488
10610499.29658604367444.70341395632564
1074440.11321189798773.88678810201231
1085357.3205890172509-4.32058901725095
1095655.5164231780690.483576821931038
1103634.47838889038551.52161110961455
1117672.94503612527083.05496387472923
1129999.0590729168721-0.059072916872108
113142137.9485824980724.0514175019278
114150145.0534231632274.94657683677273
115190189.2089031404750.791096859525384
116176169.9927767447616.00722325523852
117175186.145245479641-11.1452454796411
118112113.344732330985-1.34473233098468
1197372.28825580338480.711744196615154
1205249.26021265138072.73978734861933
1214852.0688567329985-4.0688567329985
1226158.83415121592692.16584878407314
1236866.87518248747241.12481751252763
1249799.108976298596-2.10897629859604
125146142.8950963871853.10490361281487
126160158.8072998783371.19270012166298
127155154.224492215620.775507784379675
128175177.785401253167-2.78540125316713
129163164.474219796121-1.47421979612103
130117117.12862203734-0.128622037339885
1318282.8884884446537-0.888488444653683
1325557.9053867996195-2.90538679961953
1333234.2159962707314-2.21599627073136
1344847.69045492067490.309545079325063
1355355.4799938456971-2.47999384569712
1368281.7041922837250.295807716275016
137139136.032235509112.96776449088979
138150145.7236661374294.2763338625707
139184184.189457302117-0.189457302117071
140185182.1934453528962.80655464710398
141138150.112428556389-12.1124285563885
142147153.919946472123-6.91994647212346
1437774.59017504557662.40982495442343
1443228.97862689037183.02137310962825
1454851.6627473308272-3.6627473308272
1467269.79741325836422.20258674163581
1477674.72035130512971.27964869487035
1489490.37882032802783.62117967197223
149133134.210698033378-1.21069803337838
150164162.0451279243081.95487207569171
151174172.9844933869431.01550661305686
152187182.0218197544264.97818024557367
153149157.766753858969-8.76675385896895
154102100.5706290234871.4293709765127
1558683.41334394932962.58665605067043
1563538.4782582077349-3.47825820773486
1573131.6102982291752-0.610298229175225
1582829.8350504507871-1.83505045078713
1597572.79349416555332.20650583444668
16010294.58280579383837.41719420616168
161133127.8531584737345.14684152626581
162178170.6603520599237.33964794007722
163190188.5717827853851.42821721461455
164190189.2247211577680.7752788422319
165147151.667895336616-4.66789533661588
1668380.24441497855462.75558502144535
1678385.8270202609877-2.82702026098767
1684647.0346793611689-1.03467936116887
1694038.09375113185311.90624886814692
1705051.0314883359118-1.03148833591178
1716159.23185930731291.76814069268711
17210295.67199588455786.32800411544223
173117112.3096464538674.69035354613274
174158151.7432452485736.256754751427
175170167.9953557895142.0046442104859
176190186.5749358241013.42506417589908
177155161.582176606994-6.58217660699388
178117122.049892968867-5.04989296886734
1796866.47811527976561.52188472023443
1804040.4656896287564-0.46568962875638
1815660.340828173781-4.34082817378104
1822828.4003310021466-0.400331002146627
1836666.5044011668075-0.504401166807453
184103100.6388871425462.36111285745371
185122117.548893919414.45110608059031
186166161.7334390555284.26656094447213
187176173.818344374252.18165562575001
188164160.488309759963.51169024004007
189160162.339599475296-2.33959947529625
190139143.010909308382-4.01090930838152
1917572.70620033291812.29379966708187
1924446.0017485730748-2.0017485730748
1932225.6217934133951-3.62179341339508
1943238.6733792153249-6.67337921532493
1954241.31282853283240.687171467167553
1968688.8597883420212-2.85978834202118
197140136.9767534924093.0232465075915
198163157.7169071097785.28309289022234
199222218.5535002725083.44649972749198
200166158.1187268744687.88127312553153
201183205.260204543609-22.2602045436091
202140135.067588416364.93241158364008
2039898.2676841674039-0.26768416740387
2046971.852498517595-2.85249851759502
2057575.6592930342189-0.659293034218945
2066364.0678158739368-1.06781587393674
2078178.19666485619222.80333514380785
208126121.5271267599754.47287324002519
209139133.5921728375395.40782716246129
210171174.542106636273-3.54210663627349
211170167.422024551832.57797544817002
212173171.7506163016131.24938369838673
213144149.761767589062-5.76176758906236
214105106.048995457074-1.04899545707423
2157575.2912552453254-0.291255245325384
2164144.0757184856373-3.07571848563734
2176870.656153634553-2.65615363455296
2185350.6125561114692.387443888531
2196156.08701766785994.91298233214012
2208786.08999930550620.910000694493756
221155145.2574177425759.74258225742465
222159159.702157930726-0.702157930726228
223180177.7064216926722.2935783073284
224175174.5487866341730.451213365827084
225138150.419534937934-12.4195349379342
226105100.8962527595344.10374724046616
2277372.86814184071870.131858159281319
2282627.1615813006275-1.16158130062753
2291215.9447483568063-3.94474835680626
2303534.32788407721950.672115922780495
2316463.00171963466340.998280365336565
232115110.4623698483484.5376301516523
233138133.0567179743474.94328202565326
234138155.005191830886-17.0051918308859
235182183.821057986451-1.8210579864509
236191188.3934929167272.60650708327345
237155167.468888867563-12.4688888675634
238113108.9872568471894.01274315281077
2399898.1967818866376-0.196781886637568
2402927.27067799848511.72932200151494







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.002536111038321270.005072222076642550.997463888961679
100.0002947808749228650.000589561749845730.999705219125077
114.61634447457135e-059.23268894914269e-050.999953836555254
128.26358221532064e-061.65271644306413e-050.999991736417785
135.12657708080341e-050.0001025315416160680.999948734229192
141.76682927169551e-053.53365854339101e-050.999982331707283
153.10140521981403e-066.20281043962806e-060.99999689859478
162.06623695981552e-064.13247391963105e-060.99999793376304
173.76422620230122e-077.52845240460244e-070.99999962357738
186.61690348668505e-081.32338069733701e-070.999999933830965
192.13324579522426e-084.26649159044851e-080.999999978667542
203.06021960146136e-076.12043920292272e-070.99999969397804
219.86638790828989e-081.97327758165798e-070.999999901336121
226.09774347846367e-081.21954869569273e-070.999999939022565
232.15053340046003e-084.30106680092005e-080.999999978494666
245.28682275828303e-091.05736455165661e-080.999999994713177
251.24429460507007e-092.48858921014015e-090.999999998755705
264.00244242272758e-108.00488484545516e-100.999999999599756
279.11726040475746e-111.82345208095149e-100.999999999908827
281.97876873925882e-113.95753747851764e-110.999999999980212
294.38965743729097e-128.77931487458193e-120.99999999999561
301.99005980223055e-123.98011960446111e-120.99999999999801
314.26928763366473e-138.53857526732945e-130.999999999999573
321.72224611124712e-133.44449222249425e-130.999999999999828
330.002748359356972990.005496718713945980.997251640643027
340.001747654107699920.003495308215399840.9982523458923
350.001140003604266720.002280007208533450.998859996395733
360.0006886578567459140.001377315713491830.999311342143254
370.0004463965131631330.0008927930263262670.999553603486837
380.0002752374572698870.0005504749145397730.99972476254273
390.8995444444601170.2009111110797660.100455555539883
400.8846737060979560.2306525878040890.115326293902044
410.8621667872812870.2756664254374250.137833212718713
420.8347424859841450.330515028031710.165257514015855
430.8028584488204290.3942831023591410.197141551179571
440.7677579728374730.4644840543250550.232242027162527
450.9415817918710010.1168364162579980.0584182081289989
460.9298162587374150.140367482525170.0701837412625848
470.9182173944196850.1635652111606290.0817826055803147
480.9144376592714380.1711246814571240.0855623407285621
490.8959899285927920.2080201428144160.104010071407208
500.8833536365490070.2332927269019870.116646363450993
510.8594113165502790.2811773668994420.140588683449721
520.8356938981873540.3286122036252920.164306101812646
530.8071838091682280.3856323816635440.192816190831772
540.7764795128320880.4470409743358240.223520487167912
550.7421247544978830.5157504910042330.257875245502117
560.7054352855929420.5891294288141150.294564714407058
570.9998852162044280.0002295675911430040.000114783795571502
580.9999020262945980.0001959474108039079.79737054019535e-05
590.9998526835587630.0002946328824734230.000147316441236712
600.999841962484060.0003160750318808080.000158037515940404
610.999790350437680.0004192991246393710.000209649562319686
620.9997133585860360.0005732828279269210.000286641413963461
630.999637314475130.000725371049740310.000362685524870155
640.9995117085506180.0009765828987635750.000488291449381787
650.9996116082162050.0007767835675906760.000388391783795338
660.9995966214082480.0008067571835040620.000403378591752031
670.9994583677750220.001083264449955560.00054163222497778
680.9993182971752380.001363405649523510.000681702824761754
690.9999994023080961.19538380823799e-065.97691904118993e-07
700.9999990734001111.85319977880458e-069.2659988940229e-07
710.999998497374633.00525074058373e-061.50262537029187e-06
720.999997612447214.77510557910933e-062.38755278955466e-06
730.9999990201693061.95966138791697e-069.79830693958483e-07
740.9999984423507623.11529847612091e-061.55764923806045e-06
750.9999979539839614.09203207763146e-062.04601603881573e-06
760.9999972481649665.50367006702455e-062.75183503351228e-06
770.9999956507983158.69840337033962e-064.34920168516981e-06
780.999996957899046.08420192023415e-063.04210096011708e-06
790.9999958056302078.38873958598725e-064.19436979299362e-06
800.9999943163652711.13672694585578e-055.68363472927888e-06
810.9999975095214414.98095711766516e-062.49047855883258e-06
820.9999961753308247.64933835279075e-063.82466917639538e-06
830.9999955821799048.83564019116946e-064.41782009558473e-06
840.9999935986582561.28026834877772e-056.40134174388861e-06
850.9999917568120411.64863759181441e-058.24318795907205e-06
860.999988498964892.30020702201271e-051.15010351100635e-05
870.9999850182016892.99635966219106e-051.49817983109553e-05
880.9999810289612963.79420774077633e-051.89710387038817e-05
890.9999831556790333.36886419342385e-051.68443209671193e-05
900.9999783480481634.33039036735304e-052.16519518367652e-05
910.9999692309586576.15380826869914e-053.07690413434957e-05
920.9999555238399298.89523201418757e-054.44761600709378e-05
930.9999633020311117.33959377782362e-053.66979688891181e-05
940.9999559276487798.81447024418704e-054.40723512209352e-05
950.999952994490319.40110193805852e-054.70055096902926e-05
960.9999312381836040.0001375236327929396.87618163964696e-05
970.999901020064590.0001979598708196719.89799354098355e-05
980.9998775995488090.0002448009023824310.000122400451191215
990.9998662730029250.0002674539941509620.000133726997075481
1000.9998234015459730.0003531969080548170.000176598454027408
1010.9997917955955760.0004164088088479770.000208204404423988
1020.9997118669215960.0005762661568084730.000288133078404236
1030.9996023601949140.0007952796101710670.000397639805085534
1040.9996542628027170.0006914743945666980.000345737197283349
1050.9996221096553370.0007557806893260530.000377890344663027
1060.9996081472609310.0007837054781380130.000391852739069006
1070.9995574463579230.0008851072841534570.000442553642076729
1080.9994995461823410.001000907635317450.000500453817658727
1090.9993085154315780.00138296913684380.000691484568421902
1100.9990679274946410.001864145010718770.000932072505359387
1110.9988336889701930.002332622059614580.00116631102980729
1120.9984127501187580.003174499762483330.00158724988124166
1130.9981518712956780.003696257408643980.00184812870432199
1140.9980047852079460.003990429584108640.00199521479205432
1150.9973805873840860.005238825231827750.00261941261591387
1160.9974769909844190.00504601803116110.00252300901558055
1170.9990773849399770.001845230120046110.000922615060023055
1180.998780019254470.00243996149106080.0012199807455304
1190.9983416561382430.003316687723513010.00165834386175651
1200.9979143359598960.004171328080208020.00208566404010401
1210.9976512695689890.004697460862021240.00234873043101062
1220.9969627476489840.006074504702032240.00303725235101612
1230.9959886506416080.008022698716784960.00401134935839248
1240.9949531744177490.01009365116450290.00504682558225147
1250.9938115499076270.01237690018474660.00618845009237331
1260.9920541745032830.01589165099343320.00794582549671662
1270.989764031420920.0204719371581610.0102359685790805
1280.9877486457581240.02450270848375250.0122513542418762
1290.9846405595390030.03071888092199310.0153594404609965
1300.9806982719086820.03860345618263570.0193017280913178
1310.9763873904015250.04722521919694910.0236126095984746
1320.9727572277637990.05448554447240290.0272427722362014
1330.967914163799160.06417167240168090.0320858362008405
1340.9606428348857380.07871433022852350.0393571651142618
1350.9543493122624710.09130137547505870.0456506877375293
1360.9446832412644450.110633517471110.0553167587355552
1370.936272215335240.1274555693295210.0637277846647604
1380.931042559629030.1379148807419410.0689574403709703
1390.9175383215459950.1649233569080090.0824616784540046
1400.9047446701580080.1905106596839830.0952553298419917
1410.9852222178035910.02955556439281810.014777782196409
1420.9860065460587640.02798690788247270.0139934539412364
1430.9824693263603860.03506134727922790.0175306736396139
1440.9783475827649620.04330483447007630.0216524172350382
1450.9766479077420210.04670418451595810.0233520922579791
1460.9722531210379970.05549375792400680.0277468789620034
1470.9654559971282120.06908800574357710.0345440028717885
1480.9591625298879950.08167494022401090.0408374701120054
1490.9502101904027770.09957961919444610.0497898095972231
1500.9398118326699470.1203763346601070.0601881673300535
1510.9280094707658640.1439810584682730.0719905292341364
1520.9195675171988450.1608649656023110.0804324828011553
1530.9471649161231420.1056701677537170.0528350838768583
1540.9358344441228610.1283311117542780.064165555877139
1550.9238193354234970.1523613291530070.0761806645765033
1560.9213195656148070.1573608687703850.0786804343851927
1570.9076521178085640.1846957643828720.0923478821914359
1580.8943619575719080.2112760848561850.105638042428092
1590.8756943933876360.2486112132247280.124305606612364
1600.8821484347551280.2357031304897430.117851565244872
1610.87191653012070.2561669397585990.1280834698793
1620.8916318863146550.216736227370690.108368113685345
1630.8760072791353680.2479854417292640.123992720864632
1640.8614122292754470.2771755414491060.138587770724553
1650.8886481747468450.222703650506310.111351825253155
1660.8691137151974580.2617725696050850.130886284802542
1670.8504324235064480.2991351529871040.149567576493552
1680.8311530589419950.337693882116010.168846941058005
1690.8077477365232970.3845045269534070.192252263476703
1700.7824459260667970.4351081478664060.217554073933203
1710.7503288906321290.4993422187357420.249671109367871
1720.7378442826378690.5243114347242630.262155717362131
1730.7285598076700580.5428803846598840.271440192329942
1740.7368263238999240.5263473522001520.263173676100076
1750.7064512811816730.5870974376366540.293548718818327
1760.6737495625186690.6525008749626620.326250437481331
1770.6990616377819180.6018767244361630.300938362218082
1780.6801164227111140.6397671545777710.319883577288886
1790.6400288644692560.7199422710614880.359971135530744
1800.598559179021410.8028816419571810.40144082097859
1810.5803327851696750.839334429660650.419667214830325
1820.5419075630316610.9161848739366790.458092436968339
1830.4976834061599410.9953668123198830.502316593840059
1840.4560579290068330.9121158580136670.543942070993167
1850.4407711025077040.8815422050154080.559228897492296
1860.4210512139793050.842102427958610.578948786020695
1870.380187349643630.760374699287260.61981265035637
1880.3607835036944660.7215670073889320.639216496305534
1890.3292077583257490.6584155166514980.670792241674251
1900.2981429184280710.5962858368561420.701857081571929
1910.2601882347309260.5203764694618520.739811765269074
1920.2261873245948890.4523746491897780.773812675405111
1930.1991836633146810.3983673266293630.800816336685319
1940.212187829819070.424375659638140.78781217018093
1950.1791412204580460.3582824409160910.820858779541954
1960.1529640276836910.3059280553673820.847035972316309
1970.1294336962034530.2588673924069050.870566303796547
1980.1462027425567660.2924054851135310.853797257443234
1990.1935684455522960.3871368911045920.806431554447704
2000.1751837011391430.3503674022782850.824816298860857
2010.6936561273642410.6126877452715180.306343872635759
2020.6647398925975030.6705202148049940.335260107402497
2030.6139063414164780.7721873171670440.386093658583522
2040.5801614223085150.839677155382970.419838577691485
2050.5317641801132540.9364716397734930.468235819886746
2060.4877109618091120.9754219236182240.512289038190888
2070.4320438997680860.8640877995361710.567956100231914
2080.4289178498099740.8578356996199490.571082150190026
2090.3949240273549850.789848054709970.605075972645015
2100.3554644453691390.7109288907382780.644535554630861
2110.3027896927912380.6055793855824750.697210307208762
2120.2662952866408050.5325905732816090.733704713359195
2130.3104027160462660.6208054320925320.689597283953734
2140.2585530991015080.5171061982030160.741446900898492
2150.2088240778756740.4176481557513490.791175922124326
2160.1916238709426810.3832477418853610.808376129057319
2170.1630013837841770.3260027675683540.836998616215823
2180.124314318827560.248628637655120.87568568117244
2190.09443541378773010.188870827575460.90556458621227
2200.06801917425415330.1360383485083070.931980825745847
2210.1267165987239810.2534331974479630.873283401276019
2220.09972018772338130.1994403754467630.900279812276619
2230.07762470187913520.155249403758270.922375298120865
2240.05185963186403860.1037192637280770.948140368135961
2250.1792448851516760.3584897703033520.820755114848324
2260.1342667404489750.2685334808979490.865733259551025
2270.1028286863597180.2056573727194370.897171313640282
2280.06448746992836330.1289749398567270.935512530071637
2290.03815259230744490.07630518461488980.961847407692555
2300.02015132295373050.04030264590746110.979848677046269
2310.01053409147065520.02106818294131050.989465908529345

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.00253611103832127 & 0.00507222207664255 & 0.997463888961679 \tabularnewline
10 & 0.000294780874922865 & 0.00058956174984573 & 0.999705219125077 \tabularnewline
11 & 4.61634447457135e-05 & 9.23268894914269e-05 & 0.999953836555254 \tabularnewline
12 & 8.26358221532064e-06 & 1.65271644306413e-05 & 0.999991736417785 \tabularnewline
13 & 5.12657708080341e-05 & 0.000102531541616068 & 0.999948734229192 \tabularnewline
14 & 1.76682927169551e-05 & 3.53365854339101e-05 & 0.999982331707283 \tabularnewline
15 & 3.10140521981403e-06 & 6.20281043962806e-06 & 0.99999689859478 \tabularnewline
16 & 2.06623695981552e-06 & 4.13247391963105e-06 & 0.99999793376304 \tabularnewline
17 & 3.76422620230122e-07 & 7.52845240460244e-07 & 0.99999962357738 \tabularnewline
18 & 6.61690348668505e-08 & 1.32338069733701e-07 & 0.999999933830965 \tabularnewline
19 & 2.13324579522426e-08 & 4.26649159044851e-08 & 0.999999978667542 \tabularnewline
20 & 3.06021960146136e-07 & 6.12043920292272e-07 & 0.99999969397804 \tabularnewline
21 & 9.86638790828989e-08 & 1.97327758165798e-07 & 0.999999901336121 \tabularnewline
22 & 6.09774347846367e-08 & 1.21954869569273e-07 & 0.999999939022565 \tabularnewline
23 & 2.15053340046003e-08 & 4.30106680092005e-08 & 0.999999978494666 \tabularnewline
24 & 5.28682275828303e-09 & 1.05736455165661e-08 & 0.999999994713177 \tabularnewline
25 & 1.24429460507007e-09 & 2.48858921014015e-09 & 0.999999998755705 \tabularnewline
26 & 4.00244242272758e-10 & 8.00488484545516e-10 & 0.999999999599756 \tabularnewline
27 & 9.11726040475746e-11 & 1.82345208095149e-10 & 0.999999999908827 \tabularnewline
28 & 1.97876873925882e-11 & 3.95753747851764e-11 & 0.999999999980212 \tabularnewline
29 & 4.38965743729097e-12 & 8.77931487458193e-12 & 0.99999999999561 \tabularnewline
30 & 1.99005980223055e-12 & 3.98011960446111e-12 & 0.99999999999801 \tabularnewline
31 & 4.26928763366473e-13 & 8.53857526732945e-13 & 0.999999999999573 \tabularnewline
32 & 1.72224611124712e-13 & 3.44449222249425e-13 & 0.999999999999828 \tabularnewline
33 & 0.00274835935697299 & 0.00549671871394598 & 0.997251640643027 \tabularnewline
34 & 0.00174765410769992 & 0.00349530821539984 & 0.9982523458923 \tabularnewline
35 & 0.00114000360426672 & 0.00228000720853345 & 0.998859996395733 \tabularnewline
36 & 0.000688657856745914 & 0.00137731571349183 & 0.999311342143254 \tabularnewline
37 & 0.000446396513163133 & 0.000892793026326267 & 0.999553603486837 \tabularnewline
38 & 0.000275237457269887 & 0.000550474914539773 & 0.99972476254273 \tabularnewline
39 & 0.899544444460117 & 0.200911111079766 & 0.100455555539883 \tabularnewline
40 & 0.884673706097956 & 0.230652587804089 & 0.115326293902044 \tabularnewline
41 & 0.862166787281287 & 0.275666425437425 & 0.137833212718713 \tabularnewline
42 & 0.834742485984145 & 0.33051502803171 & 0.165257514015855 \tabularnewline
43 & 0.802858448820429 & 0.394283102359141 & 0.197141551179571 \tabularnewline
44 & 0.767757972837473 & 0.464484054325055 & 0.232242027162527 \tabularnewline
45 & 0.941581791871001 & 0.116836416257998 & 0.0584182081289989 \tabularnewline
46 & 0.929816258737415 & 0.14036748252517 & 0.0701837412625848 \tabularnewline
47 & 0.918217394419685 & 0.163565211160629 & 0.0817826055803147 \tabularnewline
48 & 0.914437659271438 & 0.171124681457124 & 0.0855623407285621 \tabularnewline
49 & 0.895989928592792 & 0.208020142814416 & 0.104010071407208 \tabularnewline
50 & 0.883353636549007 & 0.233292726901987 & 0.116646363450993 \tabularnewline
51 & 0.859411316550279 & 0.281177366899442 & 0.140588683449721 \tabularnewline
52 & 0.835693898187354 & 0.328612203625292 & 0.164306101812646 \tabularnewline
53 & 0.807183809168228 & 0.385632381663544 & 0.192816190831772 \tabularnewline
54 & 0.776479512832088 & 0.447040974335824 & 0.223520487167912 \tabularnewline
55 & 0.742124754497883 & 0.515750491004233 & 0.257875245502117 \tabularnewline
56 & 0.705435285592942 & 0.589129428814115 & 0.294564714407058 \tabularnewline
57 & 0.999885216204428 & 0.000229567591143004 & 0.000114783795571502 \tabularnewline
58 & 0.999902026294598 & 0.000195947410803907 & 9.79737054019535e-05 \tabularnewline
59 & 0.999852683558763 & 0.000294632882473423 & 0.000147316441236712 \tabularnewline
60 & 0.99984196248406 & 0.000316075031880808 & 0.000158037515940404 \tabularnewline
61 & 0.99979035043768 & 0.000419299124639371 & 0.000209649562319686 \tabularnewline
62 & 0.999713358586036 & 0.000573282827926921 & 0.000286641413963461 \tabularnewline
63 & 0.99963731447513 & 0.00072537104974031 & 0.000362685524870155 \tabularnewline
64 & 0.999511708550618 & 0.000976582898763575 & 0.000488291449381787 \tabularnewline
65 & 0.999611608216205 & 0.000776783567590676 & 0.000388391783795338 \tabularnewline
66 & 0.999596621408248 & 0.000806757183504062 & 0.000403378591752031 \tabularnewline
67 & 0.999458367775022 & 0.00108326444995556 & 0.00054163222497778 \tabularnewline
68 & 0.999318297175238 & 0.00136340564952351 & 0.000681702824761754 \tabularnewline
69 & 0.999999402308096 & 1.19538380823799e-06 & 5.97691904118993e-07 \tabularnewline
70 & 0.999999073400111 & 1.85319977880458e-06 & 9.2659988940229e-07 \tabularnewline
71 & 0.99999849737463 & 3.00525074058373e-06 & 1.50262537029187e-06 \tabularnewline
72 & 0.99999761244721 & 4.77510557910933e-06 & 2.38755278955466e-06 \tabularnewline
73 & 0.999999020169306 & 1.95966138791697e-06 & 9.79830693958483e-07 \tabularnewline
74 & 0.999998442350762 & 3.11529847612091e-06 & 1.55764923806045e-06 \tabularnewline
75 & 0.999997953983961 & 4.09203207763146e-06 & 2.04601603881573e-06 \tabularnewline
76 & 0.999997248164966 & 5.50367006702455e-06 & 2.75183503351228e-06 \tabularnewline
77 & 0.999995650798315 & 8.69840337033962e-06 & 4.34920168516981e-06 \tabularnewline
78 & 0.99999695789904 & 6.08420192023415e-06 & 3.04210096011708e-06 \tabularnewline
79 & 0.999995805630207 & 8.38873958598725e-06 & 4.19436979299362e-06 \tabularnewline
80 & 0.999994316365271 & 1.13672694585578e-05 & 5.68363472927888e-06 \tabularnewline
81 & 0.999997509521441 & 4.98095711766516e-06 & 2.49047855883258e-06 \tabularnewline
82 & 0.999996175330824 & 7.64933835279075e-06 & 3.82466917639538e-06 \tabularnewline
83 & 0.999995582179904 & 8.83564019116946e-06 & 4.41782009558473e-06 \tabularnewline
84 & 0.999993598658256 & 1.28026834877772e-05 & 6.40134174388861e-06 \tabularnewline
85 & 0.999991756812041 & 1.64863759181441e-05 & 8.24318795907205e-06 \tabularnewline
86 & 0.99998849896489 & 2.30020702201271e-05 & 1.15010351100635e-05 \tabularnewline
87 & 0.999985018201689 & 2.99635966219106e-05 & 1.49817983109553e-05 \tabularnewline
88 & 0.999981028961296 & 3.79420774077633e-05 & 1.89710387038817e-05 \tabularnewline
89 & 0.999983155679033 & 3.36886419342385e-05 & 1.68443209671193e-05 \tabularnewline
90 & 0.999978348048163 & 4.33039036735304e-05 & 2.16519518367652e-05 \tabularnewline
91 & 0.999969230958657 & 6.15380826869914e-05 & 3.07690413434957e-05 \tabularnewline
92 & 0.999955523839929 & 8.89523201418757e-05 & 4.44761600709378e-05 \tabularnewline
93 & 0.999963302031111 & 7.33959377782362e-05 & 3.66979688891181e-05 \tabularnewline
94 & 0.999955927648779 & 8.81447024418704e-05 & 4.40723512209352e-05 \tabularnewline
95 & 0.99995299449031 & 9.40110193805852e-05 & 4.70055096902926e-05 \tabularnewline
96 & 0.999931238183604 & 0.000137523632792939 & 6.87618163964696e-05 \tabularnewline
97 & 0.99990102006459 & 0.000197959870819671 & 9.89799354098355e-05 \tabularnewline
98 & 0.999877599548809 & 0.000244800902382431 & 0.000122400451191215 \tabularnewline
99 & 0.999866273002925 & 0.000267453994150962 & 0.000133726997075481 \tabularnewline
100 & 0.999823401545973 & 0.000353196908054817 & 0.000176598454027408 \tabularnewline
101 & 0.999791795595576 & 0.000416408808847977 & 0.000208204404423988 \tabularnewline
102 & 0.999711866921596 & 0.000576266156808473 & 0.000288133078404236 \tabularnewline
103 & 0.999602360194914 & 0.000795279610171067 & 0.000397639805085534 \tabularnewline
104 & 0.999654262802717 & 0.000691474394566698 & 0.000345737197283349 \tabularnewline
105 & 0.999622109655337 & 0.000755780689326053 & 0.000377890344663027 \tabularnewline
106 & 0.999608147260931 & 0.000783705478138013 & 0.000391852739069006 \tabularnewline
107 & 0.999557446357923 & 0.000885107284153457 & 0.000442553642076729 \tabularnewline
108 & 0.999499546182341 & 0.00100090763531745 & 0.000500453817658727 \tabularnewline
109 & 0.999308515431578 & 0.0013829691368438 & 0.000691484568421902 \tabularnewline
110 & 0.999067927494641 & 0.00186414501071877 & 0.000932072505359387 \tabularnewline
111 & 0.998833688970193 & 0.00233262205961458 & 0.00116631102980729 \tabularnewline
112 & 0.998412750118758 & 0.00317449976248333 & 0.00158724988124166 \tabularnewline
113 & 0.998151871295678 & 0.00369625740864398 & 0.00184812870432199 \tabularnewline
114 & 0.998004785207946 & 0.00399042958410864 & 0.00199521479205432 \tabularnewline
115 & 0.997380587384086 & 0.00523882523182775 & 0.00261941261591387 \tabularnewline
116 & 0.997476990984419 & 0.0050460180311611 & 0.00252300901558055 \tabularnewline
117 & 0.999077384939977 & 0.00184523012004611 & 0.000922615060023055 \tabularnewline
118 & 0.99878001925447 & 0.0024399614910608 & 0.0012199807455304 \tabularnewline
119 & 0.998341656138243 & 0.00331668772351301 & 0.00165834386175651 \tabularnewline
120 & 0.997914335959896 & 0.00417132808020802 & 0.00208566404010401 \tabularnewline
121 & 0.997651269568989 & 0.00469746086202124 & 0.00234873043101062 \tabularnewline
122 & 0.996962747648984 & 0.00607450470203224 & 0.00303725235101612 \tabularnewline
123 & 0.995988650641608 & 0.00802269871678496 & 0.00401134935839248 \tabularnewline
124 & 0.994953174417749 & 0.0100936511645029 & 0.00504682558225147 \tabularnewline
125 & 0.993811549907627 & 0.0123769001847466 & 0.00618845009237331 \tabularnewline
126 & 0.992054174503283 & 0.0158916509934332 & 0.00794582549671662 \tabularnewline
127 & 0.98976403142092 & 0.020471937158161 & 0.0102359685790805 \tabularnewline
128 & 0.987748645758124 & 0.0245027084837525 & 0.0122513542418762 \tabularnewline
129 & 0.984640559539003 & 0.0307188809219931 & 0.0153594404609965 \tabularnewline
130 & 0.980698271908682 & 0.0386034561826357 & 0.0193017280913178 \tabularnewline
131 & 0.976387390401525 & 0.0472252191969491 & 0.0236126095984746 \tabularnewline
132 & 0.972757227763799 & 0.0544855444724029 & 0.0272427722362014 \tabularnewline
133 & 0.96791416379916 & 0.0641716724016809 & 0.0320858362008405 \tabularnewline
134 & 0.960642834885738 & 0.0787143302285235 & 0.0393571651142618 \tabularnewline
135 & 0.954349312262471 & 0.0913013754750587 & 0.0456506877375293 \tabularnewline
136 & 0.944683241264445 & 0.11063351747111 & 0.0553167587355552 \tabularnewline
137 & 0.93627221533524 & 0.127455569329521 & 0.0637277846647604 \tabularnewline
138 & 0.93104255962903 & 0.137914880741941 & 0.0689574403709703 \tabularnewline
139 & 0.917538321545995 & 0.164923356908009 & 0.0824616784540046 \tabularnewline
140 & 0.904744670158008 & 0.190510659683983 & 0.0952553298419917 \tabularnewline
141 & 0.985222217803591 & 0.0295555643928181 & 0.014777782196409 \tabularnewline
142 & 0.986006546058764 & 0.0279869078824727 & 0.0139934539412364 \tabularnewline
143 & 0.982469326360386 & 0.0350613472792279 & 0.0175306736396139 \tabularnewline
144 & 0.978347582764962 & 0.0433048344700763 & 0.0216524172350382 \tabularnewline
145 & 0.976647907742021 & 0.0467041845159581 & 0.0233520922579791 \tabularnewline
146 & 0.972253121037997 & 0.0554937579240068 & 0.0277468789620034 \tabularnewline
147 & 0.965455997128212 & 0.0690880057435771 & 0.0345440028717885 \tabularnewline
148 & 0.959162529887995 & 0.0816749402240109 & 0.0408374701120054 \tabularnewline
149 & 0.950210190402777 & 0.0995796191944461 & 0.0497898095972231 \tabularnewline
150 & 0.939811832669947 & 0.120376334660107 & 0.0601881673300535 \tabularnewline
151 & 0.928009470765864 & 0.143981058468273 & 0.0719905292341364 \tabularnewline
152 & 0.919567517198845 & 0.160864965602311 & 0.0804324828011553 \tabularnewline
153 & 0.947164916123142 & 0.105670167753717 & 0.0528350838768583 \tabularnewline
154 & 0.935834444122861 & 0.128331111754278 & 0.064165555877139 \tabularnewline
155 & 0.923819335423497 & 0.152361329153007 & 0.0761806645765033 \tabularnewline
156 & 0.921319565614807 & 0.157360868770385 & 0.0786804343851927 \tabularnewline
157 & 0.907652117808564 & 0.184695764382872 & 0.0923478821914359 \tabularnewline
158 & 0.894361957571908 & 0.211276084856185 & 0.105638042428092 \tabularnewline
159 & 0.875694393387636 & 0.248611213224728 & 0.124305606612364 \tabularnewline
160 & 0.882148434755128 & 0.235703130489743 & 0.117851565244872 \tabularnewline
161 & 0.8719165301207 & 0.256166939758599 & 0.1280834698793 \tabularnewline
162 & 0.891631886314655 & 0.21673622737069 & 0.108368113685345 \tabularnewline
163 & 0.876007279135368 & 0.247985441729264 & 0.123992720864632 \tabularnewline
164 & 0.861412229275447 & 0.277175541449106 & 0.138587770724553 \tabularnewline
165 & 0.888648174746845 & 0.22270365050631 & 0.111351825253155 \tabularnewline
166 & 0.869113715197458 & 0.261772569605085 & 0.130886284802542 \tabularnewline
167 & 0.850432423506448 & 0.299135152987104 & 0.149567576493552 \tabularnewline
168 & 0.831153058941995 & 0.33769388211601 & 0.168846941058005 \tabularnewline
169 & 0.807747736523297 & 0.384504526953407 & 0.192252263476703 \tabularnewline
170 & 0.782445926066797 & 0.435108147866406 & 0.217554073933203 \tabularnewline
171 & 0.750328890632129 & 0.499342218735742 & 0.249671109367871 \tabularnewline
172 & 0.737844282637869 & 0.524311434724263 & 0.262155717362131 \tabularnewline
173 & 0.728559807670058 & 0.542880384659884 & 0.271440192329942 \tabularnewline
174 & 0.736826323899924 & 0.526347352200152 & 0.263173676100076 \tabularnewline
175 & 0.706451281181673 & 0.587097437636654 & 0.293548718818327 \tabularnewline
176 & 0.673749562518669 & 0.652500874962662 & 0.326250437481331 \tabularnewline
177 & 0.699061637781918 & 0.601876724436163 & 0.300938362218082 \tabularnewline
178 & 0.680116422711114 & 0.639767154577771 & 0.319883577288886 \tabularnewline
179 & 0.640028864469256 & 0.719942271061488 & 0.359971135530744 \tabularnewline
180 & 0.59855917902141 & 0.802881641957181 & 0.40144082097859 \tabularnewline
181 & 0.580332785169675 & 0.83933442966065 & 0.419667214830325 \tabularnewline
182 & 0.541907563031661 & 0.916184873936679 & 0.458092436968339 \tabularnewline
183 & 0.497683406159941 & 0.995366812319883 & 0.502316593840059 \tabularnewline
184 & 0.456057929006833 & 0.912115858013667 & 0.543942070993167 \tabularnewline
185 & 0.440771102507704 & 0.881542205015408 & 0.559228897492296 \tabularnewline
186 & 0.421051213979305 & 0.84210242795861 & 0.578948786020695 \tabularnewline
187 & 0.38018734964363 & 0.76037469928726 & 0.61981265035637 \tabularnewline
188 & 0.360783503694466 & 0.721567007388932 & 0.639216496305534 \tabularnewline
189 & 0.329207758325749 & 0.658415516651498 & 0.670792241674251 \tabularnewline
190 & 0.298142918428071 & 0.596285836856142 & 0.701857081571929 \tabularnewline
191 & 0.260188234730926 & 0.520376469461852 & 0.739811765269074 \tabularnewline
192 & 0.226187324594889 & 0.452374649189778 & 0.773812675405111 \tabularnewline
193 & 0.199183663314681 & 0.398367326629363 & 0.800816336685319 \tabularnewline
194 & 0.21218782981907 & 0.42437565963814 & 0.78781217018093 \tabularnewline
195 & 0.179141220458046 & 0.358282440916091 & 0.820858779541954 \tabularnewline
196 & 0.152964027683691 & 0.305928055367382 & 0.847035972316309 \tabularnewline
197 & 0.129433696203453 & 0.258867392406905 & 0.870566303796547 \tabularnewline
198 & 0.146202742556766 & 0.292405485113531 & 0.853797257443234 \tabularnewline
199 & 0.193568445552296 & 0.387136891104592 & 0.806431554447704 \tabularnewline
200 & 0.175183701139143 & 0.350367402278285 & 0.824816298860857 \tabularnewline
201 & 0.693656127364241 & 0.612687745271518 & 0.306343872635759 \tabularnewline
202 & 0.664739892597503 & 0.670520214804994 & 0.335260107402497 \tabularnewline
203 & 0.613906341416478 & 0.772187317167044 & 0.386093658583522 \tabularnewline
204 & 0.580161422308515 & 0.83967715538297 & 0.419838577691485 \tabularnewline
205 & 0.531764180113254 & 0.936471639773493 & 0.468235819886746 \tabularnewline
206 & 0.487710961809112 & 0.975421923618224 & 0.512289038190888 \tabularnewline
207 & 0.432043899768086 & 0.864087799536171 & 0.567956100231914 \tabularnewline
208 & 0.428917849809974 & 0.857835699619949 & 0.571082150190026 \tabularnewline
209 & 0.394924027354985 & 0.78984805470997 & 0.605075972645015 \tabularnewline
210 & 0.355464445369139 & 0.710928890738278 & 0.644535554630861 \tabularnewline
211 & 0.302789692791238 & 0.605579385582475 & 0.697210307208762 \tabularnewline
212 & 0.266295286640805 & 0.532590573281609 & 0.733704713359195 \tabularnewline
213 & 0.310402716046266 & 0.620805432092532 & 0.689597283953734 \tabularnewline
214 & 0.258553099101508 & 0.517106198203016 & 0.741446900898492 \tabularnewline
215 & 0.208824077875674 & 0.417648155751349 & 0.791175922124326 \tabularnewline
216 & 0.191623870942681 & 0.383247741885361 & 0.808376129057319 \tabularnewline
217 & 0.163001383784177 & 0.326002767568354 & 0.836998616215823 \tabularnewline
218 & 0.12431431882756 & 0.24862863765512 & 0.87568568117244 \tabularnewline
219 & 0.0944354137877301 & 0.18887082757546 & 0.90556458621227 \tabularnewline
220 & 0.0680191742541533 & 0.136038348508307 & 0.931980825745847 \tabularnewline
221 & 0.126716598723981 & 0.253433197447963 & 0.873283401276019 \tabularnewline
222 & 0.0997201877233813 & 0.199440375446763 & 0.900279812276619 \tabularnewline
223 & 0.0776247018791352 & 0.15524940375827 & 0.922375298120865 \tabularnewline
224 & 0.0518596318640386 & 0.103719263728077 & 0.948140368135961 \tabularnewline
225 & 0.179244885151676 & 0.358489770303352 & 0.820755114848324 \tabularnewline
226 & 0.134266740448975 & 0.268533480897949 & 0.865733259551025 \tabularnewline
227 & 0.102828686359718 & 0.205657372719437 & 0.897171313640282 \tabularnewline
228 & 0.0644874699283633 & 0.128974939856727 & 0.935512530071637 \tabularnewline
229 & 0.0381525923074449 & 0.0763051846148898 & 0.961847407692555 \tabularnewline
230 & 0.0201513229537305 & 0.0403026459074611 & 0.979848677046269 \tabularnewline
231 & 0.0105340914706552 & 0.0210681829413105 & 0.989465908529345 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147113&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]9[/C][C]0.00253611103832127[/C][C]0.00507222207664255[/C][C]0.997463888961679[/C][/ROW]
[ROW][C]10[/C][C]0.000294780874922865[/C][C]0.00058956174984573[/C][C]0.999705219125077[/C][/ROW]
[ROW][C]11[/C][C]4.61634447457135e-05[/C][C]9.23268894914269e-05[/C][C]0.999953836555254[/C][/ROW]
[ROW][C]12[/C][C]8.26358221532064e-06[/C][C]1.65271644306413e-05[/C][C]0.999991736417785[/C][/ROW]
[ROW][C]13[/C][C]5.12657708080341e-05[/C][C]0.000102531541616068[/C][C]0.999948734229192[/C][/ROW]
[ROW][C]14[/C][C]1.76682927169551e-05[/C][C]3.53365854339101e-05[/C][C]0.999982331707283[/C][/ROW]
[ROW][C]15[/C][C]3.10140521981403e-06[/C][C]6.20281043962806e-06[/C][C]0.99999689859478[/C][/ROW]
[ROW][C]16[/C][C]2.06623695981552e-06[/C][C]4.13247391963105e-06[/C][C]0.99999793376304[/C][/ROW]
[ROW][C]17[/C][C]3.76422620230122e-07[/C][C]7.52845240460244e-07[/C][C]0.99999962357738[/C][/ROW]
[ROW][C]18[/C][C]6.61690348668505e-08[/C][C]1.32338069733701e-07[/C][C]0.999999933830965[/C][/ROW]
[ROW][C]19[/C][C]2.13324579522426e-08[/C][C]4.26649159044851e-08[/C][C]0.999999978667542[/C][/ROW]
[ROW][C]20[/C][C]3.06021960146136e-07[/C][C]6.12043920292272e-07[/C][C]0.99999969397804[/C][/ROW]
[ROW][C]21[/C][C]9.86638790828989e-08[/C][C]1.97327758165798e-07[/C][C]0.999999901336121[/C][/ROW]
[ROW][C]22[/C][C]6.09774347846367e-08[/C][C]1.21954869569273e-07[/C][C]0.999999939022565[/C][/ROW]
[ROW][C]23[/C][C]2.15053340046003e-08[/C][C]4.30106680092005e-08[/C][C]0.999999978494666[/C][/ROW]
[ROW][C]24[/C][C]5.28682275828303e-09[/C][C]1.05736455165661e-08[/C][C]0.999999994713177[/C][/ROW]
[ROW][C]25[/C][C]1.24429460507007e-09[/C][C]2.48858921014015e-09[/C][C]0.999999998755705[/C][/ROW]
[ROW][C]26[/C][C]4.00244242272758e-10[/C][C]8.00488484545516e-10[/C][C]0.999999999599756[/C][/ROW]
[ROW][C]27[/C][C]9.11726040475746e-11[/C][C]1.82345208095149e-10[/C][C]0.999999999908827[/C][/ROW]
[ROW][C]28[/C][C]1.97876873925882e-11[/C][C]3.95753747851764e-11[/C][C]0.999999999980212[/C][/ROW]
[ROW][C]29[/C][C]4.38965743729097e-12[/C][C]8.77931487458193e-12[/C][C]0.99999999999561[/C][/ROW]
[ROW][C]30[/C][C]1.99005980223055e-12[/C][C]3.98011960446111e-12[/C][C]0.99999999999801[/C][/ROW]
[ROW][C]31[/C][C]4.26928763366473e-13[/C][C]8.53857526732945e-13[/C][C]0.999999999999573[/C][/ROW]
[ROW][C]32[/C][C]1.72224611124712e-13[/C][C]3.44449222249425e-13[/C][C]0.999999999999828[/C][/ROW]
[ROW][C]33[/C][C]0.00274835935697299[/C][C]0.00549671871394598[/C][C]0.997251640643027[/C][/ROW]
[ROW][C]34[/C][C]0.00174765410769992[/C][C]0.00349530821539984[/C][C]0.9982523458923[/C][/ROW]
[ROW][C]35[/C][C]0.00114000360426672[/C][C]0.00228000720853345[/C][C]0.998859996395733[/C][/ROW]
[ROW][C]36[/C][C]0.000688657856745914[/C][C]0.00137731571349183[/C][C]0.999311342143254[/C][/ROW]
[ROW][C]37[/C][C]0.000446396513163133[/C][C]0.000892793026326267[/C][C]0.999553603486837[/C][/ROW]
[ROW][C]38[/C][C]0.000275237457269887[/C][C]0.000550474914539773[/C][C]0.99972476254273[/C][/ROW]
[ROW][C]39[/C][C]0.899544444460117[/C][C]0.200911111079766[/C][C]0.100455555539883[/C][/ROW]
[ROW][C]40[/C][C]0.884673706097956[/C][C]0.230652587804089[/C][C]0.115326293902044[/C][/ROW]
[ROW][C]41[/C][C]0.862166787281287[/C][C]0.275666425437425[/C][C]0.137833212718713[/C][/ROW]
[ROW][C]42[/C][C]0.834742485984145[/C][C]0.33051502803171[/C][C]0.165257514015855[/C][/ROW]
[ROW][C]43[/C][C]0.802858448820429[/C][C]0.394283102359141[/C][C]0.197141551179571[/C][/ROW]
[ROW][C]44[/C][C]0.767757972837473[/C][C]0.464484054325055[/C][C]0.232242027162527[/C][/ROW]
[ROW][C]45[/C][C]0.941581791871001[/C][C]0.116836416257998[/C][C]0.0584182081289989[/C][/ROW]
[ROW][C]46[/C][C]0.929816258737415[/C][C]0.14036748252517[/C][C]0.0701837412625848[/C][/ROW]
[ROW][C]47[/C][C]0.918217394419685[/C][C]0.163565211160629[/C][C]0.0817826055803147[/C][/ROW]
[ROW][C]48[/C][C]0.914437659271438[/C][C]0.171124681457124[/C][C]0.0855623407285621[/C][/ROW]
[ROW][C]49[/C][C]0.895989928592792[/C][C]0.208020142814416[/C][C]0.104010071407208[/C][/ROW]
[ROW][C]50[/C][C]0.883353636549007[/C][C]0.233292726901987[/C][C]0.116646363450993[/C][/ROW]
[ROW][C]51[/C][C]0.859411316550279[/C][C]0.281177366899442[/C][C]0.140588683449721[/C][/ROW]
[ROW][C]52[/C][C]0.835693898187354[/C][C]0.328612203625292[/C][C]0.164306101812646[/C][/ROW]
[ROW][C]53[/C][C]0.807183809168228[/C][C]0.385632381663544[/C][C]0.192816190831772[/C][/ROW]
[ROW][C]54[/C][C]0.776479512832088[/C][C]0.447040974335824[/C][C]0.223520487167912[/C][/ROW]
[ROW][C]55[/C][C]0.742124754497883[/C][C]0.515750491004233[/C][C]0.257875245502117[/C][/ROW]
[ROW][C]56[/C][C]0.705435285592942[/C][C]0.589129428814115[/C][C]0.294564714407058[/C][/ROW]
[ROW][C]57[/C][C]0.999885216204428[/C][C]0.000229567591143004[/C][C]0.000114783795571502[/C][/ROW]
[ROW][C]58[/C][C]0.999902026294598[/C][C]0.000195947410803907[/C][C]9.79737054019535e-05[/C][/ROW]
[ROW][C]59[/C][C]0.999852683558763[/C][C]0.000294632882473423[/C][C]0.000147316441236712[/C][/ROW]
[ROW][C]60[/C][C]0.99984196248406[/C][C]0.000316075031880808[/C][C]0.000158037515940404[/C][/ROW]
[ROW][C]61[/C][C]0.99979035043768[/C][C]0.000419299124639371[/C][C]0.000209649562319686[/C][/ROW]
[ROW][C]62[/C][C]0.999713358586036[/C][C]0.000573282827926921[/C][C]0.000286641413963461[/C][/ROW]
[ROW][C]63[/C][C]0.99963731447513[/C][C]0.00072537104974031[/C][C]0.000362685524870155[/C][/ROW]
[ROW][C]64[/C][C]0.999511708550618[/C][C]0.000976582898763575[/C][C]0.000488291449381787[/C][/ROW]
[ROW][C]65[/C][C]0.999611608216205[/C][C]0.000776783567590676[/C][C]0.000388391783795338[/C][/ROW]
[ROW][C]66[/C][C]0.999596621408248[/C][C]0.000806757183504062[/C][C]0.000403378591752031[/C][/ROW]
[ROW][C]67[/C][C]0.999458367775022[/C][C]0.00108326444995556[/C][C]0.00054163222497778[/C][/ROW]
[ROW][C]68[/C][C]0.999318297175238[/C][C]0.00136340564952351[/C][C]0.000681702824761754[/C][/ROW]
[ROW][C]69[/C][C]0.999999402308096[/C][C]1.19538380823799e-06[/C][C]5.97691904118993e-07[/C][/ROW]
[ROW][C]70[/C][C]0.999999073400111[/C][C]1.85319977880458e-06[/C][C]9.2659988940229e-07[/C][/ROW]
[ROW][C]71[/C][C]0.99999849737463[/C][C]3.00525074058373e-06[/C][C]1.50262537029187e-06[/C][/ROW]
[ROW][C]72[/C][C]0.99999761244721[/C][C]4.77510557910933e-06[/C][C]2.38755278955466e-06[/C][/ROW]
[ROW][C]73[/C][C]0.999999020169306[/C][C]1.95966138791697e-06[/C][C]9.79830693958483e-07[/C][/ROW]
[ROW][C]74[/C][C]0.999998442350762[/C][C]3.11529847612091e-06[/C][C]1.55764923806045e-06[/C][/ROW]
[ROW][C]75[/C][C]0.999997953983961[/C][C]4.09203207763146e-06[/C][C]2.04601603881573e-06[/C][/ROW]
[ROW][C]76[/C][C]0.999997248164966[/C][C]5.50367006702455e-06[/C][C]2.75183503351228e-06[/C][/ROW]
[ROW][C]77[/C][C]0.999995650798315[/C][C]8.69840337033962e-06[/C][C]4.34920168516981e-06[/C][/ROW]
[ROW][C]78[/C][C]0.99999695789904[/C][C]6.08420192023415e-06[/C][C]3.04210096011708e-06[/C][/ROW]
[ROW][C]79[/C][C]0.999995805630207[/C][C]8.38873958598725e-06[/C][C]4.19436979299362e-06[/C][/ROW]
[ROW][C]80[/C][C]0.999994316365271[/C][C]1.13672694585578e-05[/C][C]5.68363472927888e-06[/C][/ROW]
[ROW][C]81[/C][C]0.999997509521441[/C][C]4.98095711766516e-06[/C][C]2.49047855883258e-06[/C][/ROW]
[ROW][C]82[/C][C]0.999996175330824[/C][C]7.64933835279075e-06[/C][C]3.82466917639538e-06[/C][/ROW]
[ROW][C]83[/C][C]0.999995582179904[/C][C]8.83564019116946e-06[/C][C]4.41782009558473e-06[/C][/ROW]
[ROW][C]84[/C][C]0.999993598658256[/C][C]1.28026834877772e-05[/C][C]6.40134174388861e-06[/C][/ROW]
[ROW][C]85[/C][C]0.999991756812041[/C][C]1.64863759181441e-05[/C][C]8.24318795907205e-06[/C][/ROW]
[ROW][C]86[/C][C]0.99998849896489[/C][C]2.30020702201271e-05[/C][C]1.15010351100635e-05[/C][/ROW]
[ROW][C]87[/C][C]0.999985018201689[/C][C]2.99635966219106e-05[/C][C]1.49817983109553e-05[/C][/ROW]
[ROW][C]88[/C][C]0.999981028961296[/C][C]3.79420774077633e-05[/C][C]1.89710387038817e-05[/C][/ROW]
[ROW][C]89[/C][C]0.999983155679033[/C][C]3.36886419342385e-05[/C][C]1.68443209671193e-05[/C][/ROW]
[ROW][C]90[/C][C]0.999978348048163[/C][C]4.33039036735304e-05[/C][C]2.16519518367652e-05[/C][/ROW]
[ROW][C]91[/C][C]0.999969230958657[/C][C]6.15380826869914e-05[/C][C]3.07690413434957e-05[/C][/ROW]
[ROW][C]92[/C][C]0.999955523839929[/C][C]8.89523201418757e-05[/C][C]4.44761600709378e-05[/C][/ROW]
[ROW][C]93[/C][C]0.999963302031111[/C][C]7.33959377782362e-05[/C][C]3.66979688891181e-05[/C][/ROW]
[ROW][C]94[/C][C]0.999955927648779[/C][C]8.81447024418704e-05[/C][C]4.40723512209352e-05[/C][/ROW]
[ROW][C]95[/C][C]0.99995299449031[/C][C]9.40110193805852e-05[/C][C]4.70055096902926e-05[/C][/ROW]
[ROW][C]96[/C][C]0.999931238183604[/C][C]0.000137523632792939[/C][C]6.87618163964696e-05[/C][/ROW]
[ROW][C]97[/C][C]0.99990102006459[/C][C]0.000197959870819671[/C][C]9.89799354098355e-05[/C][/ROW]
[ROW][C]98[/C][C]0.999877599548809[/C][C]0.000244800902382431[/C][C]0.000122400451191215[/C][/ROW]
[ROW][C]99[/C][C]0.999866273002925[/C][C]0.000267453994150962[/C][C]0.000133726997075481[/C][/ROW]
[ROW][C]100[/C][C]0.999823401545973[/C][C]0.000353196908054817[/C][C]0.000176598454027408[/C][/ROW]
[ROW][C]101[/C][C]0.999791795595576[/C][C]0.000416408808847977[/C][C]0.000208204404423988[/C][/ROW]
[ROW][C]102[/C][C]0.999711866921596[/C][C]0.000576266156808473[/C][C]0.000288133078404236[/C][/ROW]
[ROW][C]103[/C][C]0.999602360194914[/C][C]0.000795279610171067[/C][C]0.000397639805085534[/C][/ROW]
[ROW][C]104[/C][C]0.999654262802717[/C][C]0.000691474394566698[/C][C]0.000345737197283349[/C][/ROW]
[ROW][C]105[/C][C]0.999622109655337[/C][C]0.000755780689326053[/C][C]0.000377890344663027[/C][/ROW]
[ROW][C]106[/C][C]0.999608147260931[/C][C]0.000783705478138013[/C][C]0.000391852739069006[/C][/ROW]
[ROW][C]107[/C][C]0.999557446357923[/C][C]0.000885107284153457[/C][C]0.000442553642076729[/C][/ROW]
[ROW][C]108[/C][C]0.999499546182341[/C][C]0.00100090763531745[/C][C]0.000500453817658727[/C][/ROW]
[ROW][C]109[/C][C]0.999308515431578[/C][C]0.0013829691368438[/C][C]0.000691484568421902[/C][/ROW]
[ROW][C]110[/C][C]0.999067927494641[/C][C]0.00186414501071877[/C][C]0.000932072505359387[/C][/ROW]
[ROW][C]111[/C][C]0.998833688970193[/C][C]0.00233262205961458[/C][C]0.00116631102980729[/C][/ROW]
[ROW][C]112[/C][C]0.998412750118758[/C][C]0.00317449976248333[/C][C]0.00158724988124166[/C][/ROW]
[ROW][C]113[/C][C]0.998151871295678[/C][C]0.00369625740864398[/C][C]0.00184812870432199[/C][/ROW]
[ROW][C]114[/C][C]0.998004785207946[/C][C]0.00399042958410864[/C][C]0.00199521479205432[/C][/ROW]
[ROW][C]115[/C][C]0.997380587384086[/C][C]0.00523882523182775[/C][C]0.00261941261591387[/C][/ROW]
[ROW][C]116[/C][C]0.997476990984419[/C][C]0.0050460180311611[/C][C]0.00252300901558055[/C][/ROW]
[ROW][C]117[/C][C]0.999077384939977[/C][C]0.00184523012004611[/C][C]0.000922615060023055[/C][/ROW]
[ROW][C]118[/C][C]0.99878001925447[/C][C]0.0024399614910608[/C][C]0.0012199807455304[/C][/ROW]
[ROW][C]119[/C][C]0.998341656138243[/C][C]0.00331668772351301[/C][C]0.00165834386175651[/C][/ROW]
[ROW][C]120[/C][C]0.997914335959896[/C][C]0.00417132808020802[/C][C]0.00208566404010401[/C][/ROW]
[ROW][C]121[/C][C]0.997651269568989[/C][C]0.00469746086202124[/C][C]0.00234873043101062[/C][/ROW]
[ROW][C]122[/C][C]0.996962747648984[/C][C]0.00607450470203224[/C][C]0.00303725235101612[/C][/ROW]
[ROW][C]123[/C][C]0.995988650641608[/C][C]0.00802269871678496[/C][C]0.00401134935839248[/C][/ROW]
[ROW][C]124[/C][C]0.994953174417749[/C][C]0.0100936511645029[/C][C]0.00504682558225147[/C][/ROW]
[ROW][C]125[/C][C]0.993811549907627[/C][C]0.0123769001847466[/C][C]0.00618845009237331[/C][/ROW]
[ROW][C]126[/C][C]0.992054174503283[/C][C]0.0158916509934332[/C][C]0.00794582549671662[/C][/ROW]
[ROW][C]127[/C][C]0.98976403142092[/C][C]0.020471937158161[/C][C]0.0102359685790805[/C][/ROW]
[ROW][C]128[/C][C]0.987748645758124[/C][C]0.0245027084837525[/C][C]0.0122513542418762[/C][/ROW]
[ROW][C]129[/C][C]0.984640559539003[/C][C]0.0307188809219931[/C][C]0.0153594404609965[/C][/ROW]
[ROW][C]130[/C][C]0.980698271908682[/C][C]0.0386034561826357[/C][C]0.0193017280913178[/C][/ROW]
[ROW][C]131[/C][C]0.976387390401525[/C][C]0.0472252191969491[/C][C]0.0236126095984746[/C][/ROW]
[ROW][C]132[/C][C]0.972757227763799[/C][C]0.0544855444724029[/C][C]0.0272427722362014[/C][/ROW]
[ROW][C]133[/C][C]0.96791416379916[/C][C]0.0641716724016809[/C][C]0.0320858362008405[/C][/ROW]
[ROW][C]134[/C][C]0.960642834885738[/C][C]0.0787143302285235[/C][C]0.0393571651142618[/C][/ROW]
[ROW][C]135[/C][C]0.954349312262471[/C][C]0.0913013754750587[/C][C]0.0456506877375293[/C][/ROW]
[ROW][C]136[/C][C]0.944683241264445[/C][C]0.11063351747111[/C][C]0.0553167587355552[/C][/ROW]
[ROW][C]137[/C][C]0.93627221533524[/C][C]0.127455569329521[/C][C]0.0637277846647604[/C][/ROW]
[ROW][C]138[/C][C]0.93104255962903[/C][C]0.137914880741941[/C][C]0.0689574403709703[/C][/ROW]
[ROW][C]139[/C][C]0.917538321545995[/C][C]0.164923356908009[/C][C]0.0824616784540046[/C][/ROW]
[ROW][C]140[/C][C]0.904744670158008[/C][C]0.190510659683983[/C][C]0.0952553298419917[/C][/ROW]
[ROW][C]141[/C][C]0.985222217803591[/C][C]0.0295555643928181[/C][C]0.014777782196409[/C][/ROW]
[ROW][C]142[/C][C]0.986006546058764[/C][C]0.0279869078824727[/C][C]0.0139934539412364[/C][/ROW]
[ROW][C]143[/C][C]0.982469326360386[/C][C]0.0350613472792279[/C][C]0.0175306736396139[/C][/ROW]
[ROW][C]144[/C][C]0.978347582764962[/C][C]0.0433048344700763[/C][C]0.0216524172350382[/C][/ROW]
[ROW][C]145[/C][C]0.976647907742021[/C][C]0.0467041845159581[/C][C]0.0233520922579791[/C][/ROW]
[ROW][C]146[/C][C]0.972253121037997[/C][C]0.0554937579240068[/C][C]0.0277468789620034[/C][/ROW]
[ROW][C]147[/C][C]0.965455997128212[/C][C]0.0690880057435771[/C][C]0.0345440028717885[/C][/ROW]
[ROW][C]148[/C][C]0.959162529887995[/C][C]0.0816749402240109[/C][C]0.0408374701120054[/C][/ROW]
[ROW][C]149[/C][C]0.950210190402777[/C][C]0.0995796191944461[/C][C]0.0497898095972231[/C][/ROW]
[ROW][C]150[/C][C]0.939811832669947[/C][C]0.120376334660107[/C][C]0.0601881673300535[/C][/ROW]
[ROW][C]151[/C][C]0.928009470765864[/C][C]0.143981058468273[/C][C]0.0719905292341364[/C][/ROW]
[ROW][C]152[/C][C]0.919567517198845[/C][C]0.160864965602311[/C][C]0.0804324828011553[/C][/ROW]
[ROW][C]153[/C][C]0.947164916123142[/C][C]0.105670167753717[/C][C]0.0528350838768583[/C][/ROW]
[ROW][C]154[/C][C]0.935834444122861[/C][C]0.128331111754278[/C][C]0.064165555877139[/C][/ROW]
[ROW][C]155[/C][C]0.923819335423497[/C][C]0.152361329153007[/C][C]0.0761806645765033[/C][/ROW]
[ROW][C]156[/C][C]0.921319565614807[/C][C]0.157360868770385[/C][C]0.0786804343851927[/C][/ROW]
[ROW][C]157[/C][C]0.907652117808564[/C][C]0.184695764382872[/C][C]0.0923478821914359[/C][/ROW]
[ROW][C]158[/C][C]0.894361957571908[/C][C]0.211276084856185[/C][C]0.105638042428092[/C][/ROW]
[ROW][C]159[/C][C]0.875694393387636[/C][C]0.248611213224728[/C][C]0.124305606612364[/C][/ROW]
[ROW][C]160[/C][C]0.882148434755128[/C][C]0.235703130489743[/C][C]0.117851565244872[/C][/ROW]
[ROW][C]161[/C][C]0.8719165301207[/C][C]0.256166939758599[/C][C]0.1280834698793[/C][/ROW]
[ROW][C]162[/C][C]0.891631886314655[/C][C]0.21673622737069[/C][C]0.108368113685345[/C][/ROW]
[ROW][C]163[/C][C]0.876007279135368[/C][C]0.247985441729264[/C][C]0.123992720864632[/C][/ROW]
[ROW][C]164[/C][C]0.861412229275447[/C][C]0.277175541449106[/C][C]0.138587770724553[/C][/ROW]
[ROW][C]165[/C][C]0.888648174746845[/C][C]0.22270365050631[/C][C]0.111351825253155[/C][/ROW]
[ROW][C]166[/C][C]0.869113715197458[/C][C]0.261772569605085[/C][C]0.130886284802542[/C][/ROW]
[ROW][C]167[/C][C]0.850432423506448[/C][C]0.299135152987104[/C][C]0.149567576493552[/C][/ROW]
[ROW][C]168[/C][C]0.831153058941995[/C][C]0.33769388211601[/C][C]0.168846941058005[/C][/ROW]
[ROW][C]169[/C][C]0.807747736523297[/C][C]0.384504526953407[/C][C]0.192252263476703[/C][/ROW]
[ROW][C]170[/C][C]0.782445926066797[/C][C]0.435108147866406[/C][C]0.217554073933203[/C][/ROW]
[ROW][C]171[/C][C]0.750328890632129[/C][C]0.499342218735742[/C][C]0.249671109367871[/C][/ROW]
[ROW][C]172[/C][C]0.737844282637869[/C][C]0.524311434724263[/C][C]0.262155717362131[/C][/ROW]
[ROW][C]173[/C][C]0.728559807670058[/C][C]0.542880384659884[/C][C]0.271440192329942[/C][/ROW]
[ROW][C]174[/C][C]0.736826323899924[/C][C]0.526347352200152[/C][C]0.263173676100076[/C][/ROW]
[ROW][C]175[/C][C]0.706451281181673[/C][C]0.587097437636654[/C][C]0.293548718818327[/C][/ROW]
[ROW][C]176[/C][C]0.673749562518669[/C][C]0.652500874962662[/C][C]0.326250437481331[/C][/ROW]
[ROW][C]177[/C][C]0.699061637781918[/C][C]0.601876724436163[/C][C]0.300938362218082[/C][/ROW]
[ROW][C]178[/C][C]0.680116422711114[/C][C]0.639767154577771[/C][C]0.319883577288886[/C][/ROW]
[ROW][C]179[/C][C]0.640028864469256[/C][C]0.719942271061488[/C][C]0.359971135530744[/C][/ROW]
[ROW][C]180[/C][C]0.59855917902141[/C][C]0.802881641957181[/C][C]0.40144082097859[/C][/ROW]
[ROW][C]181[/C][C]0.580332785169675[/C][C]0.83933442966065[/C][C]0.419667214830325[/C][/ROW]
[ROW][C]182[/C][C]0.541907563031661[/C][C]0.916184873936679[/C][C]0.458092436968339[/C][/ROW]
[ROW][C]183[/C][C]0.497683406159941[/C][C]0.995366812319883[/C][C]0.502316593840059[/C][/ROW]
[ROW][C]184[/C][C]0.456057929006833[/C][C]0.912115858013667[/C][C]0.543942070993167[/C][/ROW]
[ROW][C]185[/C][C]0.440771102507704[/C][C]0.881542205015408[/C][C]0.559228897492296[/C][/ROW]
[ROW][C]186[/C][C]0.421051213979305[/C][C]0.84210242795861[/C][C]0.578948786020695[/C][/ROW]
[ROW][C]187[/C][C]0.38018734964363[/C][C]0.76037469928726[/C][C]0.61981265035637[/C][/ROW]
[ROW][C]188[/C][C]0.360783503694466[/C][C]0.721567007388932[/C][C]0.639216496305534[/C][/ROW]
[ROW][C]189[/C][C]0.329207758325749[/C][C]0.658415516651498[/C][C]0.670792241674251[/C][/ROW]
[ROW][C]190[/C][C]0.298142918428071[/C][C]0.596285836856142[/C][C]0.701857081571929[/C][/ROW]
[ROW][C]191[/C][C]0.260188234730926[/C][C]0.520376469461852[/C][C]0.739811765269074[/C][/ROW]
[ROW][C]192[/C][C]0.226187324594889[/C][C]0.452374649189778[/C][C]0.773812675405111[/C][/ROW]
[ROW][C]193[/C][C]0.199183663314681[/C][C]0.398367326629363[/C][C]0.800816336685319[/C][/ROW]
[ROW][C]194[/C][C]0.21218782981907[/C][C]0.42437565963814[/C][C]0.78781217018093[/C][/ROW]
[ROW][C]195[/C][C]0.179141220458046[/C][C]0.358282440916091[/C][C]0.820858779541954[/C][/ROW]
[ROW][C]196[/C][C]0.152964027683691[/C][C]0.305928055367382[/C][C]0.847035972316309[/C][/ROW]
[ROW][C]197[/C][C]0.129433696203453[/C][C]0.258867392406905[/C][C]0.870566303796547[/C][/ROW]
[ROW][C]198[/C][C]0.146202742556766[/C][C]0.292405485113531[/C][C]0.853797257443234[/C][/ROW]
[ROW][C]199[/C][C]0.193568445552296[/C][C]0.387136891104592[/C][C]0.806431554447704[/C][/ROW]
[ROW][C]200[/C][C]0.175183701139143[/C][C]0.350367402278285[/C][C]0.824816298860857[/C][/ROW]
[ROW][C]201[/C][C]0.693656127364241[/C][C]0.612687745271518[/C][C]0.306343872635759[/C][/ROW]
[ROW][C]202[/C][C]0.664739892597503[/C][C]0.670520214804994[/C][C]0.335260107402497[/C][/ROW]
[ROW][C]203[/C][C]0.613906341416478[/C][C]0.772187317167044[/C][C]0.386093658583522[/C][/ROW]
[ROW][C]204[/C][C]0.580161422308515[/C][C]0.83967715538297[/C][C]0.419838577691485[/C][/ROW]
[ROW][C]205[/C][C]0.531764180113254[/C][C]0.936471639773493[/C][C]0.468235819886746[/C][/ROW]
[ROW][C]206[/C][C]0.487710961809112[/C][C]0.975421923618224[/C][C]0.512289038190888[/C][/ROW]
[ROW][C]207[/C][C]0.432043899768086[/C][C]0.864087799536171[/C][C]0.567956100231914[/C][/ROW]
[ROW][C]208[/C][C]0.428917849809974[/C][C]0.857835699619949[/C][C]0.571082150190026[/C][/ROW]
[ROW][C]209[/C][C]0.394924027354985[/C][C]0.78984805470997[/C][C]0.605075972645015[/C][/ROW]
[ROW][C]210[/C][C]0.355464445369139[/C][C]0.710928890738278[/C][C]0.644535554630861[/C][/ROW]
[ROW][C]211[/C][C]0.302789692791238[/C][C]0.605579385582475[/C][C]0.697210307208762[/C][/ROW]
[ROW][C]212[/C][C]0.266295286640805[/C][C]0.532590573281609[/C][C]0.733704713359195[/C][/ROW]
[ROW][C]213[/C][C]0.310402716046266[/C][C]0.620805432092532[/C][C]0.689597283953734[/C][/ROW]
[ROW][C]214[/C][C]0.258553099101508[/C][C]0.517106198203016[/C][C]0.741446900898492[/C][/ROW]
[ROW][C]215[/C][C]0.208824077875674[/C][C]0.417648155751349[/C][C]0.791175922124326[/C][/ROW]
[ROW][C]216[/C][C]0.191623870942681[/C][C]0.383247741885361[/C][C]0.808376129057319[/C][/ROW]
[ROW][C]217[/C][C]0.163001383784177[/C][C]0.326002767568354[/C][C]0.836998616215823[/C][/ROW]
[ROW][C]218[/C][C]0.12431431882756[/C][C]0.24862863765512[/C][C]0.87568568117244[/C][/ROW]
[ROW][C]219[/C][C]0.0944354137877301[/C][C]0.18887082757546[/C][C]0.90556458621227[/C][/ROW]
[ROW][C]220[/C][C]0.0680191742541533[/C][C]0.136038348508307[/C][C]0.931980825745847[/C][/ROW]
[ROW][C]221[/C][C]0.126716598723981[/C][C]0.253433197447963[/C][C]0.873283401276019[/C][/ROW]
[ROW][C]222[/C][C]0.0997201877233813[/C][C]0.199440375446763[/C][C]0.900279812276619[/C][/ROW]
[ROW][C]223[/C][C]0.0776247018791352[/C][C]0.15524940375827[/C][C]0.922375298120865[/C][/ROW]
[ROW][C]224[/C][C]0.0518596318640386[/C][C]0.103719263728077[/C][C]0.948140368135961[/C][/ROW]
[ROW][C]225[/C][C]0.179244885151676[/C][C]0.358489770303352[/C][C]0.820755114848324[/C][/ROW]
[ROW][C]226[/C][C]0.134266740448975[/C][C]0.268533480897949[/C][C]0.865733259551025[/C][/ROW]
[ROW][C]227[/C][C]0.102828686359718[/C][C]0.205657372719437[/C][C]0.897171313640282[/C][/ROW]
[ROW][C]228[/C][C]0.0644874699283633[/C][C]0.128974939856727[/C][C]0.935512530071637[/C][/ROW]
[ROW][C]229[/C][C]0.0381525923074449[/C][C]0.0763051846148898[/C][C]0.961847407692555[/C][/ROW]
[ROW][C]230[/C][C]0.0201513229537305[/C][C]0.0403026459074611[/C][C]0.979848677046269[/C][/ROW]
[ROW][C]231[/C][C]0.0105340914706552[/C][C]0.0210681829413105[/C][C]0.989465908529345[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147113&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147113&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-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.002536111038321270.005072222076642550.997463888961679
100.0002947808749228650.000589561749845730.999705219125077
114.61634447457135e-059.23268894914269e-050.999953836555254
128.26358221532064e-061.65271644306413e-050.999991736417785
135.12657708080341e-050.0001025315416160680.999948734229192
141.76682927169551e-053.53365854339101e-050.999982331707283
153.10140521981403e-066.20281043962806e-060.99999689859478
162.06623695981552e-064.13247391963105e-060.99999793376304
173.76422620230122e-077.52845240460244e-070.99999962357738
186.61690348668505e-081.32338069733701e-070.999999933830965
192.13324579522426e-084.26649159044851e-080.999999978667542
203.06021960146136e-076.12043920292272e-070.99999969397804
219.86638790828989e-081.97327758165798e-070.999999901336121
226.09774347846367e-081.21954869569273e-070.999999939022565
232.15053340046003e-084.30106680092005e-080.999999978494666
245.28682275828303e-091.05736455165661e-080.999999994713177
251.24429460507007e-092.48858921014015e-090.999999998755705
264.00244242272758e-108.00488484545516e-100.999999999599756
279.11726040475746e-111.82345208095149e-100.999999999908827
281.97876873925882e-113.95753747851764e-110.999999999980212
294.38965743729097e-128.77931487458193e-120.99999999999561
301.99005980223055e-123.98011960446111e-120.99999999999801
314.26928763366473e-138.53857526732945e-130.999999999999573
321.72224611124712e-133.44449222249425e-130.999999999999828
330.002748359356972990.005496718713945980.997251640643027
340.001747654107699920.003495308215399840.9982523458923
350.001140003604266720.002280007208533450.998859996395733
360.0006886578567459140.001377315713491830.999311342143254
370.0004463965131631330.0008927930263262670.999553603486837
380.0002752374572698870.0005504749145397730.99972476254273
390.8995444444601170.2009111110797660.100455555539883
400.8846737060979560.2306525878040890.115326293902044
410.8621667872812870.2756664254374250.137833212718713
420.8347424859841450.330515028031710.165257514015855
430.8028584488204290.3942831023591410.197141551179571
440.7677579728374730.4644840543250550.232242027162527
450.9415817918710010.1168364162579980.0584182081289989
460.9298162587374150.140367482525170.0701837412625848
470.9182173944196850.1635652111606290.0817826055803147
480.9144376592714380.1711246814571240.0855623407285621
490.8959899285927920.2080201428144160.104010071407208
500.8833536365490070.2332927269019870.116646363450993
510.8594113165502790.2811773668994420.140588683449721
520.8356938981873540.3286122036252920.164306101812646
530.8071838091682280.3856323816635440.192816190831772
540.7764795128320880.4470409743358240.223520487167912
550.7421247544978830.5157504910042330.257875245502117
560.7054352855929420.5891294288141150.294564714407058
570.9998852162044280.0002295675911430040.000114783795571502
580.9999020262945980.0001959474108039079.79737054019535e-05
590.9998526835587630.0002946328824734230.000147316441236712
600.999841962484060.0003160750318808080.000158037515940404
610.999790350437680.0004192991246393710.000209649562319686
620.9997133585860360.0005732828279269210.000286641413963461
630.999637314475130.000725371049740310.000362685524870155
640.9995117085506180.0009765828987635750.000488291449381787
650.9996116082162050.0007767835675906760.000388391783795338
660.9995966214082480.0008067571835040620.000403378591752031
670.9994583677750220.001083264449955560.00054163222497778
680.9993182971752380.001363405649523510.000681702824761754
690.9999994023080961.19538380823799e-065.97691904118993e-07
700.9999990734001111.85319977880458e-069.2659988940229e-07
710.999998497374633.00525074058373e-061.50262537029187e-06
720.999997612447214.77510557910933e-062.38755278955466e-06
730.9999990201693061.95966138791697e-069.79830693958483e-07
740.9999984423507623.11529847612091e-061.55764923806045e-06
750.9999979539839614.09203207763146e-062.04601603881573e-06
760.9999972481649665.50367006702455e-062.75183503351228e-06
770.9999956507983158.69840337033962e-064.34920168516981e-06
780.999996957899046.08420192023415e-063.04210096011708e-06
790.9999958056302078.38873958598725e-064.19436979299362e-06
800.9999943163652711.13672694585578e-055.68363472927888e-06
810.9999975095214414.98095711766516e-062.49047855883258e-06
820.9999961753308247.64933835279075e-063.82466917639538e-06
830.9999955821799048.83564019116946e-064.41782009558473e-06
840.9999935986582561.28026834877772e-056.40134174388861e-06
850.9999917568120411.64863759181441e-058.24318795907205e-06
860.999988498964892.30020702201271e-051.15010351100635e-05
870.9999850182016892.99635966219106e-051.49817983109553e-05
880.9999810289612963.79420774077633e-051.89710387038817e-05
890.9999831556790333.36886419342385e-051.68443209671193e-05
900.9999783480481634.33039036735304e-052.16519518367652e-05
910.9999692309586576.15380826869914e-053.07690413434957e-05
920.9999555238399298.89523201418757e-054.44761600709378e-05
930.9999633020311117.33959377782362e-053.66979688891181e-05
940.9999559276487798.81447024418704e-054.40723512209352e-05
950.999952994490319.40110193805852e-054.70055096902926e-05
960.9999312381836040.0001375236327929396.87618163964696e-05
970.999901020064590.0001979598708196719.89799354098355e-05
980.9998775995488090.0002448009023824310.000122400451191215
990.9998662730029250.0002674539941509620.000133726997075481
1000.9998234015459730.0003531969080548170.000176598454027408
1010.9997917955955760.0004164088088479770.000208204404423988
1020.9997118669215960.0005762661568084730.000288133078404236
1030.9996023601949140.0007952796101710670.000397639805085534
1040.9996542628027170.0006914743945666980.000345737197283349
1050.9996221096553370.0007557806893260530.000377890344663027
1060.9996081472609310.0007837054781380130.000391852739069006
1070.9995574463579230.0008851072841534570.000442553642076729
1080.9994995461823410.001000907635317450.000500453817658727
1090.9993085154315780.00138296913684380.000691484568421902
1100.9990679274946410.001864145010718770.000932072505359387
1110.9988336889701930.002332622059614580.00116631102980729
1120.9984127501187580.003174499762483330.00158724988124166
1130.9981518712956780.003696257408643980.00184812870432199
1140.9980047852079460.003990429584108640.00199521479205432
1150.9973805873840860.005238825231827750.00261941261591387
1160.9974769909844190.00504601803116110.00252300901558055
1170.9990773849399770.001845230120046110.000922615060023055
1180.998780019254470.00243996149106080.0012199807455304
1190.9983416561382430.003316687723513010.00165834386175651
1200.9979143359598960.004171328080208020.00208566404010401
1210.9976512695689890.004697460862021240.00234873043101062
1220.9969627476489840.006074504702032240.00303725235101612
1230.9959886506416080.008022698716784960.00401134935839248
1240.9949531744177490.01009365116450290.00504682558225147
1250.9938115499076270.01237690018474660.00618845009237331
1260.9920541745032830.01589165099343320.00794582549671662
1270.989764031420920.0204719371581610.0102359685790805
1280.9877486457581240.02450270848375250.0122513542418762
1290.9846405595390030.03071888092199310.0153594404609965
1300.9806982719086820.03860345618263570.0193017280913178
1310.9763873904015250.04722521919694910.0236126095984746
1320.9727572277637990.05448554447240290.0272427722362014
1330.967914163799160.06417167240168090.0320858362008405
1340.9606428348857380.07871433022852350.0393571651142618
1350.9543493122624710.09130137547505870.0456506877375293
1360.9446832412644450.110633517471110.0553167587355552
1370.936272215335240.1274555693295210.0637277846647604
1380.931042559629030.1379148807419410.0689574403709703
1390.9175383215459950.1649233569080090.0824616784540046
1400.9047446701580080.1905106596839830.0952553298419917
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1500.9398118326699470.1203763346601070.0601881673300535
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1600.8821484347551280.2357031304897430.117851565244872
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1800.598559179021410.8028816419571810.40144082097859
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1890.3292077583257490.6584155166514980.670792241674251
1900.2981429184280710.5962858368561420.701857081571929
1910.2601882347309260.5203764694618520.739811765269074
1920.2261873245948890.4523746491897780.773812675405111
1930.1991836633146810.3983673266293630.800816336685319
1940.212187829819070.424375659638140.78781217018093
1950.1791412204580460.3582824409160910.820858779541954
1960.1529640276836910.3059280553673820.847035972316309
1970.1294336962034530.2588673924069050.870566303796547
1980.1462027425567660.2924054851135310.853797257443234
1990.1935684455522960.3871368911045920.806431554447704
2000.1751837011391430.3503674022782850.824816298860857
2010.6936561273642410.6126877452715180.306343872635759
2020.6647398925975030.6705202148049940.335260107402497
2030.6139063414164780.7721873171670440.386093658583522
2040.5801614223085150.839677155382970.419838577691485
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2080.4289178498099740.8578356996199490.571082150190026
2090.3949240273549850.789848054709970.605075972645015
2100.3554644453691390.7109288907382780.644535554630861
2110.3027896927912380.6055793855824750.697210307208762
2120.2662952866408050.5325905732816090.733704713359195
2130.3104027160462660.6208054320925320.689597283953734
2140.2585530991015080.5171061982030160.741446900898492
2150.2088240778756740.4176481557513490.791175922124326
2160.1916238709426810.3832477418853610.808376129057319
2170.1630013837841770.3260027675683540.836998616215823
2180.124314318827560.248628637655120.87568568117244
2190.09443541378773010.188870827575460.90556458621227
2200.06801917425415330.1360383485083070.931980825745847
2210.1267165987239810.2534331974479630.873283401276019
2220.09972018772338130.1994403754467630.900279812276619
2230.07762470187913520.155249403758270.922375298120865
2240.05185963186403860.1037192637280770.948140368135961
2250.1792448851516760.3584897703033520.820755114848324
2260.1342667404489750.2685334808979490.865733259551025
2270.1028286863597180.2056573727194370.897171313640282
2280.06448746992836330.1289749398567270.935512530071637
2290.03815259230744490.07630518461488980.961847407692555
2300.02015132295373050.04030264590746110.979848677046269
2310.01053409147065520.02106818294131050.989465908529345







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level970.434977578475336NOK
5% type I error level1120.502242152466368NOK
10% type I error level1210.542600896860987NOK

\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 & 97 & 0.434977578475336 & NOK \tabularnewline
5% type I error level & 112 & 0.502242152466368 & NOK \tabularnewline
10% type I error level & 121 & 0.542600896860987 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147113&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]97[/C][C]0.434977578475336[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]112[/C][C]0.502242152466368[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]121[/C][C]0.542600896860987[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147113&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147113&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 testsOK/NOK
1% type I error level970.434977578475336NOK
5% type I error level1120.502242152466368NOK
10% type I error level1210.542600896860987NOK



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}