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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 20 May 2012 07:17:59 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/20/t1337512749rh7rtl24xhj52tx.htm/, Retrieved Tue, 30 Apr 2024 02:10:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166779, Retrieved Tue, 30 Apr 2024 02:10:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact115

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [] [2011-10-24 11:50:03] [c804c9d9debe6cbacd66d26bebf6dd2f]
- RMP   [(Partial) Autocorrelation Function] [] [2012-05-20 11:06:17] [314c90c95929b793e8a10c15bae12703]
-    D    [(Partial) Autocorrelation Function] [] [2012-05-20 11:13:59] [314c90c95929b793e8a10c15bae12703]
- R PD        [(Partial) Autocorrelation Function] [] [2012-05-20 11:17:59] [21ca38b5c207d9fbe3078e977c625188] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
31.1
31.8
32.5
34.4
35.5
35.5
36.6
37.1
37.9
38.1
39
41.5
41.8
41.9
44.6
46.1
46.4
47.2
47.7
49.2
49.3
49.3
49.5
50.1
51.9
52.6
53.2
53.5
53.7
53.7
53.9
54.1
54.8
55.4
55.9
56.8
58.4
59.3
60.3
60.5
60.8
61
61.1
61.3
61.4
61.5
63.9
63.9
64
64.1
64.5
64.5
65.9
66.8
68.7
69.2
69.6
70.2
70.6
70.7
70.7
71
72.1
73.7
77.4
79.7
91.6
93.6
94.3
97.3
101.7
103
103.1
104.6
107.2
107.7
108.3
108.8
113.1
113.8
113.8
116.5
116.9
117.6

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166779&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166779&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166779&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2072971.88860.031222
20.1187141.08150.141296
30.2251662.05140.021693
40.2709752.46870.007806
50.0323080.29430.384615
6-0.099904-0.91020.182684
70.0025490.02320.490763
80.1472091.34110.091767
9-0.026964-0.24570.403279
10-0.036653-0.33390.369639
110.0101270.09230.463357
120.250382.28110.012553
13-0.017531-0.15970.436747
14-0.000343-0.00310.498757
150.0306850.27960.390257
16-0.038071-0.34680.364792
17-0.040385-0.36790.356934
18-0.035704-0.32530.372894
19-0.06841-0.62320.267416
200.0624680.56910.28541
21-0.041918-0.38190.351759
22-0.059601-0.5430.294295
23-0.071359-0.65010.258707
24-0.024139-0.21990.413239
25-0.080716-0.73540.232098
26-0.065382-0.59570.276511
27-0.043151-0.39310.347617
280.0051770.04720.481246
29-0.013636-0.12420.450718
30-0.000947-0.00860.49657
31-0.028268-0.25750.398701
320.0141170.12860.448987
33-0.046189-0.42080.337493
34-0.055271-0.50350.30796
35-0.031705-0.28880.38671
36-0.097787-0.89090.187784
37-0.096414-0.87840.191138
38-0.050217-0.45750.324256
39-0.065183-0.59380.277114
40-0.025584-0.23310.408136
41-0.052499-0.47830.316851
420.0177640.16180.435913
43-0.030817-0.28080.389797
44-0.092126-0.83930.201854
45-0.076083-0.69310.245076
46-0.0564-0.51380.304369
47-0.01826-0.16640.434141
48-0.069746-0.63540.263452

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.207297 & 1.8886 & 0.031222 \tabularnewline
2 & 0.118714 & 1.0815 & 0.141296 \tabularnewline
3 & 0.225166 & 2.0514 & 0.021693 \tabularnewline
4 & 0.270975 & 2.4687 & 0.007806 \tabularnewline
5 & 0.032308 & 0.2943 & 0.384615 \tabularnewline
6 & -0.099904 & -0.9102 & 0.182684 \tabularnewline
7 & 0.002549 & 0.0232 & 0.490763 \tabularnewline
8 & 0.147209 & 1.3411 & 0.091767 \tabularnewline
9 & -0.026964 & -0.2457 & 0.403279 \tabularnewline
10 & -0.036653 & -0.3339 & 0.369639 \tabularnewline
11 & 0.010127 & 0.0923 & 0.463357 \tabularnewline
12 & 0.25038 & 2.2811 & 0.012553 \tabularnewline
13 & -0.017531 & -0.1597 & 0.436747 \tabularnewline
14 & -0.000343 & -0.0031 & 0.498757 \tabularnewline
15 & 0.030685 & 0.2796 & 0.390257 \tabularnewline
16 & -0.038071 & -0.3468 & 0.364792 \tabularnewline
17 & -0.040385 & -0.3679 & 0.356934 \tabularnewline
18 & -0.035704 & -0.3253 & 0.372894 \tabularnewline
19 & -0.06841 & -0.6232 & 0.267416 \tabularnewline
20 & 0.062468 & 0.5691 & 0.28541 \tabularnewline
21 & -0.041918 & -0.3819 & 0.351759 \tabularnewline
22 & -0.059601 & -0.543 & 0.294295 \tabularnewline
23 & -0.071359 & -0.6501 & 0.258707 \tabularnewline
24 & -0.024139 & -0.2199 & 0.413239 \tabularnewline
25 & -0.080716 & -0.7354 & 0.232098 \tabularnewline
26 & -0.065382 & -0.5957 & 0.276511 \tabularnewline
27 & -0.043151 & -0.3931 & 0.347617 \tabularnewline
28 & 0.005177 & 0.0472 & 0.481246 \tabularnewline
29 & -0.013636 & -0.1242 & 0.450718 \tabularnewline
30 & -0.000947 & -0.0086 & 0.49657 \tabularnewline
31 & -0.028268 & -0.2575 & 0.398701 \tabularnewline
32 & 0.014117 & 0.1286 & 0.448987 \tabularnewline
33 & -0.046189 & -0.4208 & 0.337493 \tabularnewline
34 & -0.055271 & -0.5035 & 0.30796 \tabularnewline
35 & -0.031705 & -0.2888 & 0.38671 \tabularnewline
36 & -0.097787 & -0.8909 & 0.187784 \tabularnewline
37 & -0.096414 & -0.8784 & 0.191138 \tabularnewline
38 & -0.050217 & -0.4575 & 0.324256 \tabularnewline
39 & -0.065183 & -0.5938 & 0.277114 \tabularnewline
40 & -0.025584 & -0.2331 & 0.408136 \tabularnewline
41 & -0.052499 & -0.4783 & 0.316851 \tabularnewline
42 & 0.017764 & 0.1618 & 0.435913 \tabularnewline
43 & -0.030817 & -0.2808 & 0.389797 \tabularnewline
44 & -0.092126 & -0.8393 & 0.201854 \tabularnewline
45 & -0.076083 & -0.6931 & 0.245076 \tabularnewline
46 & -0.0564 & -0.5138 & 0.304369 \tabularnewline
47 & -0.01826 & -0.1664 & 0.434141 \tabularnewline
48 & -0.069746 & -0.6354 & 0.263452 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166779&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.207297[/C][C]1.8886[/C][C]0.031222[/C][/ROW]
[ROW][C]2[/C][C]0.118714[/C][C]1.0815[/C][C]0.141296[/C][/ROW]
[ROW][C]3[/C][C]0.225166[/C][C]2.0514[/C][C]0.021693[/C][/ROW]
[ROW][C]4[/C][C]0.270975[/C][C]2.4687[/C][C]0.007806[/C][/ROW]
[ROW][C]5[/C][C]0.032308[/C][C]0.2943[/C][C]0.384615[/C][/ROW]
[ROW][C]6[/C][C]-0.099904[/C][C]-0.9102[/C][C]0.182684[/C][/ROW]
[ROW][C]7[/C][C]0.002549[/C][C]0.0232[/C][C]0.490763[/C][/ROW]
[ROW][C]8[/C][C]0.147209[/C][C]1.3411[/C][C]0.091767[/C][/ROW]
[ROW][C]9[/C][C]-0.026964[/C][C]-0.2457[/C][C]0.403279[/C][/ROW]
[ROW][C]10[/C][C]-0.036653[/C][C]-0.3339[/C][C]0.369639[/C][/ROW]
[ROW][C]11[/C][C]0.010127[/C][C]0.0923[/C][C]0.463357[/C][/ROW]
[ROW][C]12[/C][C]0.25038[/C][C]2.2811[/C][C]0.012553[/C][/ROW]
[ROW][C]13[/C][C]-0.017531[/C][C]-0.1597[/C][C]0.436747[/C][/ROW]
[ROW][C]14[/C][C]-0.000343[/C][C]-0.0031[/C][C]0.498757[/C][/ROW]
[ROW][C]15[/C][C]0.030685[/C][C]0.2796[/C][C]0.390257[/C][/ROW]
[ROW][C]16[/C][C]-0.038071[/C][C]-0.3468[/C][C]0.364792[/C][/ROW]
[ROW][C]17[/C][C]-0.040385[/C][C]-0.3679[/C][C]0.356934[/C][/ROW]
[ROW][C]18[/C][C]-0.035704[/C][C]-0.3253[/C][C]0.372894[/C][/ROW]
[ROW][C]19[/C][C]-0.06841[/C][C]-0.6232[/C][C]0.267416[/C][/ROW]
[ROW][C]20[/C][C]0.062468[/C][C]0.5691[/C][C]0.28541[/C][/ROW]
[ROW][C]21[/C][C]-0.041918[/C][C]-0.3819[/C][C]0.351759[/C][/ROW]
[ROW][C]22[/C][C]-0.059601[/C][C]-0.543[/C][C]0.294295[/C][/ROW]
[ROW][C]23[/C][C]-0.071359[/C][C]-0.6501[/C][C]0.258707[/C][/ROW]
[ROW][C]24[/C][C]-0.024139[/C][C]-0.2199[/C][C]0.413239[/C][/ROW]
[ROW][C]25[/C][C]-0.080716[/C][C]-0.7354[/C][C]0.232098[/C][/ROW]
[ROW][C]26[/C][C]-0.065382[/C][C]-0.5957[/C][C]0.276511[/C][/ROW]
[ROW][C]27[/C][C]-0.043151[/C][C]-0.3931[/C][C]0.347617[/C][/ROW]
[ROW][C]28[/C][C]0.005177[/C][C]0.0472[/C][C]0.481246[/C][/ROW]
[ROW][C]29[/C][C]-0.013636[/C][C]-0.1242[/C][C]0.450718[/C][/ROW]
[ROW][C]30[/C][C]-0.000947[/C][C]-0.0086[/C][C]0.49657[/C][/ROW]
[ROW][C]31[/C][C]-0.028268[/C][C]-0.2575[/C][C]0.398701[/C][/ROW]
[ROW][C]32[/C][C]0.014117[/C][C]0.1286[/C][C]0.448987[/C][/ROW]
[ROW][C]33[/C][C]-0.046189[/C][C]-0.4208[/C][C]0.337493[/C][/ROW]
[ROW][C]34[/C][C]-0.055271[/C][C]-0.5035[/C][C]0.30796[/C][/ROW]
[ROW][C]35[/C][C]-0.031705[/C][C]-0.2888[/C][C]0.38671[/C][/ROW]
[ROW][C]36[/C][C]-0.097787[/C][C]-0.8909[/C][C]0.187784[/C][/ROW]
[ROW][C]37[/C][C]-0.096414[/C][C]-0.8784[/C][C]0.191138[/C][/ROW]
[ROW][C]38[/C][C]-0.050217[/C][C]-0.4575[/C][C]0.324256[/C][/ROW]
[ROW][C]39[/C][C]-0.065183[/C][C]-0.5938[/C][C]0.277114[/C][/ROW]
[ROW][C]40[/C][C]-0.025584[/C][C]-0.2331[/C][C]0.408136[/C][/ROW]
[ROW][C]41[/C][C]-0.052499[/C][C]-0.4783[/C][C]0.316851[/C][/ROW]
[ROW][C]42[/C][C]0.017764[/C][C]0.1618[/C][C]0.435913[/C][/ROW]
[ROW][C]43[/C][C]-0.030817[/C][C]-0.2808[/C][C]0.389797[/C][/ROW]
[ROW][C]44[/C][C]-0.092126[/C][C]-0.8393[/C][C]0.201854[/C][/ROW]
[ROW][C]45[/C][C]-0.076083[/C][C]-0.6931[/C][C]0.245076[/C][/ROW]
[ROW][C]46[/C][C]-0.0564[/C][C]-0.5138[/C][C]0.304369[/C][/ROW]
[ROW][C]47[/C][C]-0.01826[/C][C]-0.1664[/C][C]0.434141[/C][/ROW]
[ROW][C]48[/C][C]-0.069746[/C][C]-0.6354[/C][C]0.263452[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166779&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166779&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2072971.88860.031222
20.1187141.08150.141296
30.2251662.05140.021693
40.2709752.46870.007806
50.0323080.29430.384615
6-0.099904-0.91020.182684
70.0025490.02320.490763
80.1472091.34110.091767
9-0.026964-0.24570.403279
10-0.036653-0.33390.369639
110.0101270.09230.463357
120.250382.28110.012553
13-0.017531-0.15970.436747
14-0.000343-0.00310.498757
150.0306850.27960.390257
16-0.038071-0.34680.364792
17-0.040385-0.36790.356934
18-0.035704-0.32530.372894
19-0.06841-0.62320.267416
200.0624680.56910.28541
21-0.041918-0.38190.351759
22-0.059601-0.5430.294295
23-0.071359-0.65010.258707
24-0.024139-0.21990.413239
25-0.080716-0.73540.232098
26-0.065382-0.59570.276511
27-0.043151-0.39310.347617
280.0051770.04720.481246
29-0.013636-0.12420.450718
30-0.000947-0.00860.49657
31-0.028268-0.25750.398701
320.0141170.12860.448987
33-0.046189-0.42080.337493
34-0.055271-0.50350.30796
35-0.031705-0.28880.38671
36-0.097787-0.89090.187784
37-0.096414-0.87840.191138
38-0.050217-0.45750.324256
39-0.065183-0.59380.277114
40-0.025584-0.23310.408136
41-0.052499-0.47830.316851
420.0177640.16180.435913
43-0.030817-0.28080.389797
44-0.092126-0.83930.201854
45-0.076083-0.69310.245076
46-0.0564-0.51380.304369
47-0.01826-0.16640.434141
48-0.069746-0.63540.263452






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2072971.88860.031222
20.0791430.7210.236461
30.1956811.78270.039143
40.2033151.85230.03377
5-0.083348-0.75930.224901
6-0.186426-1.69840.046587
7-0.052371-0.47710.317265
80.1537421.40070.082522
90.0119760.10910.456689
100.0258430.23540.407222
11-0.042627-0.38840.349374
120.2094251.9080.029927
13-0.085884-0.78240.218092
140.0186930.17030.432594
15-0.064952-0.59170.277816
16-0.172275-1.56950.060169
170.0262570.23920.405766
180.0723080.65880.255939
19-0.008265-0.07530.47008
200.0845690.77050.221608
21-0.042359-0.38590.350275
22-0.102236-0.93140.17717
23-0.074872-0.68210.248531
24-0.064385-0.58660.279542
25-0.012608-0.11490.454414
260.0211480.19270.423845
270.0437180.39830.345718
280.0963010.87730.191417
290.0035980.03280.486966
30-0.011656-0.10620.457845
31-0.049843-0.45410.325473
32-0.108148-0.98530.163677
33-0.04892-0.44570.328492
340.0036820.03350.48666
350.0546980.49830.309787
36-0.025936-0.23630.406895
37-0.01371-0.12490.45045
38-0.0256-0.23320.40808
39-0.049368-0.44980.327027
40-0.01878-0.17110.432284
41-0.04256-0.38770.349601
420.0310920.28330.38884
43-0.015817-0.14410.442887
44-0.056004-0.51020.305626
45-0.03052-0.27810.390832
46-0.034978-0.31870.375392
470.035420.32270.373871
480.004560.04150.483481

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.207297 & 1.8886 & 0.031222 \tabularnewline
2 & 0.079143 & 0.721 & 0.236461 \tabularnewline
3 & 0.195681 & 1.7827 & 0.039143 \tabularnewline
4 & 0.203315 & 1.8523 & 0.03377 \tabularnewline
5 & -0.083348 & -0.7593 & 0.224901 \tabularnewline
6 & -0.186426 & -1.6984 & 0.046587 \tabularnewline
7 & -0.052371 & -0.4771 & 0.317265 \tabularnewline
8 & 0.153742 & 1.4007 & 0.082522 \tabularnewline
9 & 0.011976 & 0.1091 & 0.456689 \tabularnewline
10 & 0.025843 & 0.2354 & 0.407222 \tabularnewline
11 & -0.042627 & -0.3884 & 0.349374 \tabularnewline
12 & 0.209425 & 1.908 & 0.029927 \tabularnewline
13 & -0.085884 & -0.7824 & 0.218092 \tabularnewline
14 & 0.018693 & 0.1703 & 0.432594 \tabularnewline
15 & -0.064952 & -0.5917 & 0.277816 \tabularnewline
16 & -0.172275 & -1.5695 & 0.060169 \tabularnewline
17 & 0.026257 & 0.2392 & 0.405766 \tabularnewline
18 & 0.072308 & 0.6588 & 0.255939 \tabularnewline
19 & -0.008265 & -0.0753 & 0.47008 \tabularnewline
20 & 0.084569 & 0.7705 & 0.221608 \tabularnewline
21 & -0.042359 & -0.3859 & 0.350275 \tabularnewline
22 & -0.102236 & -0.9314 & 0.17717 \tabularnewline
23 & -0.074872 & -0.6821 & 0.248531 \tabularnewline
24 & -0.064385 & -0.5866 & 0.279542 \tabularnewline
25 & -0.012608 & -0.1149 & 0.454414 \tabularnewline
26 & 0.021148 & 0.1927 & 0.423845 \tabularnewline
27 & 0.043718 & 0.3983 & 0.345718 \tabularnewline
28 & 0.096301 & 0.8773 & 0.191417 \tabularnewline
29 & 0.003598 & 0.0328 & 0.486966 \tabularnewline
30 & -0.011656 & -0.1062 & 0.457845 \tabularnewline
31 & -0.049843 & -0.4541 & 0.325473 \tabularnewline
32 & -0.108148 & -0.9853 & 0.163677 \tabularnewline
33 & -0.04892 & -0.4457 & 0.328492 \tabularnewline
34 & 0.003682 & 0.0335 & 0.48666 \tabularnewline
35 & 0.054698 & 0.4983 & 0.309787 \tabularnewline
36 & -0.025936 & -0.2363 & 0.406895 \tabularnewline
37 & -0.01371 & -0.1249 & 0.45045 \tabularnewline
38 & -0.0256 & -0.2332 & 0.40808 \tabularnewline
39 & -0.049368 & -0.4498 & 0.327027 \tabularnewline
40 & -0.01878 & -0.1711 & 0.432284 \tabularnewline
41 & -0.04256 & -0.3877 & 0.349601 \tabularnewline
42 & 0.031092 & 0.2833 & 0.38884 \tabularnewline
43 & -0.015817 & -0.1441 & 0.442887 \tabularnewline
44 & -0.056004 & -0.5102 & 0.305626 \tabularnewline
45 & -0.03052 & -0.2781 & 0.390832 \tabularnewline
46 & -0.034978 & -0.3187 & 0.375392 \tabularnewline
47 & 0.03542 & 0.3227 & 0.373871 \tabularnewline
48 & 0.00456 & 0.0415 & 0.483481 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166779&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.207297[/C][C]1.8886[/C][C]0.031222[/C][/ROW]
[ROW][C]2[/C][C]0.079143[/C][C]0.721[/C][C]0.236461[/C][/ROW]
[ROW][C]3[/C][C]0.195681[/C][C]1.7827[/C][C]0.039143[/C][/ROW]
[ROW][C]4[/C][C]0.203315[/C][C]1.8523[/C][C]0.03377[/C][/ROW]
[ROW][C]5[/C][C]-0.083348[/C][C]-0.7593[/C][C]0.224901[/C][/ROW]
[ROW][C]6[/C][C]-0.186426[/C][C]-1.6984[/C][C]0.046587[/C][/ROW]
[ROW][C]7[/C][C]-0.052371[/C][C]-0.4771[/C][C]0.317265[/C][/ROW]
[ROW][C]8[/C][C]0.153742[/C][C]1.4007[/C][C]0.082522[/C][/ROW]
[ROW][C]9[/C][C]0.011976[/C][C]0.1091[/C][C]0.456689[/C][/ROW]
[ROW][C]10[/C][C]0.025843[/C][C]0.2354[/C][C]0.407222[/C][/ROW]
[ROW][C]11[/C][C]-0.042627[/C][C]-0.3884[/C][C]0.349374[/C][/ROW]
[ROW][C]12[/C][C]0.209425[/C][C]1.908[/C][C]0.029927[/C][/ROW]
[ROW][C]13[/C][C]-0.085884[/C][C]-0.7824[/C][C]0.218092[/C][/ROW]
[ROW][C]14[/C][C]0.018693[/C][C]0.1703[/C][C]0.432594[/C][/ROW]
[ROW][C]15[/C][C]-0.064952[/C][C]-0.5917[/C][C]0.277816[/C][/ROW]
[ROW][C]16[/C][C]-0.172275[/C][C]-1.5695[/C][C]0.060169[/C][/ROW]
[ROW][C]17[/C][C]0.026257[/C][C]0.2392[/C][C]0.405766[/C][/ROW]
[ROW][C]18[/C][C]0.072308[/C][C]0.6588[/C][C]0.255939[/C][/ROW]
[ROW][C]19[/C][C]-0.008265[/C][C]-0.0753[/C][C]0.47008[/C][/ROW]
[ROW][C]20[/C][C]0.084569[/C][C]0.7705[/C][C]0.221608[/C][/ROW]
[ROW][C]21[/C][C]-0.042359[/C][C]-0.3859[/C][C]0.350275[/C][/ROW]
[ROW][C]22[/C][C]-0.102236[/C][C]-0.9314[/C][C]0.17717[/C][/ROW]
[ROW][C]23[/C][C]-0.074872[/C][C]-0.6821[/C][C]0.248531[/C][/ROW]
[ROW][C]24[/C][C]-0.064385[/C][C]-0.5866[/C][C]0.279542[/C][/ROW]
[ROW][C]25[/C][C]-0.012608[/C][C]-0.1149[/C][C]0.454414[/C][/ROW]
[ROW][C]26[/C][C]0.021148[/C][C]0.1927[/C][C]0.423845[/C][/ROW]
[ROW][C]27[/C][C]0.043718[/C][C]0.3983[/C][C]0.345718[/C][/ROW]
[ROW][C]28[/C][C]0.096301[/C][C]0.8773[/C][C]0.191417[/C][/ROW]
[ROW][C]29[/C][C]0.003598[/C][C]0.0328[/C][C]0.486966[/C][/ROW]
[ROW][C]30[/C][C]-0.011656[/C][C]-0.1062[/C][C]0.457845[/C][/ROW]
[ROW][C]31[/C][C]-0.049843[/C][C]-0.4541[/C][C]0.325473[/C][/ROW]
[ROW][C]32[/C][C]-0.108148[/C][C]-0.9853[/C][C]0.163677[/C][/ROW]
[ROW][C]33[/C][C]-0.04892[/C][C]-0.4457[/C][C]0.328492[/C][/ROW]
[ROW][C]34[/C][C]0.003682[/C][C]0.0335[/C][C]0.48666[/C][/ROW]
[ROW][C]35[/C][C]0.054698[/C][C]0.4983[/C][C]0.309787[/C][/ROW]
[ROW][C]36[/C][C]-0.025936[/C][C]-0.2363[/C][C]0.406895[/C][/ROW]
[ROW][C]37[/C][C]-0.01371[/C][C]-0.1249[/C][C]0.45045[/C][/ROW]
[ROW][C]38[/C][C]-0.0256[/C][C]-0.2332[/C][C]0.40808[/C][/ROW]
[ROW][C]39[/C][C]-0.049368[/C][C]-0.4498[/C][C]0.327027[/C][/ROW]
[ROW][C]40[/C][C]-0.01878[/C][C]-0.1711[/C][C]0.432284[/C][/ROW]
[ROW][C]41[/C][C]-0.04256[/C][C]-0.3877[/C][C]0.349601[/C][/ROW]
[ROW][C]42[/C][C]0.031092[/C][C]0.2833[/C][C]0.38884[/C][/ROW]
[ROW][C]43[/C][C]-0.015817[/C][C]-0.1441[/C][C]0.442887[/C][/ROW]
[ROW][C]44[/C][C]-0.056004[/C][C]-0.5102[/C][C]0.305626[/C][/ROW]
[ROW][C]45[/C][C]-0.03052[/C][C]-0.2781[/C][C]0.390832[/C][/ROW]
[ROW][C]46[/C][C]-0.034978[/C][C]-0.3187[/C][C]0.375392[/C][/ROW]
[ROW][C]47[/C][C]0.03542[/C][C]0.3227[/C][C]0.373871[/C][/ROW]
[ROW][C]48[/C][C]0.00456[/C][C]0.0415[/C][C]0.483481[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166779&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166779&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2072971.88860.031222
20.0791430.7210.236461
30.1956811.78270.039143
40.2033151.85230.03377
5-0.083348-0.75930.224901
6-0.186426-1.69840.046587
7-0.052371-0.47710.317265
80.1537421.40070.082522
90.0119760.10910.456689
100.0258430.23540.407222
11-0.042627-0.38840.349374
120.2094251.9080.029927
13-0.085884-0.78240.218092
140.0186930.17030.432594
15-0.064952-0.59170.277816
16-0.172275-1.56950.060169
170.0262570.23920.405766
180.0723080.65880.255939
19-0.008265-0.07530.47008
200.0845690.77050.221608
21-0.042359-0.38590.350275
22-0.102236-0.93140.17717
23-0.074872-0.68210.248531
24-0.064385-0.58660.279542
25-0.012608-0.11490.454414
260.0211480.19270.423845
270.0437180.39830.345718
280.0963010.87730.191417
290.0035980.03280.486966
30-0.011656-0.10620.457845
31-0.049843-0.45410.325473
32-0.108148-0.98530.163677
33-0.04892-0.44570.328492
340.0036820.03350.48666
350.0546980.49830.309787
36-0.025936-0.23630.406895
37-0.01371-0.12490.45045
38-0.0256-0.23320.40808
39-0.049368-0.44980.327027
40-0.01878-0.17110.432284
41-0.04256-0.38770.349601
420.0310920.28330.38884
43-0.015817-0.14410.442887
44-0.056004-0.51020.305626
45-0.03052-0.27810.390832
46-0.034978-0.31870.375392
470.035420.32270.373871
480.004560.04150.483481


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')