Free Statistics

of Irreproducible Research!

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 computationSun, 27 Dec 2009 06:56:04 -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/27/t1261922235jse40686s9r1duh.htm/, Retrieved Fri, 03 May 2024 01:27:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70889, Retrieved Fri, 03 May 2024 01:27:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [test 3] [2007-10-13 09:57:27] [74be16979710d4c4e7c6647856088456]
- RMPD  [Standard Deviation-Mean Plot] [paper standard de...] [2008-12-10 13:47:28] [11edab5c4db3615abbf782b1c6e7cacf]
- RMPD      [(Partial) Autocorrelation Function] [paper ACF WLH] [2009-12-27 13:56:04] [1b03feaac1d41902024770a37504c07f] [Current]
Feedback Forum

Post a new message
Dataseries X:
401
394
372
334
320
334
400
427
423
395
373
377
391
398
393
375
371
364
400
406
407
397
389
394
399
401
396
392
384
370
380
376
378
376
373
374
379
376
371
375
360
338
352
344
330
334
333
343
350
341
320
302
287
304
370
385
365
333
313
330
367




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70889&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]4 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=70889&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70889&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7981556.23380
20.4489363.50630.000429
30.2139441.6710.049927
40.2300631.79680.038656
50.4186653.26990.000886
60.5660744.42122.1e-05
70.519884.06047.1e-05
80.366992.86630.002846
90.2397281.87230.032978
100.2029011.58470.059102
110.248831.94340.028291
120.2901762.26630.013495
130.2134371.6670.050321
140.1113320.86950.193984
150.0324290.25330.400452
160.0051470.04020.484033
170.0162530.12690.449703
180.0163990.12810.449252
19-0.042832-0.33450.369565
20-0.109753-0.85720.197345
21-0.15739-1.22930.111848
22-0.178744-1.3960.083882
23-0.168895-1.31910.096031
24-0.154857-1.20950.115574
25-0.186423-1.4560.075259
26-0.212251-1.65770.051253
27-0.219614-1.71520.045688
28-0.209965-1.63990.053089
29-0.194187-1.51670.06726
30-0.199084-1.55490.062572
31-0.244777-1.91180.030303
32-0.288433-2.25270.013942
33-0.29508-2.30460.012303
34-0.256828-2.00590.024654
35-0.193457-1.51090.067983
36-0.157237-1.22810.112071
37-0.19652-1.53490.064993
38-0.236381-1.84620.034859
39-0.22378-1.74780.042767
40-0.159952-1.24930.10817
41-0.091729-0.71640.238232
42-0.087639-0.68450.248133
43-0.170731-1.33340.093671
44-0.240903-1.88150.032338
45-0.213861-1.67030.049991
46-0.086888-0.67860.249975
470.0597540.46670.321192
480.1053120.82250.206995
490.0010610.00830.496707
50-0.145123-1.13340.130732
51-0.204932-1.60060.05732
52-0.132577-1.03550.152271
530.0061940.04840.480787
540.0962030.75140.22766
550.0698720.54570.293624
560.001410.0110.495625
57-0.047108-0.36790.357103
58-0.048673-0.38010.352578
59-0.022078-0.17240.431832
60-0.000461-0.00360.498568

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.798155 & 6.2338 & 0 \tabularnewline
2 & 0.448936 & 3.5063 & 0.000429 \tabularnewline
3 & 0.213944 & 1.671 & 0.049927 \tabularnewline
4 & 0.230063 & 1.7968 & 0.038656 \tabularnewline
5 & 0.418665 & 3.2699 & 0.000886 \tabularnewline
6 & 0.566074 & 4.4212 & 2.1e-05 \tabularnewline
7 & 0.51988 & 4.0604 & 7.1e-05 \tabularnewline
8 & 0.36699 & 2.8663 & 0.002846 \tabularnewline
9 & 0.239728 & 1.8723 & 0.032978 \tabularnewline
10 & 0.202901 & 1.5847 & 0.059102 \tabularnewline
11 & 0.24883 & 1.9434 & 0.028291 \tabularnewline
12 & 0.290176 & 2.2663 & 0.013495 \tabularnewline
13 & 0.213437 & 1.667 & 0.050321 \tabularnewline
14 & 0.111332 & 0.8695 & 0.193984 \tabularnewline
15 & 0.032429 & 0.2533 & 0.400452 \tabularnewline
16 & 0.005147 & 0.0402 & 0.484033 \tabularnewline
17 & 0.016253 & 0.1269 & 0.449703 \tabularnewline
18 & 0.016399 & 0.1281 & 0.449252 \tabularnewline
19 & -0.042832 & -0.3345 & 0.369565 \tabularnewline
20 & -0.109753 & -0.8572 & 0.197345 \tabularnewline
21 & -0.15739 & -1.2293 & 0.111848 \tabularnewline
22 & -0.178744 & -1.396 & 0.083882 \tabularnewline
23 & -0.168895 & -1.3191 & 0.096031 \tabularnewline
24 & -0.154857 & -1.2095 & 0.115574 \tabularnewline
25 & -0.186423 & -1.456 & 0.075259 \tabularnewline
26 & -0.212251 & -1.6577 & 0.051253 \tabularnewline
27 & -0.219614 & -1.7152 & 0.045688 \tabularnewline
28 & -0.209965 & -1.6399 & 0.053089 \tabularnewline
29 & -0.194187 & -1.5167 & 0.06726 \tabularnewline
30 & -0.199084 & -1.5549 & 0.062572 \tabularnewline
31 & -0.244777 & -1.9118 & 0.030303 \tabularnewline
32 & -0.288433 & -2.2527 & 0.013942 \tabularnewline
33 & -0.29508 & -2.3046 & 0.012303 \tabularnewline
34 & -0.256828 & -2.0059 & 0.024654 \tabularnewline
35 & -0.193457 & -1.5109 & 0.067983 \tabularnewline
36 & -0.157237 & -1.2281 & 0.112071 \tabularnewline
37 & -0.19652 & -1.5349 & 0.064993 \tabularnewline
38 & -0.236381 & -1.8462 & 0.034859 \tabularnewline
39 & -0.22378 & -1.7478 & 0.042767 \tabularnewline
40 & -0.159952 & -1.2493 & 0.10817 \tabularnewline
41 & -0.091729 & -0.7164 & 0.238232 \tabularnewline
42 & -0.087639 & -0.6845 & 0.248133 \tabularnewline
43 & -0.170731 & -1.3334 & 0.093671 \tabularnewline
44 & -0.240903 & -1.8815 & 0.032338 \tabularnewline
45 & -0.213861 & -1.6703 & 0.049991 \tabularnewline
46 & -0.086888 & -0.6786 & 0.249975 \tabularnewline
47 & 0.059754 & 0.4667 & 0.321192 \tabularnewline
48 & 0.105312 & 0.8225 & 0.206995 \tabularnewline
49 & 0.001061 & 0.0083 & 0.496707 \tabularnewline
50 & -0.145123 & -1.1334 & 0.130732 \tabularnewline
51 & -0.204932 & -1.6006 & 0.05732 \tabularnewline
52 & -0.132577 & -1.0355 & 0.152271 \tabularnewline
53 & 0.006194 & 0.0484 & 0.480787 \tabularnewline
54 & 0.096203 & 0.7514 & 0.22766 \tabularnewline
55 & 0.069872 & 0.5457 & 0.293624 \tabularnewline
56 & 0.00141 & 0.011 & 0.495625 \tabularnewline
57 & -0.047108 & -0.3679 & 0.357103 \tabularnewline
58 & -0.048673 & -0.3801 & 0.352578 \tabularnewline
59 & -0.022078 & -0.1724 & 0.431832 \tabularnewline
60 & -0.000461 & -0.0036 & 0.498568 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70889&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]0.798155[/C][C]6.2338[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.448936[/C][C]3.5063[/C][C]0.000429[/C][/ROW]
[ROW][C]3[/C][C]0.213944[/C][C]1.671[/C][C]0.049927[/C][/ROW]
[ROW][C]4[/C][C]0.230063[/C][C]1.7968[/C][C]0.038656[/C][/ROW]
[ROW][C]5[/C][C]0.418665[/C][C]3.2699[/C][C]0.000886[/C][/ROW]
[ROW][C]6[/C][C]0.566074[/C][C]4.4212[/C][C]2.1e-05[/C][/ROW]
[ROW][C]7[/C][C]0.51988[/C][C]4.0604[/C][C]7.1e-05[/C][/ROW]
[ROW][C]8[/C][C]0.36699[/C][C]2.8663[/C][C]0.002846[/C][/ROW]
[ROW][C]9[/C][C]0.239728[/C][C]1.8723[/C][C]0.032978[/C][/ROW]
[ROW][C]10[/C][C]0.202901[/C][C]1.5847[/C][C]0.059102[/C][/ROW]
[ROW][C]11[/C][C]0.24883[/C][C]1.9434[/C][C]0.028291[/C][/ROW]
[ROW][C]12[/C][C]0.290176[/C][C]2.2663[/C][C]0.013495[/C][/ROW]
[ROW][C]13[/C][C]0.213437[/C][C]1.667[/C][C]0.050321[/C][/ROW]
[ROW][C]14[/C][C]0.111332[/C][C]0.8695[/C][C]0.193984[/C][/ROW]
[ROW][C]15[/C][C]0.032429[/C][C]0.2533[/C][C]0.400452[/C][/ROW]
[ROW][C]16[/C][C]0.005147[/C][C]0.0402[/C][C]0.484033[/C][/ROW]
[ROW][C]17[/C][C]0.016253[/C][C]0.1269[/C][C]0.449703[/C][/ROW]
[ROW][C]18[/C][C]0.016399[/C][C]0.1281[/C][C]0.449252[/C][/ROW]
[ROW][C]19[/C][C]-0.042832[/C][C]-0.3345[/C][C]0.369565[/C][/ROW]
[ROW][C]20[/C][C]-0.109753[/C][C]-0.8572[/C][C]0.197345[/C][/ROW]
[ROW][C]21[/C][C]-0.15739[/C][C]-1.2293[/C][C]0.111848[/C][/ROW]
[ROW][C]22[/C][C]-0.178744[/C][C]-1.396[/C][C]0.083882[/C][/ROW]
[ROW][C]23[/C][C]-0.168895[/C][C]-1.3191[/C][C]0.096031[/C][/ROW]
[ROW][C]24[/C][C]-0.154857[/C][C]-1.2095[/C][C]0.115574[/C][/ROW]
[ROW][C]25[/C][C]-0.186423[/C][C]-1.456[/C][C]0.075259[/C][/ROW]
[ROW][C]26[/C][C]-0.212251[/C][C]-1.6577[/C][C]0.051253[/C][/ROW]
[ROW][C]27[/C][C]-0.219614[/C][C]-1.7152[/C][C]0.045688[/C][/ROW]
[ROW][C]28[/C][C]-0.209965[/C][C]-1.6399[/C][C]0.053089[/C][/ROW]
[ROW][C]29[/C][C]-0.194187[/C][C]-1.5167[/C][C]0.06726[/C][/ROW]
[ROW][C]30[/C][C]-0.199084[/C][C]-1.5549[/C][C]0.062572[/C][/ROW]
[ROW][C]31[/C][C]-0.244777[/C][C]-1.9118[/C][C]0.030303[/C][/ROW]
[ROW][C]32[/C][C]-0.288433[/C][C]-2.2527[/C][C]0.013942[/C][/ROW]
[ROW][C]33[/C][C]-0.29508[/C][C]-2.3046[/C][C]0.012303[/C][/ROW]
[ROW][C]34[/C][C]-0.256828[/C][C]-2.0059[/C][C]0.024654[/C][/ROW]
[ROW][C]35[/C][C]-0.193457[/C][C]-1.5109[/C][C]0.067983[/C][/ROW]
[ROW][C]36[/C][C]-0.157237[/C][C]-1.2281[/C][C]0.112071[/C][/ROW]
[ROW][C]37[/C][C]-0.19652[/C][C]-1.5349[/C][C]0.064993[/C][/ROW]
[ROW][C]38[/C][C]-0.236381[/C][C]-1.8462[/C][C]0.034859[/C][/ROW]
[ROW][C]39[/C][C]-0.22378[/C][C]-1.7478[/C][C]0.042767[/C][/ROW]
[ROW][C]40[/C][C]-0.159952[/C][C]-1.2493[/C][C]0.10817[/C][/ROW]
[ROW][C]41[/C][C]-0.091729[/C][C]-0.7164[/C][C]0.238232[/C][/ROW]
[ROW][C]42[/C][C]-0.087639[/C][C]-0.6845[/C][C]0.248133[/C][/ROW]
[ROW][C]43[/C][C]-0.170731[/C][C]-1.3334[/C][C]0.093671[/C][/ROW]
[ROW][C]44[/C][C]-0.240903[/C][C]-1.8815[/C][C]0.032338[/C][/ROW]
[ROW][C]45[/C][C]-0.213861[/C][C]-1.6703[/C][C]0.049991[/C][/ROW]
[ROW][C]46[/C][C]-0.086888[/C][C]-0.6786[/C][C]0.249975[/C][/ROW]
[ROW][C]47[/C][C]0.059754[/C][C]0.4667[/C][C]0.321192[/C][/ROW]
[ROW][C]48[/C][C]0.105312[/C][C]0.8225[/C][C]0.206995[/C][/ROW]
[ROW][C]49[/C][C]0.001061[/C][C]0.0083[/C][C]0.496707[/C][/ROW]
[ROW][C]50[/C][C]-0.145123[/C][C]-1.1334[/C][C]0.130732[/C][/ROW]
[ROW][C]51[/C][C]-0.204932[/C][C]-1.6006[/C][C]0.05732[/C][/ROW]
[ROW][C]52[/C][C]-0.132577[/C][C]-1.0355[/C][C]0.152271[/C][/ROW]
[ROW][C]53[/C][C]0.006194[/C][C]0.0484[/C][C]0.480787[/C][/ROW]
[ROW][C]54[/C][C]0.096203[/C][C]0.7514[/C][C]0.22766[/C][/ROW]
[ROW][C]55[/C][C]0.069872[/C][C]0.5457[/C][C]0.293624[/C][/ROW]
[ROW][C]56[/C][C]0.00141[/C][C]0.011[/C][C]0.495625[/C][/ROW]
[ROW][C]57[/C][C]-0.047108[/C][C]-0.3679[/C][C]0.357103[/C][/ROW]
[ROW][C]58[/C][C]-0.048673[/C][C]-0.3801[/C][C]0.352578[/C][/ROW]
[ROW][C]59[/C][C]-0.022078[/C][C]-0.1724[/C][C]0.431832[/C][/ROW]
[ROW][C]60[/C][C]-0.000461[/C][C]-0.0036[/C][C]0.498568[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70889&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70889&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
10.7981556.23380
20.4489363.50630.000429
30.2139441.6710.049927
40.2300631.79680.038656
50.4186653.26990.000886
60.5660744.42122.1e-05
70.519884.06047.1e-05
80.366992.86630.002846
90.2397281.87230.032978
100.2029011.58470.059102
110.248831.94340.028291
120.2901762.26630.013495
130.2134371.6670.050321
140.1113320.86950.193984
150.0324290.25330.400452
160.0051470.04020.484033
170.0162530.12690.449703
180.0163990.12810.449252
19-0.042832-0.33450.369565
20-0.109753-0.85720.197345
21-0.15739-1.22930.111848
22-0.178744-1.3960.083882
23-0.168895-1.31910.096031
24-0.154857-1.20950.115574
25-0.186423-1.4560.075259
26-0.212251-1.65770.051253
27-0.219614-1.71520.045688
28-0.209965-1.63990.053089
29-0.194187-1.51670.06726
30-0.199084-1.55490.062572
31-0.244777-1.91180.030303
32-0.288433-2.25270.013942
33-0.29508-2.30460.012303
34-0.256828-2.00590.024654
35-0.193457-1.51090.067983
36-0.157237-1.22810.112071
37-0.19652-1.53490.064993
38-0.236381-1.84620.034859
39-0.22378-1.74780.042767
40-0.159952-1.24930.10817
41-0.091729-0.71640.238232
42-0.087639-0.68450.248133
43-0.170731-1.33340.093671
44-0.240903-1.88150.032338
45-0.213861-1.67030.049991
46-0.086888-0.67860.249975
470.0597540.46670.321192
480.1053120.82250.206995
490.0010610.00830.496707
50-0.145123-1.13340.130732
51-0.204932-1.60060.05732
52-0.132577-1.03550.152271
530.0061940.04840.480787
540.0962030.75140.22766
550.0698720.54570.293624
560.001410.0110.495625
57-0.047108-0.36790.357103
58-0.048673-0.38010.352578
59-0.022078-0.17240.431832
60-0.000461-0.00360.498568







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7981556.23380
2-0.518301-4.04817.4e-05
30.3149062.45950.008382
40.370262.89180.002651
50.2038061.59180.058303
6-0.024466-0.19110.424547
7-0.106614-0.83270.204136
80.2196581.71560.045657
9-0.006655-0.0520.479357
10-0.147189-1.14960.127401
110.0296070.23120.408951
12-0.006917-0.0540.478548
13-0.33047-2.5810.006135
140.1854971.44880.07626
15-0.156871-1.22520.112605
16-0.128104-1.00050.160505
17-0.055814-0.43590.332216
18-3e-0600.49999
19-0.097821-0.7640.223905
20-0.058748-0.45880.323992
21-0.024826-0.19390.42345
220.0079190.06190.475441
23-0.029118-0.22740.410429
240.0119690.09350.462914
25-0.004048-0.03160.48744
260.0499540.39020.34889
270.0756670.5910.27836
28-0.00129-0.01010.495998
29-0.003983-0.03110.487641
30-0.016093-0.12570.450194
31-0.034416-0.26880.394497
32-0.104576-0.81680.20862
330.035050.27370.392601
340.0229580.17930.429147
35-0.064118-0.50080.309166
36-0.067668-0.52850.299533
37-0.043957-0.34330.36627
380.1171180.91470.18197
390.027410.21410.4156
40-0.046006-0.35930.360299
410.0074150.05790.477004
42-0.065623-0.51250.305065
43-0.137079-1.07060.144278
440.0781680.61050.271895
450.0790110.61710.269733
460.0755440.590.278678
470.020140.15730.437764
48-0.040078-0.3130.377666
49-0.021582-0.16860.433351
50-0.119682-0.93470.176802
51-0.012324-0.09630.461817
520.0070250.05490.478212
53-0.103888-0.81140.210148
54-0.002311-0.0180.492831
550.0391260.30560.380482
560.063920.49920.309708
57-0.116195-0.90750.183853
58-0.072024-0.56250.287911
59-0.009689-0.07570.469962
600.0470470.36740.357278

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.798155 & 6.2338 & 0 \tabularnewline
2 & -0.518301 & -4.0481 & 7.4e-05 \tabularnewline
3 & 0.314906 & 2.4595 & 0.008382 \tabularnewline
4 & 0.37026 & 2.8918 & 0.002651 \tabularnewline
5 & 0.203806 & 1.5918 & 0.058303 \tabularnewline
6 & -0.024466 & -0.1911 & 0.424547 \tabularnewline
7 & -0.106614 & -0.8327 & 0.204136 \tabularnewline
8 & 0.219658 & 1.7156 & 0.045657 \tabularnewline
9 & -0.006655 & -0.052 & 0.479357 \tabularnewline
10 & -0.147189 & -1.1496 & 0.127401 \tabularnewline
11 & 0.029607 & 0.2312 & 0.408951 \tabularnewline
12 & -0.006917 & -0.054 & 0.478548 \tabularnewline
13 & -0.33047 & -2.581 & 0.006135 \tabularnewline
14 & 0.185497 & 1.4488 & 0.07626 \tabularnewline
15 & -0.156871 & -1.2252 & 0.112605 \tabularnewline
16 & -0.128104 & -1.0005 & 0.160505 \tabularnewline
17 & -0.055814 & -0.4359 & 0.332216 \tabularnewline
18 & -3e-06 & 0 & 0.49999 \tabularnewline
19 & -0.097821 & -0.764 & 0.223905 \tabularnewline
20 & -0.058748 & -0.4588 & 0.323992 \tabularnewline
21 & -0.024826 & -0.1939 & 0.42345 \tabularnewline
22 & 0.007919 & 0.0619 & 0.475441 \tabularnewline
23 & -0.029118 & -0.2274 & 0.410429 \tabularnewline
24 & 0.011969 & 0.0935 & 0.462914 \tabularnewline
25 & -0.004048 & -0.0316 & 0.48744 \tabularnewline
26 & 0.049954 & 0.3902 & 0.34889 \tabularnewline
27 & 0.075667 & 0.591 & 0.27836 \tabularnewline
28 & -0.00129 & -0.0101 & 0.495998 \tabularnewline
29 & -0.003983 & -0.0311 & 0.487641 \tabularnewline
30 & -0.016093 & -0.1257 & 0.450194 \tabularnewline
31 & -0.034416 & -0.2688 & 0.394497 \tabularnewline
32 & -0.104576 & -0.8168 & 0.20862 \tabularnewline
33 & 0.03505 & 0.2737 & 0.392601 \tabularnewline
34 & 0.022958 & 0.1793 & 0.429147 \tabularnewline
35 & -0.064118 & -0.5008 & 0.309166 \tabularnewline
36 & -0.067668 & -0.5285 & 0.299533 \tabularnewline
37 & -0.043957 & -0.3433 & 0.36627 \tabularnewline
38 & 0.117118 & 0.9147 & 0.18197 \tabularnewline
39 & 0.02741 & 0.2141 & 0.4156 \tabularnewline
40 & -0.046006 & -0.3593 & 0.360299 \tabularnewline
41 & 0.007415 & 0.0579 & 0.477004 \tabularnewline
42 & -0.065623 & -0.5125 & 0.305065 \tabularnewline
43 & -0.137079 & -1.0706 & 0.144278 \tabularnewline
44 & 0.078168 & 0.6105 & 0.271895 \tabularnewline
45 & 0.079011 & 0.6171 & 0.269733 \tabularnewline
46 & 0.075544 & 0.59 & 0.278678 \tabularnewline
47 & 0.02014 & 0.1573 & 0.437764 \tabularnewline
48 & -0.040078 & -0.313 & 0.377666 \tabularnewline
49 & -0.021582 & -0.1686 & 0.433351 \tabularnewline
50 & -0.119682 & -0.9347 & 0.176802 \tabularnewline
51 & -0.012324 & -0.0963 & 0.461817 \tabularnewline
52 & 0.007025 & 0.0549 & 0.478212 \tabularnewline
53 & -0.103888 & -0.8114 & 0.210148 \tabularnewline
54 & -0.002311 & -0.018 & 0.492831 \tabularnewline
55 & 0.039126 & 0.3056 & 0.380482 \tabularnewline
56 & 0.06392 & 0.4992 & 0.309708 \tabularnewline
57 & -0.116195 & -0.9075 & 0.183853 \tabularnewline
58 & -0.072024 & -0.5625 & 0.287911 \tabularnewline
59 & -0.009689 & -0.0757 & 0.469962 \tabularnewline
60 & 0.047047 & 0.3674 & 0.357278 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70889&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]0.798155[/C][C]6.2338[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.518301[/C][C]-4.0481[/C][C]7.4e-05[/C][/ROW]
[ROW][C]3[/C][C]0.314906[/C][C]2.4595[/C][C]0.008382[/C][/ROW]
[ROW][C]4[/C][C]0.37026[/C][C]2.8918[/C][C]0.002651[/C][/ROW]
[ROW][C]5[/C][C]0.203806[/C][C]1.5918[/C][C]0.058303[/C][/ROW]
[ROW][C]6[/C][C]-0.024466[/C][C]-0.1911[/C][C]0.424547[/C][/ROW]
[ROW][C]7[/C][C]-0.106614[/C][C]-0.8327[/C][C]0.204136[/C][/ROW]
[ROW][C]8[/C][C]0.219658[/C][C]1.7156[/C][C]0.045657[/C][/ROW]
[ROW][C]9[/C][C]-0.006655[/C][C]-0.052[/C][C]0.479357[/C][/ROW]
[ROW][C]10[/C][C]-0.147189[/C][C]-1.1496[/C][C]0.127401[/C][/ROW]
[ROW][C]11[/C][C]0.029607[/C][C]0.2312[/C][C]0.408951[/C][/ROW]
[ROW][C]12[/C][C]-0.006917[/C][C]-0.054[/C][C]0.478548[/C][/ROW]
[ROW][C]13[/C][C]-0.33047[/C][C]-2.581[/C][C]0.006135[/C][/ROW]
[ROW][C]14[/C][C]0.185497[/C][C]1.4488[/C][C]0.07626[/C][/ROW]
[ROW][C]15[/C][C]-0.156871[/C][C]-1.2252[/C][C]0.112605[/C][/ROW]
[ROW][C]16[/C][C]-0.128104[/C][C]-1.0005[/C][C]0.160505[/C][/ROW]
[ROW][C]17[/C][C]-0.055814[/C][C]-0.4359[/C][C]0.332216[/C][/ROW]
[ROW][C]18[/C][C]-3e-06[/C][C]0[/C][C]0.49999[/C][/ROW]
[ROW][C]19[/C][C]-0.097821[/C][C]-0.764[/C][C]0.223905[/C][/ROW]
[ROW][C]20[/C][C]-0.058748[/C][C]-0.4588[/C][C]0.323992[/C][/ROW]
[ROW][C]21[/C][C]-0.024826[/C][C]-0.1939[/C][C]0.42345[/C][/ROW]
[ROW][C]22[/C][C]0.007919[/C][C]0.0619[/C][C]0.475441[/C][/ROW]
[ROW][C]23[/C][C]-0.029118[/C][C]-0.2274[/C][C]0.410429[/C][/ROW]
[ROW][C]24[/C][C]0.011969[/C][C]0.0935[/C][C]0.462914[/C][/ROW]
[ROW][C]25[/C][C]-0.004048[/C][C]-0.0316[/C][C]0.48744[/C][/ROW]
[ROW][C]26[/C][C]0.049954[/C][C]0.3902[/C][C]0.34889[/C][/ROW]
[ROW][C]27[/C][C]0.075667[/C][C]0.591[/C][C]0.27836[/C][/ROW]
[ROW][C]28[/C][C]-0.00129[/C][C]-0.0101[/C][C]0.495998[/C][/ROW]
[ROW][C]29[/C][C]-0.003983[/C][C]-0.0311[/C][C]0.487641[/C][/ROW]
[ROW][C]30[/C][C]-0.016093[/C][C]-0.1257[/C][C]0.450194[/C][/ROW]
[ROW][C]31[/C][C]-0.034416[/C][C]-0.2688[/C][C]0.394497[/C][/ROW]
[ROW][C]32[/C][C]-0.104576[/C][C]-0.8168[/C][C]0.20862[/C][/ROW]
[ROW][C]33[/C][C]0.03505[/C][C]0.2737[/C][C]0.392601[/C][/ROW]
[ROW][C]34[/C][C]0.022958[/C][C]0.1793[/C][C]0.429147[/C][/ROW]
[ROW][C]35[/C][C]-0.064118[/C][C]-0.5008[/C][C]0.309166[/C][/ROW]
[ROW][C]36[/C][C]-0.067668[/C][C]-0.5285[/C][C]0.299533[/C][/ROW]
[ROW][C]37[/C][C]-0.043957[/C][C]-0.3433[/C][C]0.36627[/C][/ROW]
[ROW][C]38[/C][C]0.117118[/C][C]0.9147[/C][C]0.18197[/C][/ROW]
[ROW][C]39[/C][C]0.02741[/C][C]0.2141[/C][C]0.4156[/C][/ROW]
[ROW][C]40[/C][C]-0.046006[/C][C]-0.3593[/C][C]0.360299[/C][/ROW]
[ROW][C]41[/C][C]0.007415[/C][C]0.0579[/C][C]0.477004[/C][/ROW]
[ROW][C]42[/C][C]-0.065623[/C][C]-0.5125[/C][C]0.305065[/C][/ROW]
[ROW][C]43[/C][C]-0.137079[/C][C]-1.0706[/C][C]0.144278[/C][/ROW]
[ROW][C]44[/C][C]0.078168[/C][C]0.6105[/C][C]0.271895[/C][/ROW]
[ROW][C]45[/C][C]0.079011[/C][C]0.6171[/C][C]0.269733[/C][/ROW]
[ROW][C]46[/C][C]0.075544[/C][C]0.59[/C][C]0.278678[/C][/ROW]
[ROW][C]47[/C][C]0.02014[/C][C]0.1573[/C][C]0.437764[/C][/ROW]
[ROW][C]48[/C][C]-0.040078[/C][C]-0.313[/C][C]0.377666[/C][/ROW]
[ROW][C]49[/C][C]-0.021582[/C][C]-0.1686[/C][C]0.433351[/C][/ROW]
[ROW][C]50[/C][C]-0.119682[/C][C]-0.9347[/C][C]0.176802[/C][/ROW]
[ROW][C]51[/C][C]-0.012324[/C][C]-0.0963[/C][C]0.461817[/C][/ROW]
[ROW][C]52[/C][C]0.007025[/C][C]0.0549[/C][C]0.478212[/C][/ROW]
[ROW][C]53[/C][C]-0.103888[/C][C]-0.8114[/C][C]0.210148[/C][/ROW]
[ROW][C]54[/C][C]-0.002311[/C][C]-0.018[/C][C]0.492831[/C][/ROW]
[ROW][C]55[/C][C]0.039126[/C][C]0.3056[/C][C]0.380482[/C][/ROW]
[ROW][C]56[/C][C]0.06392[/C][C]0.4992[/C][C]0.309708[/C][/ROW]
[ROW][C]57[/C][C]-0.116195[/C][C]-0.9075[/C][C]0.183853[/C][/ROW]
[ROW][C]58[/C][C]-0.072024[/C][C]-0.5625[/C][C]0.287911[/C][/ROW]
[ROW][C]59[/C][C]-0.009689[/C][C]-0.0757[/C][C]0.469962[/C][/ROW]
[ROW][C]60[/C][C]0.047047[/C][C]0.3674[/C][C]0.357278[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70889&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70889&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
10.7981556.23380
2-0.518301-4.04817.4e-05
30.3149062.45950.008382
40.370262.89180.002651
50.2038061.59180.058303
6-0.024466-0.19110.424547
7-0.106614-0.83270.204136
80.2196581.71560.045657
9-0.006655-0.0520.479357
10-0.147189-1.14960.127401
110.0296070.23120.408951
12-0.006917-0.0540.478548
13-0.33047-2.5810.006135
140.1854971.44880.07626
15-0.156871-1.22520.112605
16-0.128104-1.00050.160505
17-0.055814-0.43590.332216
18-3e-0600.49999
19-0.097821-0.7640.223905
20-0.058748-0.45880.323992
21-0.024826-0.19390.42345
220.0079190.06190.475441
23-0.029118-0.22740.410429
240.0119690.09350.462914
25-0.004048-0.03160.48744
260.0499540.39020.34889
270.0756670.5910.27836
28-0.00129-0.01010.495998
29-0.003983-0.03110.487641
30-0.016093-0.12570.450194
31-0.034416-0.26880.394497
32-0.104576-0.81680.20862
330.035050.27370.392601
340.0229580.17930.429147
35-0.064118-0.50080.309166
36-0.067668-0.52850.299533
37-0.043957-0.34330.36627
380.1171180.91470.18197
390.027410.21410.4156
40-0.046006-0.35930.360299
410.0074150.05790.477004
42-0.065623-0.51250.305065
43-0.137079-1.07060.144278
440.0781680.61050.271895
450.0790110.61710.269733
460.0755440.590.278678
470.020140.15730.437764
48-0.040078-0.3130.377666
49-0.021582-0.16860.433351
50-0.119682-0.93470.176802
51-0.012324-0.09630.461817
520.0070250.05490.478212
53-0.103888-0.81140.210148
54-0.002311-0.0180.492831
550.0391260.30560.380482
560.063920.49920.309708
57-0.116195-0.90750.183853
58-0.072024-0.56250.287911
59-0.009689-0.07570.469962
600.0470470.36740.357278



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