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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, 18 Dec 2010 13:59:09 +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/18/t1292680655ztpmgsfh38wencn.htm/, Retrieved Tue, 30 Apr 2024 04:05:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111970, Retrieved Tue, 30 Apr 2024 04:05:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [(partial) autocor...] [2009-12-09 13:20:29] [f7fc9270f813d017f9fa5b506fdc7682]
-   P   [(Partial) Autocorrelation Function] [autocorrelation] [2009-12-09 13:36:40] [f7fc9270f813d017f9fa5b506fdc7682]
-   PD      [(Partial) Autocorrelation Function] [autocorrelation o...] [2010-12-18 13:59:09] [8f110cf3e3846d42560df9b5835185a6] [Current]
-   P         [(Partial) Autocorrelation Function] [differentiatie va...] [2010-12-21 11:53:47] [a8a0ff0853b70f438be515083758c362]
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Dataseries X:
78.33
78.21
78.94
77.94
77.31
75.75
77.73
77.90
77.45
77.46
77.97
77.23
76.56
76.70
76.51
76.03
76.69
76.38
76.80
76.63
77.17
78.63
78.89
76.94
77.50
79.27
79.77
78.62
78.60
77.88
78.71
79.27
80.12
81.12
81.48
82.81
82.39
82.41
82.20
81.99
81.61
83.51
84.05
82.99
83.54
84.44
84.24
83.88
84.17
84.59
84.76
85.14
85.22
84.77
84.50
84.56
83.79
83.96
84.80
84.89
84.78
84.80
84.44
84.65
84.22
84.08
85.29
85.00
84.63
84.92
84.61
84.50
84.29
84.50
84.41
84.71
84.21
83.86
84.40
83.71
84.42
85.26
85.08
85.65
85.74
85.89
86.08
85.49
85.97
85.84
86.72
85.42
83.87
85.45
85.35
84.27
83.13
83.79
83.70
83.76
83.47
83.78
84.83
84.43
84.90
85.36
85.49
85.29




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111970&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111970&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.96494910.0280
20.9322539.68830
30.9164249.52380
40.8967899.31970
50.8666069.0060
60.8312478.63860
70.8105538.42350
80.7898778.20860
90.7640547.94030
100.7345857.6340
110.7072617.35010
120.6800957.06780
130.6447046.70
140.6117426.35740
150.5772195.99860
160.541115.62340
170.4992345.18821e-06
180.4539834.71794e-06
190.4164764.32821.7e-05
200.3741763.88868.7e-05
210.3303613.43320.000423
220.2964273.08060.001311
230.2679892.7850.003161
240.23412.43280.008312
250.192992.00560.023699
260.1578771.64070.051884
270.1268671.31840.095073
280.093710.97390.16615
290.062030.64460.260264
300.0284960.29610.383847
310.005380.05590.477757
32-0.018573-0.1930.423653
33-0.040354-0.41940.33789
34-0.059948-0.6230.2673
35-0.075809-0.78780.21626
36-0.090212-0.93750.175293
37-0.108516-1.12770.130966
38-0.119599-1.24290.108297
39-0.131425-1.36580.087418
40-0.148771-1.54610.062506
41-0.16729-1.73850.042484
42-0.179384-1.86420.032503
43-0.188182-1.95560.026545
44-0.199099-2.06910.020462
45-0.209329-2.17540.01589
46-0.219349-2.27950.0123
47-0.226106-2.34980.010301
48-0.23079-2.39840.00909

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.964949 & 10.028 & 0 \tabularnewline
2 & 0.932253 & 9.6883 & 0 \tabularnewline
3 & 0.916424 & 9.5238 & 0 \tabularnewline
4 & 0.896789 & 9.3197 & 0 \tabularnewline
5 & 0.866606 & 9.006 & 0 \tabularnewline
6 & 0.831247 & 8.6386 & 0 \tabularnewline
7 & 0.810553 & 8.4235 & 0 \tabularnewline
8 & 0.789877 & 8.2086 & 0 \tabularnewline
9 & 0.764054 & 7.9403 & 0 \tabularnewline
10 & 0.734585 & 7.634 & 0 \tabularnewline
11 & 0.707261 & 7.3501 & 0 \tabularnewline
12 & 0.680095 & 7.0678 & 0 \tabularnewline
13 & 0.644704 & 6.7 & 0 \tabularnewline
14 & 0.611742 & 6.3574 & 0 \tabularnewline
15 & 0.577219 & 5.9986 & 0 \tabularnewline
16 & 0.54111 & 5.6234 & 0 \tabularnewline
17 & 0.499234 & 5.1882 & 1e-06 \tabularnewline
18 & 0.453983 & 4.7179 & 4e-06 \tabularnewline
19 & 0.416476 & 4.3282 & 1.7e-05 \tabularnewline
20 & 0.374176 & 3.8886 & 8.7e-05 \tabularnewline
21 & 0.330361 & 3.4332 & 0.000423 \tabularnewline
22 & 0.296427 & 3.0806 & 0.001311 \tabularnewline
23 & 0.267989 & 2.785 & 0.003161 \tabularnewline
24 & 0.2341 & 2.4328 & 0.008312 \tabularnewline
25 & 0.19299 & 2.0056 & 0.023699 \tabularnewline
26 & 0.157877 & 1.6407 & 0.051884 \tabularnewline
27 & 0.126867 & 1.3184 & 0.095073 \tabularnewline
28 & 0.09371 & 0.9739 & 0.16615 \tabularnewline
29 & 0.06203 & 0.6446 & 0.260264 \tabularnewline
30 & 0.028496 & 0.2961 & 0.383847 \tabularnewline
31 & 0.00538 & 0.0559 & 0.477757 \tabularnewline
32 & -0.018573 & -0.193 & 0.423653 \tabularnewline
33 & -0.040354 & -0.4194 & 0.33789 \tabularnewline
34 & -0.059948 & -0.623 & 0.2673 \tabularnewline
35 & -0.075809 & -0.7878 & 0.21626 \tabularnewline
36 & -0.090212 & -0.9375 & 0.175293 \tabularnewline
37 & -0.108516 & -1.1277 & 0.130966 \tabularnewline
38 & -0.119599 & -1.2429 & 0.108297 \tabularnewline
39 & -0.131425 & -1.3658 & 0.087418 \tabularnewline
40 & -0.148771 & -1.5461 & 0.062506 \tabularnewline
41 & -0.16729 & -1.7385 & 0.042484 \tabularnewline
42 & -0.179384 & -1.8642 & 0.032503 \tabularnewline
43 & -0.188182 & -1.9556 & 0.026545 \tabularnewline
44 & -0.199099 & -2.0691 & 0.020462 \tabularnewline
45 & -0.209329 & -2.1754 & 0.01589 \tabularnewline
46 & -0.219349 & -2.2795 & 0.0123 \tabularnewline
47 & -0.226106 & -2.3498 & 0.010301 \tabularnewline
48 & -0.23079 & -2.3984 & 0.00909 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111970&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]0.964949[/C][C]10.028[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.932253[/C][C]9.6883[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.916424[/C][C]9.5238[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.896789[/C][C]9.3197[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.866606[/C][C]9.006[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.831247[/C][C]8.6386[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.810553[/C][C]8.4235[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.789877[/C][C]8.2086[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.764054[/C][C]7.9403[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.734585[/C][C]7.634[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.707261[/C][C]7.3501[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.680095[/C][C]7.0678[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.644704[/C][C]6.7[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.611742[/C][C]6.3574[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.577219[/C][C]5.9986[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.54111[/C][C]5.6234[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.499234[/C][C]5.1882[/C][C]1e-06[/C][/ROW]
[ROW][C]18[/C][C]0.453983[/C][C]4.7179[/C][C]4e-06[/C][/ROW]
[ROW][C]19[/C][C]0.416476[/C][C]4.3282[/C][C]1.7e-05[/C][/ROW]
[ROW][C]20[/C][C]0.374176[/C][C]3.8886[/C][C]8.7e-05[/C][/ROW]
[ROW][C]21[/C][C]0.330361[/C][C]3.4332[/C][C]0.000423[/C][/ROW]
[ROW][C]22[/C][C]0.296427[/C][C]3.0806[/C][C]0.001311[/C][/ROW]
[ROW][C]23[/C][C]0.267989[/C][C]2.785[/C][C]0.003161[/C][/ROW]
[ROW][C]24[/C][C]0.2341[/C][C]2.4328[/C][C]0.008312[/C][/ROW]
[ROW][C]25[/C][C]0.19299[/C][C]2.0056[/C][C]0.023699[/C][/ROW]
[ROW][C]26[/C][C]0.157877[/C][C]1.6407[/C][C]0.051884[/C][/ROW]
[ROW][C]27[/C][C]0.126867[/C][C]1.3184[/C][C]0.095073[/C][/ROW]
[ROW][C]28[/C][C]0.09371[/C][C]0.9739[/C][C]0.16615[/C][/ROW]
[ROW][C]29[/C][C]0.06203[/C][C]0.6446[/C][C]0.260264[/C][/ROW]
[ROW][C]30[/C][C]0.028496[/C][C]0.2961[/C][C]0.383847[/C][/ROW]
[ROW][C]31[/C][C]0.00538[/C][C]0.0559[/C][C]0.477757[/C][/ROW]
[ROW][C]32[/C][C]-0.018573[/C][C]-0.193[/C][C]0.423653[/C][/ROW]
[ROW][C]33[/C][C]-0.040354[/C][C]-0.4194[/C][C]0.33789[/C][/ROW]
[ROW][C]34[/C][C]-0.059948[/C][C]-0.623[/C][C]0.2673[/C][/ROW]
[ROW][C]35[/C][C]-0.075809[/C][C]-0.7878[/C][C]0.21626[/C][/ROW]
[ROW][C]36[/C][C]-0.090212[/C][C]-0.9375[/C][C]0.175293[/C][/ROW]
[ROW][C]37[/C][C]-0.108516[/C][C]-1.1277[/C][C]0.130966[/C][/ROW]
[ROW][C]38[/C][C]-0.119599[/C][C]-1.2429[/C][C]0.108297[/C][/ROW]
[ROW][C]39[/C][C]-0.131425[/C][C]-1.3658[/C][C]0.087418[/C][/ROW]
[ROW][C]40[/C][C]-0.148771[/C][C]-1.5461[/C][C]0.062506[/C][/ROW]
[ROW][C]41[/C][C]-0.16729[/C][C]-1.7385[/C][C]0.042484[/C][/ROW]
[ROW][C]42[/C][C]-0.179384[/C][C]-1.8642[/C][C]0.032503[/C][/ROW]
[ROW][C]43[/C][C]-0.188182[/C][C]-1.9556[/C][C]0.026545[/C][/ROW]
[ROW][C]44[/C][C]-0.199099[/C][C]-2.0691[/C][C]0.020462[/C][/ROW]
[ROW][C]45[/C][C]-0.209329[/C][C]-2.1754[/C][C]0.01589[/C][/ROW]
[ROW][C]46[/C][C]-0.219349[/C][C]-2.2795[/C][C]0.0123[/C][/ROW]
[ROW][C]47[/C][C]-0.226106[/C][C]-2.3498[/C][C]0.010301[/C][/ROW]
[ROW][C]48[/C][C]-0.23079[/C][C]-2.3984[/C][C]0.00909[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111970&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111970&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
10.96494910.0280
20.9322539.68830
30.9164249.52380
40.8967899.31970
50.8666069.0060
60.8312478.63860
70.8105538.42350
80.7898778.20860
90.7640547.94030
100.7345857.6340
110.7072617.35010
120.6800957.06780
130.6447046.70
140.6117426.35740
150.5772195.99860
160.541115.62340
170.4992345.18821e-06
180.4539834.71794e-06
190.4164764.32821.7e-05
200.3741763.88868.7e-05
210.3303613.43320.000423
220.2964273.08060.001311
230.2679892.7850.003161
240.23412.43280.008312
250.192992.00560.023699
260.1578771.64070.051884
270.1268671.31840.095073
280.093710.97390.16615
290.062030.64460.260264
300.0284960.29610.383847
310.005380.05590.477757
32-0.018573-0.1930.423653
33-0.040354-0.41940.33789
34-0.059948-0.6230.2673
35-0.075809-0.78780.21626
36-0.090212-0.93750.175293
37-0.108516-1.12770.130966
38-0.119599-1.24290.108297
39-0.131425-1.36580.087418
40-0.148771-1.54610.062506
41-0.16729-1.73850.042484
42-0.179384-1.86420.032503
43-0.188182-1.95560.026545
44-0.199099-2.06910.020462
45-0.209329-2.17540.01589
46-0.219349-2.27950.0123
47-0.226106-2.34980.010301
48-0.23079-2.39840.00909







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.96494910.0280
20.0163580.170.432666
30.229152.38140.009499
4-0.049272-0.51210.304831
5-0.114484-1.18980.118375
6-0.128243-1.33270.092711
70.1447241.5040.067748
8-0.028075-0.29180.385515
90.0193480.20110.42051
10-0.081056-0.84240.200725
11-0.027918-0.29010.386135
12-0.073082-0.75950.224606
13-0.096541-1.00330.158983
140.0140980.14650.441896
15-0.080488-0.83650.202372
16-0.03708-0.38530.350371
17-0.12437-1.29250.099473
18-0.089707-0.93230.176641
190.0196140.20380.419432
20-0.087036-0.90450.183869
21-0.008804-0.09150.463634
220.1164841.21050.114358
230.0467450.48580.31405
24-0.058009-0.60280.273937
25-0.08821-0.91670.180671
26-0.020454-0.21260.416033
27-0.003751-0.0390.48449
280.0250260.26010.397651
290.0931970.96850.167472
30-0.069298-0.72020.236489
310.0990081.02890.152907
32-0.039903-0.41470.339597
330.0850730.88410.189301
34-0.005607-0.05830.476822
350.0839370.87230.192491
36-0.037354-0.38820.349319
37-0.015841-0.16460.434774
380.0203070.2110.416628
39-0.054328-0.56460.286759
40-0.08172-0.84930.198809
41-0.050052-0.52020.302012
420.0425060.44170.329784
43-0.020991-0.21810.413862
440.0584330.60730.27248
45-0.074913-0.77850.218983
46-0.09476-0.98480.163467
47-0.045441-0.47220.318856
480.020180.20970.417141

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.964949 & 10.028 & 0 \tabularnewline
2 & 0.016358 & 0.17 & 0.432666 \tabularnewline
3 & 0.22915 & 2.3814 & 0.009499 \tabularnewline
4 & -0.049272 & -0.5121 & 0.304831 \tabularnewline
5 & -0.114484 & -1.1898 & 0.118375 \tabularnewline
6 & -0.128243 & -1.3327 & 0.092711 \tabularnewline
7 & 0.144724 & 1.504 & 0.067748 \tabularnewline
8 & -0.028075 & -0.2918 & 0.385515 \tabularnewline
9 & 0.019348 & 0.2011 & 0.42051 \tabularnewline
10 & -0.081056 & -0.8424 & 0.200725 \tabularnewline
11 & -0.027918 & -0.2901 & 0.386135 \tabularnewline
12 & -0.073082 & -0.7595 & 0.224606 \tabularnewline
13 & -0.096541 & -1.0033 & 0.158983 \tabularnewline
14 & 0.014098 & 0.1465 & 0.441896 \tabularnewline
15 & -0.080488 & -0.8365 & 0.202372 \tabularnewline
16 & -0.03708 & -0.3853 & 0.350371 \tabularnewline
17 & -0.12437 & -1.2925 & 0.099473 \tabularnewline
18 & -0.089707 & -0.9323 & 0.176641 \tabularnewline
19 & 0.019614 & 0.2038 & 0.419432 \tabularnewline
20 & -0.087036 & -0.9045 & 0.183869 \tabularnewline
21 & -0.008804 & -0.0915 & 0.463634 \tabularnewline
22 & 0.116484 & 1.2105 & 0.114358 \tabularnewline
23 & 0.046745 & 0.4858 & 0.31405 \tabularnewline
24 & -0.058009 & -0.6028 & 0.273937 \tabularnewline
25 & -0.08821 & -0.9167 & 0.180671 \tabularnewline
26 & -0.020454 & -0.2126 & 0.416033 \tabularnewline
27 & -0.003751 & -0.039 & 0.48449 \tabularnewline
28 & 0.025026 & 0.2601 & 0.397651 \tabularnewline
29 & 0.093197 & 0.9685 & 0.167472 \tabularnewline
30 & -0.069298 & -0.7202 & 0.236489 \tabularnewline
31 & 0.099008 & 1.0289 & 0.152907 \tabularnewline
32 & -0.039903 & -0.4147 & 0.339597 \tabularnewline
33 & 0.085073 & 0.8841 & 0.189301 \tabularnewline
34 & -0.005607 & -0.0583 & 0.476822 \tabularnewline
35 & 0.083937 & 0.8723 & 0.192491 \tabularnewline
36 & -0.037354 & -0.3882 & 0.349319 \tabularnewline
37 & -0.015841 & -0.1646 & 0.434774 \tabularnewline
38 & 0.020307 & 0.211 & 0.416628 \tabularnewline
39 & -0.054328 & -0.5646 & 0.286759 \tabularnewline
40 & -0.08172 & -0.8493 & 0.198809 \tabularnewline
41 & -0.050052 & -0.5202 & 0.302012 \tabularnewline
42 & 0.042506 & 0.4417 & 0.329784 \tabularnewline
43 & -0.020991 & -0.2181 & 0.413862 \tabularnewline
44 & 0.058433 & 0.6073 & 0.27248 \tabularnewline
45 & -0.074913 & -0.7785 & 0.218983 \tabularnewline
46 & -0.09476 & -0.9848 & 0.163467 \tabularnewline
47 & -0.045441 & -0.4722 & 0.318856 \tabularnewline
48 & 0.02018 & 0.2097 & 0.417141 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111970&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]0.964949[/C][C]10.028[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.016358[/C][C]0.17[/C][C]0.432666[/C][/ROW]
[ROW][C]3[/C][C]0.22915[/C][C]2.3814[/C][C]0.009499[/C][/ROW]
[ROW][C]4[/C][C]-0.049272[/C][C]-0.5121[/C][C]0.304831[/C][/ROW]
[ROW][C]5[/C][C]-0.114484[/C][C]-1.1898[/C][C]0.118375[/C][/ROW]
[ROW][C]6[/C][C]-0.128243[/C][C]-1.3327[/C][C]0.092711[/C][/ROW]
[ROW][C]7[/C][C]0.144724[/C][C]1.504[/C][C]0.067748[/C][/ROW]
[ROW][C]8[/C][C]-0.028075[/C][C]-0.2918[/C][C]0.385515[/C][/ROW]
[ROW][C]9[/C][C]0.019348[/C][C]0.2011[/C][C]0.42051[/C][/ROW]
[ROW][C]10[/C][C]-0.081056[/C][C]-0.8424[/C][C]0.200725[/C][/ROW]
[ROW][C]11[/C][C]-0.027918[/C][C]-0.2901[/C][C]0.386135[/C][/ROW]
[ROW][C]12[/C][C]-0.073082[/C][C]-0.7595[/C][C]0.224606[/C][/ROW]
[ROW][C]13[/C][C]-0.096541[/C][C]-1.0033[/C][C]0.158983[/C][/ROW]
[ROW][C]14[/C][C]0.014098[/C][C]0.1465[/C][C]0.441896[/C][/ROW]
[ROW][C]15[/C][C]-0.080488[/C][C]-0.8365[/C][C]0.202372[/C][/ROW]
[ROW][C]16[/C][C]-0.03708[/C][C]-0.3853[/C][C]0.350371[/C][/ROW]
[ROW][C]17[/C][C]-0.12437[/C][C]-1.2925[/C][C]0.099473[/C][/ROW]
[ROW][C]18[/C][C]-0.089707[/C][C]-0.9323[/C][C]0.176641[/C][/ROW]
[ROW][C]19[/C][C]0.019614[/C][C]0.2038[/C][C]0.419432[/C][/ROW]
[ROW][C]20[/C][C]-0.087036[/C][C]-0.9045[/C][C]0.183869[/C][/ROW]
[ROW][C]21[/C][C]-0.008804[/C][C]-0.0915[/C][C]0.463634[/C][/ROW]
[ROW][C]22[/C][C]0.116484[/C][C]1.2105[/C][C]0.114358[/C][/ROW]
[ROW][C]23[/C][C]0.046745[/C][C]0.4858[/C][C]0.31405[/C][/ROW]
[ROW][C]24[/C][C]-0.058009[/C][C]-0.6028[/C][C]0.273937[/C][/ROW]
[ROW][C]25[/C][C]-0.08821[/C][C]-0.9167[/C][C]0.180671[/C][/ROW]
[ROW][C]26[/C][C]-0.020454[/C][C]-0.2126[/C][C]0.416033[/C][/ROW]
[ROW][C]27[/C][C]-0.003751[/C][C]-0.039[/C][C]0.48449[/C][/ROW]
[ROW][C]28[/C][C]0.025026[/C][C]0.2601[/C][C]0.397651[/C][/ROW]
[ROW][C]29[/C][C]0.093197[/C][C]0.9685[/C][C]0.167472[/C][/ROW]
[ROW][C]30[/C][C]-0.069298[/C][C]-0.7202[/C][C]0.236489[/C][/ROW]
[ROW][C]31[/C][C]0.099008[/C][C]1.0289[/C][C]0.152907[/C][/ROW]
[ROW][C]32[/C][C]-0.039903[/C][C]-0.4147[/C][C]0.339597[/C][/ROW]
[ROW][C]33[/C][C]0.085073[/C][C]0.8841[/C][C]0.189301[/C][/ROW]
[ROW][C]34[/C][C]-0.005607[/C][C]-0.0583[/C][C]0.476822[/C][/ROW]
[ROW][C]35[/C][C]0.083937[/C][C]0.8723[/C][C]0.192491[/C][/ROW]
[ROW][C]36[/C][C]-0.037354[/C][C]-0.3882[/C][C]0.349319[/C][/ROW]
[ROW][C]37[/C][C]-0.015841[/C][C]-0.1646[/C][C]0.434774[/C][/ROW]
[ROW][C]38[/C][C]0.020307[/C][C]0.211[/C][C]0.416628[/C][/ROW]
[ROW][C]39[/C][C]-0.054328[/C][C]-0.5646[/C][C]0.286759[/C][/ROW]
[ROW][C]40[/C][C]-0.08172[/C][C]-0.8493[/C][C]0.198809[/C][/ROW]
[ROW][C]41[/C][C]-0.050052[/C][C]-0.5202[/C][C]0.302012[/C][/ROW]
[ROW][C]42[/C][C]0.042506[/C][C]0.4417[/C][C]0.329784[/C][/ROW]
[ROW][C]43[/C][C]-0.020991[/C][C]-0.2181[/C][C]0.413862[/C][/ROW]
[ROW][C]44[/C][C]0.058433[/C][C]0.6073[/C][C]0.27248[/C][/ROW]
[ROW][C]45[/C][C]-0.074913[/C][C]-0.7785[/C][C]0.218983[/C][/ROW]
[ROW][C]46[/C][C]-0.09476[/C][C]-0.9848[/C][C]0.163467[/C][/ROW]
[ROW][C]47[/C][C]-0.045441[/C][C]-0.4722[/C][C]0.318856[/C][/ROW]
[ROW][C]48[/C][C]0.02018[/C][C]0.2097[/C][C]0.417141[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111970&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111970&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
10.96494910.0280
20.0163580.170.432666
30.229152.38140.009499
4-0.049272-0.51210.304831
5-0.114484-1.18980.118375
6-0.128243-1.33270.092711
70.1447241.5040.067748
8-0.028075-0.29180.385515
90.0193480.20110.42051
10-0.081056-0.84240.200725
11-0.027918-0.29010.386135
12-0.073082-0.75950.224606
13-0.096541-1.00330.158983
140.0140980.14650.441896
15-0.080488-0.83650.202372
16-0.03708-0.38530.350371
17-0.12437-1.29250.099473
18-0.089707-0.93230.176641
190.0196140.20380.419432
20-0.087036-0.90450.183869
21-0.008804-0.09150.463634
220.1164841.21050.114358
230.0467450.48580.31405
24-0.058009-0.60280.273937
25-0.08821-0.91670.180671
26-0.020454-0.21260.416033
27-0.003751-0.0390.48449
280.0250260.26010.397651
290.0931970.96850.167472
30-0.069298-0.72020.236489
310.0990081.02890.152907
32-0.039903-0.41470.339597
330.0850730.88410.189301
34-0.005607-0.05830.476822
350.0839370.87230.192491
36-0.037354-0.38820.349319
37-0.015841-0.16460.434774
380.0203070.2110.416628
39-0.054328-0.56460.286759
40-0.08172-0.84930.198809
41-0.050052-0.52020.302012
420.0425060.44170.329784
43-0.020991-0.21810.413862
440.0584330.60730.27248
45-0.074913-0.77850.218983
46-0.09476-0.98480.163467
47-0.045441-0.47220.318856
480.020180.20970.417141



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; 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 (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')