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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 11 Dec 2010 11:23:05 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/11/t1292066473lfym9s8ezmnwqce.htm/, Retrieved Mon, 06 May 2024 22:23:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108064, Retrieved Mon, 06 May 2024 22:23:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [ACF interventie D=0] [2010-12-11 11:19:23] [04d4386fa51dbd2ef12d0f1f80644886]
-   PD    [(Partial) Autocorrelation Function] [ACF interventie D=1] [2010-12-11 11:23:05] [de8ccb310fbbdc3d90ae577a3e011cf9] [Current]
-   PD      [(Partial) Autocorrelation Function] [ACF aanvoer D=0] [2010-12-11 11:25:10] [04d4386fa51dbd2ef12d0f1f80644886]
-   PD        [(Partial) Autocorrelation Function] [ACF aanvoer D=1] [2010-12-11 11:26:57] [04d4386fa51dbd2ef12d0f1f80644886]
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Dataseries X:
16
29
22
30
20
39
18
9.6
10.2
20.2
50
120
19.8
18
3
11
15
27
28
14
5.6
6.5
8.5
87.9
5.8
25.2
7.5
13.7
34
17
9
9.2
5
24
40
86.5
0.54
14
4.8
28
16
5.8
16
9.1
6
17
26
99.6
41
72
23
42
40
18
45
18
2
10
13.6
160




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108064&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108064&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108064&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4342393.00850.002086
20.1424490.98690.164316
3-0.000884-0.00610.497569
4-0.029171-0.20210.420346
50.1924181.33310.094394
60.1488771.03140.15375
70.1484781.02870.154392
80.0805390.5580.289722
90.0405720.28110.389925
100.1573491.09010.140545
11-0.024364-0.16880.433333
12-0.160837-1.11430.135347
13-0.108189-0.74960.228591
140.0428960.29720.383802
150.1882141.3040.099229
160.1270910.88050.191484
170.0257590.17850.429556
18-0.05877-0.40720.342845
19-0.139363-0.96550.169559
200.0527510.36550.358184
210.068540.47490.318521
22-0.009725-0.06740.47328
230.0266320.18450.427193
24-0.030097-0.20850.417853
25-0.041891-0.29020.386445
26-0.095819-0.66390.25498
27-0.160973-1.11530.135147
28-0.131644-0.91210.183148
29-0.143162-0.99190.163121
30-0.124567-0.8630.196207
31-0.030566-0.21180.416592
32-0.125579-0.870.194306
33-0.09086-0.62950.266005
34-0.076495-0.530.299287
35-0.120694-0.83620.203596
36-0.134366-0.93090.178279
37-0.187349-1.2980.100246
38-0.10642-0.73730.232264
39-0.080763-0.55950.289196
40-0.032988-0.22860.410095
410.0203690.14110.444182
42-0.023701-0.16420.435129
430.009410.06520.474145
44-0.04375-0.30310.381559
45-0.056636-0.39240.348254
46-0.04229-0.2930.385394
470.0053310.03690.485346
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.434239 & 3.0085 & 0.002086 \tabularnewline
2 & 0.142449 & 0.9869 & 0.164316 \tabularnewline
3 & -0.000884 & -0.0061 & 0.497569 \tabularnewline
4 & -0.029171 & -0.2021 & 0.420346 \tabularnewline
5 & 0.192418 & 1.3331 & 0.094394 \tabularnewline
6 & 0.148877 & 1.0314 & 0.15375 \tabularnewline
7 & 0.148478 & 1.0287 & 0.154392 \tabularnewline
8 & 0.080539 & 0.558 & 0.289722 \tabularnewline
9 & 0.040572 & 0.2811 & 0.389925 \tabularnewline
10 & 0.157349 & 1.0901 & 0.140545 \tabularnewline
11 & -0.024364 & -0.1688 & 0.433333 \tabularnewline
12 & -0.160837 & -1.1143 & 0.135347 \tabularnewline
13 & -0.108189 & -0.7496 & 0.228591 \tabularnewline
14 & 0.042896 & 0.2972 & 0.383802 \tabularnewline
15 & 0.188214 & 1.304 & 0.099229 \tabularnewline
16 & 0.127091 & 0.8805 & 0.191484 \tabularnewline
17 & 0.025759 & 0.1785 & 0.429556 \tabularnewline
18 & -0.05877 & -0.4072 & 0.342845 \tabularnewline
19 & -0.139363 & -0.9655 & 0.169559 \tabularnewline
20 & 0.052751 & 0.3655 & 0.358184 \tabularnewline
21 & 0.06854 & 0.4749 & 0.318521 \tabularnewline
22 & -0.009725 & -0.0674 & 0.47328 \tabularnewline
23 & 0.026632 & 0.1845 & 0.427193 \tabularnewline
24 & -0.030097 & -0.2085 & 0.417853 \tabularnewline
25 & -0.041891 & -0.2902 & 0.386445 \tabularnewline
26 & -0.095819 & -0.6639 & 0.25498 \tabularnewline
27 & -0.160973 & -1.1153 & 0.135147 \tabularnewline
28 & -0.131644 & -0.9121 & 0.183148 \tabularnewline
29 & -0.143162 & -0.9919 & 0.163121 \tabularnewline
30 & -0.124567 & -0.863 & 0.196207 \tabularnewline
31 & -0.030566 & -0.2118 & 0.416592 \tabularnewline
32 & -0.125579 & -0.87 & 0.194306 \tabularnewline
33 & -0.09086 & -0.6295 & 0.266005 \tabularnewline
34 & -0.076495 & -0.53 & 0.299287 \tabularnewline
35 & -0.120694 & -0.8362 & 0.203596 \tabularnewline
36 & -0.134366 & -0.9309 & 0.178279 \tabularnewline
37 & -0.187349 & -1.298 & 0.100246 \tabularnewline
38 & -0.10642 & -0.7373 & 0.232264 \tabularnewline
39 & -0.080763 & -0.5595 & 0.289196 \tabularnewline
40 & -0.032988 & -0.2286 & 0.410095 \tabularnewline
41 & 0.020369 & 0.1411 & 0.444182 \tabularnewline
42 & -0.023701 & -0.1642 & 0.435129 \tabularnewline
43 & 0.00941 & 0.0652 & 0.474145 \tabularnewline
44 & -0.04375 & -0.3031 & 0.381559 \tabularnewline
45 & -0.056636 & -0.3924 & 0.348254 \tabularnewline
46 & -0.04229 & -0.293 & 0.385394 \tabularnewline
47 & 0.005331 & 0.0369 & 0.485346 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108064&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]0.434239[/C][C]3.0085[/C][C]0.002086[/C][/ROW]
[ROW][C]2[/C][C]0.142449[/C][C]0.9869[/C][C]0.164316[/C][/ROW]
[ROW][C]3[/C][C]-0.000884[/C][C]-0.0061[/C][C]0.497569[/C][/ROW]
[ROW][C]4[/C][C]-0.029171[/C][C]-0.2021[/C][C]0.420346[/C][/ROW]
[ROW][C]5[/C][C]0.192418[/C][C]1.3331[/C][C]0.094394[/C][/ROW]
[ROW][C]6[/C][C]0.148877[/C][C]1.0314[/C][C]0.15375[/C][/ROW]
[ROW][C]7[/C][C]0.148478[/C][C]1.0287[/C][C]0.154392[/C][/ROW]
[ROW][C]8[/C][C]0.080539[/C][C]0.558[/C][C]0.289722[/C][/ROW]
[ROW][C]9[/C][C]0.040572[/C][C]0.2811[/C][C]0.389925[/C][/ROW]
[ROW][C]10[/C][C]0.157349[/C][C]1.0901[/C][C]0.140545[/C][/ROW]
[ROW][C]11[/C][C]-0.024364[/C][C]-0.1688[/C][C]0.433333[/C][/ROW]
[ROW][C]12[/C][C]-0.160837[/C][C]-1.1143[/C][C]0.135347[/C][/ROW]
[ROW][C]13[/C][C]-0.108189[/C][C]-0.7496[/C][C]0.228591[/C][/ROW]
[ROW][C]14[/C][C]0.042896[/C][C]0.2972[/C][C]0.383802[/C][/ROW]
[ROW][C]15[/C][C]0.188214[/C][C]1.304[/C][C]0.099229[/C][/ROW]
[ROW][C]16[/C][C]0.127091[/C][C]0.8805[/C][C]0.191484[/C][/ROW]
[ROW][C]17[/C][C]0.025759[/C][C]0.1785[/C][C]0.429556[/C][/ROW]
[ROW][C]18[/C][C]-0.05877[/C][C]-0.4072[/C][C]0.342845[/C][/ROW]
[ROW][C]19[/C][C]-0.139363[/C][C]-0.9655[/C][C]0.169559[/C][/ROW]
[ROW][C]20[/C][C]0.052751[/C][C]0.3655[/C][C]0.358184[/C][/ROW]
[ROW][C]21[/C][C]0.06854[/C][C]0.4749[/C][C]0.318521[/C][/ROW]
[ROW][C]22[/C][C]-0.009725[/C][C]-0.0674[/C][C]0.47328[/C][/ROW]
[ROW][C]23[/C][C]0.026632[/C][C]0.1845[/C][C]0.427193[/C][/ROW]
[ROW][C]24[/C][C]-0.030097[/C][C]-0.2085[/C][C]0.417853[/C][/ROW]
[ROW][C]25[/C][C]-0.041891[/C][C]-0.2902[/C][C]0.386445[/C][/ROW]
[ROW][C]26[/C][C]-0.095819[/C][C]-0.6639[/C][C]0.25498[/C][/ROW]
[ROW][C]27[/C][C]-0.160973[/C][C]-1.1153[/C][C]0.135147[/C][/ROW]
[ROW][C]28[/C][C]-0.131644[/C][C]-0.9121[/C][C]0.183148[/C][/ROW]
[ROW][C]29[/C][C]-0.143162[/C][C]-0.9919[/C][C]0.163121[/C][/ROW]
[ROW][C]30[/C][C]-0.124567[/C][C]-0.863[/C][C]0.196207[/C][/ROW]
[ROW][C]31[/C][C]-0.030566[/C][C]-0.2118[/C][C]0.416592[/C][/ROW]
[ROW][C]32[/C][C]-0.125579[/C][C]-0.87[/C][C]0.194306[/C][/ROW]
[ROW][C]33[/C][C]-0.09086[/C][C]-0.6295[/C][C]0.266005[/C][/ROW]
[ROW][C]34[/C][C]-0.076495[/C][C]-0.53[/C][C]0.299287[/C][/ROW]
[ROW][C]35[/C][C]-0.120694[/C][C]-0.8362[/C][C]0.203596[/C][/ROW]
[ROW][C]36[/C][C]-0.134366[/C][C]-0.9309[/C][C]0.178279[/C][/ROW]
[ROW][C]37[/C][C]-0.187349[/C][C]-1.298[/C][C]0.100246[/C][/ROW]
[ROW][C]38[/C][C]-0.10642[/C][C]-0.7373[/C][C]0.232264[/C][/ROW]
[ROW][C]39[/C][C]-0.080763[/C][C]-0.5595[/C][C]0.289196[/C][/ROW]
[ROW][C]40[/C][C]-0.032988[/C][C]-0.2286[/C][C]0.410095[/C][/ROW]
[ROW][C]41[/C][C]0.020369[/C][C]0.1411[/C][C]0.444182[/C][/ROW]
[ROW][C]42[/C][C]-0.023701[/C][C]-0.1642[/C][C]0.435129[/C][/ROW]
[ROW][C]43[/C][C]0.00941[/C][C]0.0652[/C][C]0.474145[/C][/ROW]
[ROW][C]44[/C][C]-0.04375[/C][C]-0.3031[/C][C]0.381559[/C][/ROW]
[ROW][C]45[/C][C]-0.056636[/C][C]-0.3924[/C][C]0.348254[/C][/ROW]
[ROW][C]46[/C][C]-0.04229[/C][C]-0.293[/C][C]0.385394[/C][/ROW]
[ROW][C]47[/C][C]0.005331[/C][C]0.0369[/C][C]0.485346[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108064&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108064&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4342393.00850.002086
20.1424490.98690.164316
3-0.000884-0.00610.497569
4-0.029171-0.20210.420346
50.1924181.33310.094394
60.1488771.03140.15375
70.1484781.02870.154392
80.0805390.5580.289722
90.0405720.28110.389925
100.1573491.09010.140545
11-0.024364-0.16880.433333
12-0.160837-1.11430.135347
13-0.108189-0.74960.228591
140.0428960.29720.383802
150.1882141.3040.099229
160.1270910.88050.191484
170.0257590.17850.429556
18-0.05877-0.40720.342845
19-0.139363-0.96550.169559
200.0527510.36550.358184
210.068540.47490.318521
22-0.009725-0.06740.47328
230.0266320.18450.427193
24-0.030097-0.20850.417853
25-0.041891-0.29020.386445
26-0.095819-0.66390.25498
27-0.160973-1.11530.135147
28-0.131644-0.91210.183148
29-0.143162-0.99190.163121
30-0.124567-0.8630.196207
31-0.030566-0.21180.416592
32-0.125579-0.870.194306
33-0.09086-0.62950.266005
34-0.076495-0.530.299287
35-0.120694-0.83620.203596
36-0.134366-0.93090.178279
37-0.187349-1.2980.100246
38-0.10642-0.73730.232264
39-0.080763-0.55950.289196
40-0.032988-0.22860.410095
410.0203690.14110.444182
42-0.023701-0.16420.435129
430.009410.06520.474145
44-0.04375-0.30310.381559
45-0.056636-0.39240.348254
46-0.04229-0.2930.385394
470.0053310.03690.485346
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4342393.00850.002086
2-0.05683-0.39370.347761
3-0.051407-0.35620.361642
4-0.00212-0.01470.494172
50.265031.83620.036264
6-0.049525-0.34310.366504
70.083840.58090.282027
8-0.003937-0.02730.489175
90.0481630.33370.370037
100.1217780.84370.201511
11-0.203051-1.40680.082968
12-0.171656-1.18930.120092
130.0631670.43760.331808
140.1532961.06210.146761
150.0272060.18850.425645
16-0.025866-0.17920.429265
170.0125090.08670.465649
180.0180790.12530.450422
19-0.112867-0.7820.219038
200.1181110.81830.208617
21-0.017268-0.11960.452635
22-0.058142-0.40280.344435
230.0499960.34640.365285
24-0.06955-0.48190.316048
25-0.11274-0.78110.219294
26-0.018496-0.12810.449284
27-0.050323-0.34860.36444
28-0.057673-0.39960.345624
29-0.044568-0.30880.379414
30-0.154108-1.06770.145499
310.0696060.48220.315911
32-0.059789-0.41420.340275
330.0557290.38610.350563
34-0.007711-0.05340.478809
35-0.057488-0.39830.346091
36-0.089991-0.62350.267962
37-0.076605-0.53070.299024
38-0.03241-0.22450.411644
39-0.004473-0.0310.487703
400.0515930.35740.361161
41-0.003658-0.02530.489943
420.0732450.50750.307079
430.0441780.30610.380436
44-0.051857-0.35930.360483
450.0067870.0470.481344
460.0215980.14960.440838
470.0881920.6110.272038
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.434239 & 3.0085 & 0.002086 \tabularnewline
2 & -0.05683 & -0.3937 & 0.347761 \tabularnewline
3 & -0.051407 & -0.3562 & 0.361642 \tabularnewline
4 & -0.00212 & -0.0147 & 0.494172 \tabularnewline
5 & 0.26503 & 1.8362 & 0.036264 \tabularnewline
6 & -0.049525 & -0.3431 & 0.366504 \tabularnewline
7 & 0.08384 & 0.5809 & 0.282027 \tabularnewline
8 & -0.003937 & -0.0273 & 0.489175 \tabularnewline
9 & 0.048163 & 0.3337 & 0.370037 \tabularnewline
10 & 0.121778 & 0.8437 & 0.201511 \tabularnewline
11 & -0.203051 & -1.4068 & 0.082968 \tabularnewline
12 & -0.171656 & -1.1893 & 0.120092 \tabularnewline
13 & 0.063167 & 0.4376 & 0.331808 \tabularnewline
14 & 0.153296 & 1.0621 & 0.146761 \tabularnewline
15 & 0.027206 & 0.1885 & 0.425645 \tabularnewline
16 & -0.025866 & -0.1792 & 0.429265 \tabularnewline
17 & 0.012509 & 0.0867 & 0.465649 \tabularnewline
18 & 0.018079 & 0.1253 & 0.450422 \tabularnewline
19 & -0.112867 & -0.782 & 0.219038 \tabularnewline
20 & 0.118111 & 0.8183 & 0.208617 \tabularnewline
21 & -0.017268 & -0.1196 & 0.452635 \tabularnewline
22 & -0.058142 & -0.4028 & 0.344435 \tabularnewline
23 & 0.049996 & 0.3464 & 0.365285 \tabularnewline
24 & -0.06955 & -0.4819 & 0.316048 \tabularnewline
25 & -0.11274 & -0.7811 & 0.219294 \tabularnewline
26 & -0.018496 & -0.1281 & 0.449284 \tabularnewline
27 & -0.050323 & -0.3486 & 0.36444 \tabularnewline
28 & -0.057673 & -0.3996 & 0.345624 \tabularnewline
29 & -0.044568 & -0.3088 & 0.379414 \tabularnewline
30 & -0.154108 & -1.0677 & 0.145499 \tabularnewline
31 & 0.069606 & 0.4822 & 0.315911 \tabularnewline
32 & -0.059789 & -0.4142 & 0.340275 \tabularnewline
33 & 0.055729 & 0.3861 & 0.350563 \tabularnewline
34 & -0.007711 & -0.0534 & 0.478809 \tabularnewline
35 & -0.057488 & -0.3983 & 0.346091 \tabularnewline
36 & -0.089991 & -0.6235 & 0.267962 \tabularnewline
37 & -0.076605 & -0.5307 & 0.299024 \tabularnewline
38 & -0.03241 & -0.2245 & 0.411644 \tabularnewline
39 & -0.004473 & -0.031 & 0.487703 \tabularnewline
40 & 0.051593 & 0.3574 & 0.361161 \tabularnewline
41 & -0.003658 & -0.0253 & 0.489943 \tabularnewline
42 & 0.073245 & 0.5075 & 0.307079 \tabularnewline
43 & 0.044178 & 0.3061 & 0.380436 \tabularnewline
44 & -0.051857 & -0.3593 & 0.360483 \tabularnewline
45 & 0.006787 & 0.047 & 0.481344 \tabularnewline
46 & 0.021598 & 0.1496 & 0.440838 \tabularnewline
47 & 0.088192 & 0.611 & 0.272038 \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108064&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]0.434239[/C][C]3.0085[/C][C]0.002086[/C][/ROW]
[ROW][C]2[/C][C]-0.05683[/C][C]-0.3937[/C][C]0.347761[/C][/ROW]
[ROW][C]3[/C][C]-0.051407[/C][C]-0.3562[/C][C]0.361642[/C][/ROW]
[ROW][C]4[/C][C]-0.00212[/C][C]-0.0147[/C][C]0.494172[/C][/ROW]
[ROW][C]5[/C][C]0.26503[/C][C]1.8362[/C][C]0.036264[/C][/ROW]
[ROW][C]6[/C][C]-0.049525[/C][C]-0.3431[/C][C]0.366504[/C][/ROW]
[ROW][C]7[/C][C]0.08384[/C][C]0.5809[/C][C]0.282027[/C][/ROW]
[ROW][C]8[/C][C]-0.003937[/C][C]-0.0273[/C][C]0.489175[/C][/ROW]
[ROW][C]9[/C][C]0.048163[/C][C]0.3337[/C][C]0.370037[/C][/ROW]
[ROW][C]10[/C][C]0.121778[/C][C]0.8437[/C][C]0.201511[/C][/ROW]
[ROW][C]11[/C][C]-0.203051[/C][C]-1.4068[/C][C]0.082968[/C][/ROW]
[ROW][C]12[/C][C]-0.171656[/C][C]-1.1893[/C][C]0.120092[/C][/ROW]
[ROW][C]13[/C][C]0.063167[/C][C]0.4376[/C][C]0.331808[/C][/ROW]
[ROW][C]14[/C][C]0.153296[/C][C]1.0621[/C][C]0.146761[/C][/ROW]
[ROW][C]15[/C][C]0.027206[/C][C]0.1885[/C][C]0.425645[/C][/ROW]
[ROW][C]16[/C][C]-0.025866[/C][C]-0.1792[/C][C]0.429265[/C][/ROW]
[ROW][C]17[/C][C]0.012509[/C][C]0.0867[/C][C]0.465649[/C][/ROW]
[ROW][C]18[/C][C]0.018079[/C][C]0.1253[/C][C]0.450422[/C][/ROW]
[ROW][C]19[/C][C]-0.112867[/C][C]-0.782[/C][C]0.219038[/C][/ROW]
[ROW][C]20[/C][C]0.118111[/C][C]0.8183[/C][C]0.208617[/C][/ROW]
[ROW][C]21[/C][C]-0.017268[/C][C]-0.1196[/C][C]0.452635[/C][/ROW]
[ROW][C]22[/C][C]-0.058142[/C][C]-0.4028[/C][C]0.344435[/C][/ROW]
[ROW][C]23[/C][C]0.049996[/C][C]0.3464[/C][C]0.365285[/C][/ROW]
[ROW][C]24[/C][C]-0.06955[/C][C]-0.4819[/C][C]0.316048[/C][/ROW]
[ROW][C]25[/C][C]-0.11274[/C][C]-0.7811[/C][C]0.219294[/C][/ROW]
[ROW][C]26[/C][C]-0.018496[/C][C]-0.1281[/C][C]0.449284[/C][/ROW]
[ROW][C]27[/C][C]-0.050323[/C][C]-0.3486[/C][C]0.36444[/C][/ROW]
[ROW][C]28[/C][C]-0.057673[/C][C]-0.3996[/C][C]0.345624[/C][/ROW]
[ROW][C]29[/C][C]-0.044568[/C][C]-0.3088[/C][C]0.379414[/C][/ROW]
[ROW][C]30[/C][C]-0.154108[/C][C]-1.0677[/C][C]0.145499[/C][/ROW]
[ROW][C]31[/C][C]0.069606[/C][C]0.4822[/C][C]0.315911[/C][/ROW]
[ROW][C]32[/C][C]-0.059789[/C][C]-0.4142[/C][C]0.340275[/C][/ROW]
[ROW][C]33[/C][C]0.055729[/C][C]0.3861[/C][C]0.350563[/C][/ROW]
[ROW][C]34[/C][C]-0.007711[/C][C]-0.0534[/C][C]0.478809[/C][/ROW]
[ROW][C]35[/C][C]-0.057488[/C][C]-0.3983[/C][C]0.346091[/C][/ROW]
[ROW][C]36[/C][C]-0.089991[/C][C]-0.6235[/C][C]0.267962[/C][/ROW]
[ROW][C]37[/C][C]-0.076605[/C][C]-0.5307[/C][C]0.299024[/C][/ROW]
[ROW][C]38[/C][C]-0.03241[/C][C]-0.2245[/C][C]0.411644[/C][/ROW]
[ROW][C]39[/C][C]-0.004473[/C][C]-0.031[/C][C]0.487703[/C][/ROW]
[ROW][C]40[/C][C]0.051593[/C][C]0.3574[/C][C]0.361161[/C][/ROW]
[ROW][C]41[/C][C]-0.003658[/C][C]-0.0253[/C][C]0.489943[/C][/ROW]
[ROW][C]42[/C][C]0.073245[/C][C]0.5075[/C][C]0.307079[/C][/ROW]
[ROW][C]43[/C][C]0.044178[/C][C]0.3061[/C][C]0.380436[/C][/ROW]
[ROW][C]44[/C][C]-0.051857[/C][C]-0.3593[/C][C]0.360483[/C][/ROW]
[ROW][C]45[/C][C]0.006787[/C][C]0.047[/C][C]0.481344[/C][/ROW]
[ROW][C]46[/C][C]0.021598[/C][C]0.1496[/C][C]0.440838[/C][/ROW]
[ROW][C]47[/C][C]0.088192[/C][C]0.611[/C][C]0.272038[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108064&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108064&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4342393.00850.002086
2-0.05683-0.39370.347761
3-0.051407-0.35620.361642
4-0.00212-0.01470.494172
50.265031.83620.036264
6-0.049525-0.34310.366504
70.083840.58090.282027
8-0.003937-0.02730.489175
90.0481630.33370.370037
100.1217780.84370.201511
11-0.203051-1.40680.082968
12-0.171656-1.18930.120092
130.0631670.43760.331808
140.1532961.06210.146761
150.0272060.18850.425645
16-0.025866-0.17920.429265
170.0125090.08670.465649
180.0180790.12530.450422
19-0.112867-0.7820.219038
200.1181110.81830.208617
21-0.017268-0.11960.452635
22-0.058142-0.40280.344435
230.0499960.34640.365285
24-0.06955-0.48190.316048
25-0.11274-0.78110.219294
26-0.018496-0.12810.449284
27-0.050323-0.34860.36444
28-0.057673-0.39960.345624
29-0.044568-0.30880.379414
30-0.154108-1.06770.145499
310.0696060.48220.315911
32-0.059789-0.41420.340275
330.0557290.38610.350563
34-0.007711-0.05340.478809
35-0.057488-0.39830.346091
36-0.089991-0.62350.267962
37-0.076605-0.53070.299024
38-0.03241-0.22450.411644
39-0.004473-0.0310.487703
400.0515930.35740.361161
41-0.003658-0.02530.489943
420.0732450.50750.307079
430.0441780.30610.380436
44-0.051857-0.35930.360483
450.0067870.0470.481344
460.0215980.14960.440838
470.0881920.6110.272038
48NANANA



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')