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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 computationThu, 17 Dec 2009 03:35:53 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/17/t1261046329z5zyt4d32nx40m0.htm/, Retrieved Tue, 30 Apr 2024 07:48:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68703, Retrieved Tue, 30 Apr 2024 07:48:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Partial autocorre...] [2008-12-09 20:18:51] [12d343c4448a5f9e527bb31caeac580b]
-   P   [(Partial) Autocorrelation Function] [Partial autocorre...] [2008-12-09 20:27:26] [12d343c4448a5f9e527bb31caeac580b]
- RMPD      [(Partial) Autocorrelation Function] [Partial correlati...] [2009-12-17 10:35:53] [bcaf453a09027aa0f995cb78bdc3c98a] [Current]
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Dataseries X:
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8
8
7.7
7.3
7.4
8.1
8.3
8.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68703&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68703&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68703&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3367722.60860.005729
2-0.303004-2.34710.01112
3-0.526512-4.07836.8e-05
4-0.347681-2.69310.004582
50.1477491.14450.12849
60.5343944.13945.5e-05
70.3493152.70580.004429
8-0.067593-0.52360.301251
9-0.341231-2.64320.005232
10-0.317985-2.46310.00833
11-0.007173-0.05560.477937
120.3677462.84860.003004
130.080590.62430.267415
14-0.081037-0.62770.266287
15-0.08475-0.65650.257016
16-0.086491-0.670.252727
170.0003260.00250.498998
180.0969230.75080.227866
190.0273350.21170.416515
20-0.054541-0.42250.337094
21-0.063247-0.48990.312993
22-0.05828-0.45140.326651
230.0433350.33570.369145
240.1661741.28720.101487
25-0.104647-0.81060.210401
26-0.146866-1.13760.129901
27-0.066347-0.51390.304597
28-0.011507-0.08910.464635
290.0814540.63090.265238
300.1305591.01130.157966
310.0383390.2970.383757
32-0.120626-0.93440.17693
33-0.167171-1.29490.100157
340.0055160.04270.483032
350.1722121.33390.093631
360.2347321.81820.037011
37-0.021855-0.16930.433071
38-0.179847-1.39310.084367
39-0.188706-1.46170.07452
40-0.03458-0.26790.394864
410.1646561.27540.103538
420.2686532.0810.020856
430.0733830.56840.285934
44-0.191575-1.48390.07153
45-0.262443-2.03290.023249
46-0.064921-0.50290.308445
470.1359791.05330.148215
480.208281.61330.05596
490.0486230.37660.353887
50-0.112159-0.86880.194214
51-0.14575-1.1290.131701
52-0.063004-0.4880.313655
530.0300860.2330.408261
540.0846440.65560.257279
550.0442430.34270.366509
56-0.062493-0.48410.315048
57-0.081824-0.63380.264309
58-0.013466-0.10430.458637
590.0072970.05650.477557
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.336772 & 2.6086 & 0.005729 \tabularnewline
2 & -0.303004 & -2.3471 & 0.01112 \tabularnewline
3 & -0.526512 & -4.0783 & 6.8e-05 \tabularnewline
4 & -0.347681 & -2.6931 & 0.004582 \tabularnewline
5 & 0.147749 & 1.1445 & 0.12849 \tabularnewline
6 & 0.534394 & 4.1394 & 5.5e-05 \tabularnewline
7 & 0.349315 & 2.7058 & 0.004429 \tabularnewline
8 & -0.067593 & -0.5236 & 0.301251 \tabularnewline
9 & -0.341231 & -2.6432 & 0.005232 \tabularnewline
10 & -0.317985 & -2.4631 & 0.00833 \tabularnewline
11 & -0.007173 & -0.0556 & 0.477937 \tabularnewline
12 & 0.367746 & 2.8486 & 0.003004 \tabularnewline
13 & 0.08059 & 0.6243 & 0.267415 \tabularnewline
14 & -0.081037 & -0.6277 & 0.266287 \tabularnewline
15 & -0.08475 & -0.6565 & 0.257016 \tabularnewline
16 & -0.086491 & -0.67 & 0.252727 \tabularnewline
17 & 0.000326 & 0.0025 & 0.498998 \tabularnewline
18 & 0.096923 & 0.7508 & 0.227866 \tabularnewline
19 & 0.027335 & 0.2117 & 0.416515 \tabularnewline
20 & -0.054541 & -0.4225 & 0.337094 \tabularnewline
21 & -0.063247 & -0.4899 & 0.312993 \tabularnewline
22 & -0.05828 & -0.4514 & 0.326651 \tabularnewline
23 & 0.043335 & 0.3357 & 0.369145 \tabularnewline
24 & 0.166174 & 1.2872 & 0.101487 \tabularnewline
25 & -0.104647 & -0.8106 & 0.210401 \tabularnewline
26 & -0.146866 & -1.1376 & 0.129901 \tabularnewline
27 & -0.066347 & -0.5139 & 0.304597 \tabularnewline
28 & -0.011507 & -0.0891 & 0.464635 \tabularnewline
29 & 0.081454 & 0.6309 & 0.265238 \tabularnewline
30 & 0.130559 & 1.0113 & 0.157966 \tabularnewline
31 & 0.038339 & 0.297 & 0.383757 \tabularnewline
32 & -0.120626 & -0.9344 & 0.17693 \tabularnewline
33 & -0.167171 & -1.2949 & 0.100157 \tabularnewline
34 & 0.005516 & 0.0427 & 0.483032 \tabularnewline
35 & 0.172212 & 1.3339 & 0.093631 \tabularnewline
36 & 0.234732 & 1.8182 & 0.037011 \tabularnewline
37 & -0.021855 & -0.1693 & 0.433071 \tabularnewline
38 & -0.179847 & -1.3931 & 0.084367 \tabularnewline
39 & -0.188706 & -1.4617 & 0.07452 \tabularnewline
40 & -0.03458 & -0.2679 & 0.394864 \tabularnewline
41 & 0.164656 & 1.2754 & 0.103538 \tabularnewline
42 & 0.268653 & 2.081 & 0.020856 \tabularnewline
43 & 0.073383 & 0.5684 & 0.285934 \tabularnewline
44 & -0.191575 & -1.4839 & 0.07153 \tabularnewline
45 & -0.262443 & -2.0329 & 0.023249 \tabularnewline
46 & -0.064921 & -0.5029 & 0.308445 \tabularnewline
47 & 0.135979 & 1.0533 & 0.148215 \tabularnewline
48 & 0.20828 & 1.6133 & 0.05596 \tabularnewline
49 & 0.048623 & 0.3766 & 0.353887 \tabularnewline
50 & -0.112159 & -0.8688 & 0.194214 \tabularnewline
51 & -0.14575 & -1.129 & 0.131701 \tabularnewline
52 & -0.063004 & -0.488 & 0.313655 \tabularnewline
53 & 0.030086 & 0.233 & 0.408261 \tabularnewline
54 & 0.084644 & 0.6556 & 0.257279 \tabularnewline
55 & 0.044243 & 0.3427 & 0.366509 \tabularnewline
56 & -0.062493 & -0.4841 & 0.315048 \tabularnewline
57 & -0.081824 & -0.6338 & 0.264309 \tabularnewline
58 & -0.013466 & -0.1043 & 0.458637 \tabularnewline
59 & 0.007297 & 0.0565 & 0.477557 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68703&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]0.336772[/C][C]2.6086[/C][C]0.005729[/C][/ROW]
[ROW][C]2[/C][C]-0.303004[/C][C]-2.3471[/C][C]0.01112[/C][/ROW]
[ROW][C]3[/C][C]-0.526512[/C][C]-4.0783[/C][C]6.8e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.347681[/C][C]-2.6931[/C][C]0.004582[/C][/ROW]
[ROW][C]5[/C][C]0.147749[/C][C]1.1445[/C][C]0.12849[/C][/ROW]
[ROW][C]6[/C][C]0.534394[/C][C]4.1394[/C][C]5.5e-05[/C][/ROW]
[ROW][C]7[/C][C]0.349315[/C][C]2.7058[/C][C]0.004429[/C][/ROW]
[ROW][C]8[/C][C]-0.067593[/C][C]-0.5236[/C][C]0.301251[/C][/ROW]
[ROW][C]9[/C][C]-0.341231[/C][C]-2.6432[/C][C]0.005232[/C][/ROW]
[ROW][C]10[/C][C]-0.317985[/C][C]-2.4631[/C][C]0.00833[/C][/ROW]
[ROW][C]11[/C][C]-0.007173[/C][C]-0.0556[/C][C]0.477937[/C][/ROW]
[ROW][C]12[/C][C]0.367746[/C][C]2.8486[/C][C]0.003004[/C][/ROW]
[ROW][C]13[/C][C]0.08059[/C][C]0.6243[/C][C]0.267415[/C][/ROW]
[ROW][C]14[/C][C]-0.081037[/C][C]-0.6277[/C][C]0.266287[/C][/ROW]
[ROW][C]15[/C][C]-0.08475[/C][C]-0.6565[/C][C]0.257016[/C][/ROW]
[ROW][C]16[/C][C]-0.086491[/C][C]-0.67[/C][C]0.252727[/C][/ROW]
[ROW][C]17[/C][C]0.000326[/C][C]0.0025[/C][C]0.498998[/C][/ROW]
[ROW][C]18[/C][C]0.096923[/C][C]0.7508[/C][C]0.227866[/C][/ROW]
[ROW][C]19[/C][C]0.027335[/C][C]0.2117[/C][C]0.416515[/C][/ROW]
[ROW][C]20[/C][C]-0.054541[/C][C]-0.4225[/C][C]0.337094[/C][/ROW]
[ROW][C]21[/C][C]-0.063247[/C][C]-0.4899[/C][C]0.312993[/C][/ROW]
[ROW][C]22[/C][C]-0.05828[/C][C]-0.4514[/C][C]0.326651[/C][/ROW]
[ROW][C]23[/C][C]0.043335[/C][C]0.3357[/C][C]0.369145[/C][/ROW]
[ROW][C]24[/C][C]0.166174[/C][C]1.2872[/C][C]0.101487[/C][/ROW]
[ROW][C]25[/C][C]-0.104647[/C][C]-0.8106[/C][C]0.210401[/C][/ROW]
[ROW][C]26[/C][C]-0.146866[/C][C]-1.1376[/C][C]0.129901[/C][/ROW]
[ROW][C]27[/C][C]-0.066347[/C][C]-0.5139[/C][C]0.304597[/C][/ROW]
[ROW][C]28[/C][C]-0.011507[/C][C]-0.0891[/C][C]0.464635[/C][/ROW]
[ROW][C]29[/C][C]0.081454[/C][C]0.6309[/C][C]0.265238[/C][/ROW]
[ROW][C]30[/C][C]0.130559[/C][C]1.0113[/C][C]0.157966[/C][/ROW]
[ROW][C]31[/C][C]0.038339[/C][C]0.297[/C][C]0.383757[/C][/ROW]
[ROW][C]32[/C][C]-0.120626[/C][C]-0.9344[/C][C]0.17693[/C][/ROW]
[ROW][C]33[/C][C]-0.167171[/C][C]-1.2949[/C][C]0.100157[/C][/ROW]
[ROW][C]34[/C][C]0.005516[/C][C]0.0427[/C][C]0.483032[/C][/ROW]
[ROW][C]35[/C][C]0.172212[/C][C]1.3339[/C][C]0.093631[/C][/ROW]
[ROW][C]36[/C][C]0.234732[/C][C]1.8182[/C][C]0.037011[/C][/ROW]
[ROW][C]37[/C][C]-0.021855[/C][C]-0.1693[/C][C]0.433071[/C][/ROW]
[ROW][C]38[/C][C]-0.179847[/C][C]-1.3931[/C][C]0.084367[/C][/ROW]
[ROW][C]39[/C][C]-0.188706[/C][C]-1.4617[/C][C]0.07452[/C][/ROW]
[ROW][C]40[/C][C]-0.03458[/C][C]-0.2679[/C][C]0.394864[/C][/ROW]
[ROW][C]41[/C][C]0.164656[/C][C]1.2754[/C][C]0.103538[/C][/ROW]
[ROW][C]42[/C][C]0.268653[/C][C]2.081[/C][C]0.020856[/C][/ROW]
[ROW][C]43[/C][C]0.073383[/C][C]0.5684[/C][C]0.285934[/C][/ROW]
[ROW][C]44[/C][C]-0.191575[/C][C]-1.4839[/C][C]0.07153[/C][/ROW]
[ROW][C]45[/C][C]-0.262443[/C][C]-2.0329[/C][C]0.023249[/C][/ROW]
[ROW][C]46[/C][C]-0.064921[/C][C]-0.5029[/C][C]0.308445[/C][/ROW]
[ROW][C]47[/C][C]0.135979[/C][C]1.0533[/C][C]0.148215[/C][/ROW]
[ROW][C]48[/C][C]0.20828[/C][C]1.6133[/C][C]0.05596[/C][/ROW]
[ROW][C]49[/C][C]0.048623[/C][C]0.3766[/C][C]0.353887[/C][/ROW]
[ROW][C]50[/C][C]-0.112159[/C][C]-0.8688[/C][C]0.194214[/C][/ROW]
[ROW][C]51[/C][C]-0.14575[/C][C]-1.129[/C][C]0.131701[/C][/ROW]
[ROW][C]52[/C][C]-0.063004[/C][C]-0.488[/C][C]0.313655[/C][/ROW]
[ROW][C]53[/C][C]0.030086[/C][C]0.233[/C][C]0.408261[/C][/ROW]
[ROW][C]54[/C][C]0.084644[/C][C]0.6556[/C][C]0.257279[/C][/ROW]
[ROW][C]55[/C][C]0.044243[/C][C]0.3427[/C][C]0.366509[/C][/ROW]
[ROW][C]56[/C][C]-0.062493[/C][C]-0.4841[/C][C]0.315048[/C][/ROW]
[ROW][C]57[/C][C]-0.081824[/C][C]-0.6338[/C][C]0.264309[/C][/ROW]
[ROW][C]58[/C][C]-0.013466[/C][C]-0.1043[/C][C]0.458637[/C][/ROW]
[ROW][C]59[/C][C]0.007297[/C][C]0.0565[/C][C]0.477557[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68703&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68703&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
10.3367722.60860.005729
2-0.303004-2.34710.01112
3-0.526512-4.07836.8e-05
4-0.347681-2.69310.004582
50.1477491.14450.12849
60.5343944.13945.5e-05
70.3493152.70580.004429
8-0.067593-0.52360.301251
9-0.341231-2.64320.005232
10-0.317985-2.46310.00833
11-0.007173-0.05560.477937
120.3677462.84860.003004
130.080590.62430.267415
14-0.081037-0.62770.266287
15-0.08475-0.65650.257016
16-0.086491-0.670.252727
170.0003260.00250.498998
180.0969230.75080.227866
190.0273350.21170.416515
20-0.054541-0.42250.337094
21-0.063247-0.48990.312993
22-0.05828-0.45140.326651
230.0433350.33570.369145
240.1661741.28720.101487
25-0.104647-0.81060.210401
26-0.146866-1.13760.129901
27-0.066347-0.51390.304597
28-0.011507-0.08910.464635
290.0814540.63090.265238
300.1305591.01130.157966
310.0383390.2970.383757
32-0.120626-0.93440.17693
33-0.167171-1.29490.100157
340.0055160.04270.483032
350.1722121.33390.093631
360.2347321.81820.037011
37-0.021855-0.16930.433071
38-0.179847-1.39310.084367
39-0.188706-1.46170.07452
40-0.03458-0.26790.394864
410.1646561.27540.103538
420.2686532.0810.020856
430.0733830.56840.285934
44-0.191575-1.48390.07153
45-0.262443-2.03290.023249
46-0.064921-0.50290.308445
470.1359791.05330.148215
480.208281.61330.05596
490.0486230.37660.353887
50-0.112159-0.86880.194214
51-0.14575-1.1290.131701
52-0.063004-0.4880.313655
530.0300860.2330.408261
540.0846440.65560.257279
550.0442430.34270.366509
56-0.062493-0.48410.315048
57-0.081824-0.63380.264309
58-0.013466-0.10430.458637
590.0072970.05650.477557
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3367722.60860.005729
2-0.46969-3.63820.000286
3-0.31601-2.44780.008658
4-0.247163-1.91450.030163
50.0835540.64720.259984
60.2562571.9850.025863
70.0453590.35130.363279
80.0701560.54340.294425
90.0403940.31290.377724
10-0.005905-0.04570.481836
110.0094430.07310.470966
120.1501231.16290.124747
13-0.464009-3.59420.000329
140.1078610.83550.20338
150.0763820.59170.278154
16-0.000149-0.00120.499541
17-0.051079-0.39570.346882
18-0.017182-0.13310.447282
190.0980620.75960.225238
20-0.001474-0.01140.495464
21-0.049406-0.38270.351648
22-0.138893-1.07590.143148
230.0618840.47940.316714
240.0591420.45810.324262
25-0.170898-1.32380.095301
26-0.082745-0.64090.262
27-0.094453-0.73160.233622
280.0537940.41670.339198
290.0003550.00270.498908
30-0.02368-0.18340.42754
310.0622680.48230.315666
32-0.027364-0.2120.416428
330.0013130.01020.495961
340.2401281.860.033893
350.001080.00840.496676
360.0155470.12040.452275
370.0485550.37610.354082
38-0.10158-0.78680.217237
39-0.08888-0.68850.246907
40-0.014861-0.11510.454371
41-0.047297-0.36640.357692
420.1124710.87120.193559
43-0.083403-0.6460.260358
440.0416190.32240.374143
450.0759630.58840.279233
46-0.016946-0.13130.448004
47-0.029356-0.22740.410445
48-0.105913-0.82040.207618
49-0.003268-0.02530.489946
50-0.085029-0.65860.256326
510.0411680.31890.375461
52-0.105216-0.8150.209148
53-0.034198-0.26490.396
54-0.064116-0.49660.310629
550.0485290.37590.354156
560.0169510.13130.447986
57-0.051595-0.39970.345416
58-0.080131-0.62070.268576
590.0726190.56250.287935
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.336772 & 2.6086 & 0.005729 \tabularnewline
2 & -0.46969 & -3.6382 & 0.000286 \tabularnewline
3 & -0.31601 & -2.4478 & 0.008658 \tabularnewline
4 & -0.247163 & -1.9145 & 0.030163 \tabularnewline
5 & 0.083554 & 0.6472 & 0.259984 \tabularnewline
6 & 0.256257 & 1.985 & 0.025863 \tabularnewline
7 & 0.045359 & 0.3513 & 0.363279 \tabularnewline
8 & 0.070156 & 0.5434 & 0.294425 \tabularnewline
9 & 0.040394 & 0.3129 & 0.377724 \tabularnewline
10 & -0.005905 & -0.0457 & 0.481836 \tabularnewline
11 & 0.009443 & 0.0731 & 0.470966 \tabularnewline
12 & 0.150123 & 1.1629 & 0.124747 \tabularnewline
13 & -0.464009 & -3.5942 & 0.000329 \tabularnewline
14 & 0.107861 & 0.8355 & 0.20338 \tabularnewline
15 & 0.076382 & 0.5917 & 0.278154 \tabularnewline
16 & -0.000149 & -0.0012 & 0.499541 \tabularnewline
17 & -0.051079 & -0.3957 & 0.346882 \tabularnewline
18 & -0.017182 & -0.1331 & 0.447282 \tabularnewline
19 & 0.098062 & 0.7596 & 0.225238 \tabularnewline
20 & -0.001474 & -0.0114 & 0.495464 \tabularnewline
21 & -0.049406 & -0.3827 & 0.351648 \tabularnewline
22 & -0.138893 & -1.0759 & 0.143148 \tabularnewline
23 & 0.061884 & 0.4794 & 0.316714 \tabularnewline
24 & 0.059142 & 0.4581 & 0.324262 \tabularnewline
25 & -0.170898 & -1.3238 & 0.095301 \tabularnewline
26 & -0.082745 & -0.6409 & 0.262 \tabularnewline
27 & -0.094453 & -0.7316 & 0.233622 \tabularnewline
28 & 0.053794 & 0.4167 & 0.339198 \tabularnewline
29 & 0.000355 & 0.0027 & 0.498908 \tabularnewline
30 & -0.02368 & -0.1834 & 0.42754 \tabularnewline
31 & 0.062268 & 0.4823 & 0.315666 \tabularnewline
32 & -0.027364 & -0.212 & 0.416428 \tabularnewline
33 & 0.001313 & 0.0102 & 0.495961 \tabularnewline
34 & 0.240128 & 1.86 & 0.033893 \tabularnewline
35 & 0.00108 & 0.0084 & 0.496676 \tabularnewline
36 & 0.015547 & 0.1204 & 0.452275 \tabularnewline
37 & 0.048555 & 0.3761 & 0.354082 \tabularnewline
38 & -0.10158 & -0.7868 & 0.217237 \tabularnewline
39 & -0.08888 & -0.6885 & 0.246907 \tabularnewline
40 & -0.014861 & -0.1151 & 0.454371 \tabularnewline
41 & -0.047297 & -0.3664 & 0.357692 \tabularnewline
42 & 0.112471 & 0.8712 & 0.193559 \tabularnewline
43 & -0.083403 & -0.646 & 0.260358 \tabularnewline
44 & 0.041619 & 0.3224 & 0.374143 \tabularnewline
45 & 0.075963 & 0.5884 & 0.279233 \tabularnewline
46 & -0.016946 & -0.1313 & 0.448004 \tabularnewline
47 & -0.029356 & -0.2274 & 0.410445 \tabularnewline
48 & -0.105913 & -0.8204 & 0.207618 \tabularnewline
49 & -0.003268 & -0.0253 & 0.489946 \tabularnewline
50 & -0.085029 & -0.6586 & 0.256326 \tabularnewline
51 & 0.041168 & 0.3189 & 0.375461 \tabularnewline
52 & -0.105216 & -0.815 & 0.209148 \tabularnewline
53 & -0.034198 & -0.2649 & 0.396 \tabularnewline
54 & -0.064116 & -0.4966 & 0.310629 \tabularnewline
55 & 0.048529 & 0.3759 & 0.354156 \tabularnewline
56 & 0.016951 & 0.1313 & 0.447986 \tabularnewline
57 & -0.051595 & -0.3997 & 0.345416 \tabularnewline
58 & -0.080131 & -0.6207 & 0.268576 \tabularnewline
59 & 0.072619 & 0.5625 & 0.287935 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68703&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]0.336772[/C][C]2.6086[/C][C]0.005729[/C][/ROW]
[ROW][C]2[/C][C]-0.46969[/C][C]-3.6382[/C][C]0.000286[/C][/ROW]
[ROW][C]3[/C][C]-0.31601[/C][C]-2.4478[/C][C]0.008658[/C][/ROW]
[ROW][C]4[/C][C]-0.247163[/C][C]-1.9145[/C][C]0.030163[/C][/ROW]
[ROW][C]5[/C][C]0.083554[/C][C]0.6472[/C][C]0.259984[/C][/ROW]
[ROW][C]6[/C][C]0.256257[/C][C]1.985[/C][C]0.025863[/C][/ROW]
[ROW][C]7[/C][C]0.045359[/C][C]0.3513[/C][C]0.363279[/C][/ROW]
[ROW][C]8[/C][C]0.070156[/C][C]0.5434[/C][C]0.294425[/C][/ROW]
[ROW][C]9[/C][C]0.040394[/C][C]0.3129[/C][C]0.377724[/C][/ROW]
[ROW][C]10[/C][C]-0.005905[/C][C]-0.0457[/C][C]0.481836[/C][/ROW]
[ROW][C]11[/C][C]0.009443[/C][C]0.0731[/C][C]0.470966[/C][/ROW]
[ROW][C]12[/C][C]0.150123[/C][C]1.1629[/C][C]0.124747[/C][/ROW]
[ROW][C]13[/C][C]-0.464009[/C][C]-3.5942[/C][C]0.000329[/C][/ROW]
[ROW][C]14[/C][C]0.107861[/C][C]0.8355[/C][C]0.20338[/C][/ROW]
[ROW][C]15[/C][C]0.076382[/C][C]0.5917[/C][C]0.278154[/C][/ROW]
[ROW][C]16[/C][C]-0.000149[/C][C]-0.0012[/C][C]0.499541[/C][/ROW]
[ROW][C]17[/C][C]-0.051079[/C][C]-0.3957[/C][C]0.346882[/C][/ROW]
[ROW][C]18[/C][C]-0.017182[/C][C]-0.1331[/C][C]0.447282[/C][/ROW]
[ROW][C]19[/C][C]0.098062[/C][C]0.7596[/C][C]0.225238[/C][/ROW]
[ROW][C]20[/C][C]-0.001474[/C][C]-0.0114[/C][C]0.495464[/C][/ROW]
[ROW][C]21[/C][C]-0.049406[/C][C]-0.3827[/C][C]0.351648[/C][/ROW]
[ROW][C]22[/C][C]-0.138893[/C][C]-1.0759[/C][C]0.143148[/C][/ROW]
[ROW][C]23[/C][C]0.061884[/C][C]0.4794[/C][C]0.316714[/C][/ROW]
[ROW][C]24[/C][C]0.059142[/C][C]0.4581[/C][C]0.324262[/C][/ROW]
[ROW][C]25[/C][C]-0.170898[/C][C]-1.3238[/C][C]0.095301[/C][/ROW]
[ROW][C]26[/C][C]-0.082745[/C][C]-0.6409[/C][C]0.262[/C][/ROW]
[ROW][C]27[/C][C]-0.094453[/C][C]-0.7316[/C][C]0.233622[/C][/ROW]
[ROW][C]28[/C][C]0.053794[/C][C]0.4167[/C][C]0.339198[/C][/ROW]
[ROW][C]29[/C][C]0.000355[/C][C]0.0027[/C][C]0.498908[/C][/ROW]
[ROW][C]30[/C][C]-0.02368[/C][C]-0.1834[/C][C]0.42754[/C][/ROW]
[ROW][C]31[/C][C]0.062268[/C][C]0.4823[/C][C]0.315666[/C][/ROW]
[ROW][C]32[/C][C]-0.027364[/C][C]-0.212[/C][C]0.416428[/C][/ROW]
[ROW][C]33[/C][C]0.001313[/C][C]0.0102[/C][C]0.495961[/C][/ROW]
[ROW][C]34[/C][C]0.240128[/C][C]1.86[/C][C]0.033893[/C][/ROW]
[ROW][C]35[/C][C]0.00108[/C][C]0.0084[/C][C]0.496676[/C][/ROW]
[ROW][C]36[/C][C]0.015547[/C][C]0.1204[/C][C]0.452275[/C][/ROW]
[ROW][C]37[/C][C]0.048555[/C][C]0.3761[/C][C]0.354082[/C][/ROW]
[ROW][C]38[/C][C]-0.10158[/C][C]-0.7868[/C][C]0.217237[/C][/ROW]
[ROW][C]39[/C][C]-0.08888[/C][C]-0.6885[/C][C]0.246907[/C][/ROW]
[ROW][C]40[/C][C]-0.014861[/C][C]-0.1151[/C][C]0.454371[/C][/ROW]
[ROW][C]41[/C][C]-0.047297[/C][C]-0.3664[/C][C]0.357692[/C][/ROW]
[ROW][C]42[/C][C]0.112471[/C][C]0.8712[/C][C]0.193559[/C][/ROW]
[ROW][C]43[/C][C]-0.083403[/C][C]-0.646[/C][C]0.260358[/C][/ROW]
[ROW][C]44[/C][C]0.041619[/C][C]0.3224[/C][C]0.374143[/C][/ROW]
[ROW][C]45[/C][C]0.075963[/C][C]0.5884[/C][C]0.279233[/C][/ROW]
[ROW][C]46[/C][C]-0.016946[/C][C]-0.1313[/C][C]0.448004[/C][/ROW]
[ROW][C]47[/C][C]-0.029356[/C][C]-0.2274[/C][C]0.410445[/C][/ROW]
[ROW][C]48[/C][C]-0.105913[/C][C]-0.8204[/C][C]0.207618[/C][/ROW]
[ROW][C]49[/C][C]-0.003268[/C][C]-0.0253[/C][C]0.489946[/C][/ROW]
[ROW][C]50[/C][C]-0.085029[/C][C]-0.6586[/C][C]0.256326[/C][/ROW]
[ROW][C]51[/C][C]0.041168[/C][C]0.3189[/C][C]0.375461[/C][/ROW]
[ROW][C]52[/C][C]-0.105216[/C][C]-0.815[/C][C]0.209148[/C][/ROW]
[ROW][C]53[/C][C]-0.034198[/C][C]-0.2649[/C][C]0.396[/C][/ROW]
[ROW][C]54[/C][C]-0.064116[/C][C]-0.4966[/C][C]0.310629[/C][/ROW]
[ROW][C]55[/C][C]0.048529[/C][C]0.3759[/C][C]0.354156[/C][/ROW]
[ROW][C]56[/C][C]0.016951[/C][C]0.1313[/C][C]0.447986[/C][/ROW]
[ROW][C]57[/C][C]-0.051595[/C][C]-0.3997[/C][C]0.345416[/C][/ROW]
[ROW][C]58[/C][C]-0.080131[/C][C]-0.6207[/C][C]0.268576[/C][/ROW]
[ROW][C]59[/C][C]0.072619[/C][C]0.5625[/C][C]0.287935[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68703&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68703&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
10.3367722.60860.005729
2-0.46969-3.63820.000286
3-0.31601-2.44780.008658
4-0.247163-1.91450.030163
50.0835540.64720.259984
60.2562571.9850.025863
70.0453590.35130.363279
80.0701560.54340.294425
90.0403940.31290.377724
10-0.005905-0.04570.481836
110.0094430.07310.470966
120.1501231.16290.124747
13-0.464009-3.59420.000329
140.1078610.83550.20338
150.0763820.59170.278154
16-0.000149-0.00120.499541
17-0.051079-0.39570.346882
18-0.017182-0.13310.447282
190.0980620.75960.225238
20-0.001474-0.01140.495464
21-0.049406-0.38270.351648
22-0.138893-1.07590.143148
230.0618840.47940.316714
240.0591420.45810.324262
25-0.170898-1.32380.095301
26-0.082745-0.64090.262
27-0.094453-0.73160.233622
280.0537940.41670.339198
290.0003550.00270.498908
30-0.02368-0.18340.42754
310.0622680.48230.315666
32-0.027364-0.2120.416428
330.0013130.01020.495961
340.2401281.860.033893
350.001080.00840.496676
360.0155470.12040.452275
370.0485550.37610.354082
38-0.10158-0.78680.217237
39-0.08888-0.68850.246907
40-0.014861-0.11510.454371
41-0.047297-0.36640.357692
420.1124710.87120.193559
43-0.083403-0.6460.260358
440.0416190.32240.374143
450.0759630.58840.279233
46-0.016946-0.13130.448004
47-0.029356-0.22740.410445
48-0.105913-0.82040.207618
49-0.003268-0.02530.489946
50-0.085029-0.65860.256326
510.0411680.31890.375461
52-0.105216-0.8150.209148
53-0.034198-0.26490.396
54-0.064116-0.49660.310629
550.0485290.37590.354156
560.0169510.13130.447986
57-0.051595-0.39970.345416
58-0.080131-0.62070.268576
590.0726190.56250.287935
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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')