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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 28 Nov 2007 10:12:18 -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/2007/Nov/28/t11962693554lj8bpp808tn85v.htm/, Retrieved Thu, 02 May 2024 04:25:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7160, Retrieved Thu, 02 May 2024 04:25:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbridome
Estimated Impact166
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [workshop3] [2007-11-28 17:12:18] [9cd804c1ac16035a4cb2da1c6dfdb61e] [Current]
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Dataseries X:
39892
32194
21629
59968
45694
55756
48554
41052
49822
39191
31994
35735
38930
33658
23849
58972
59249
63955
53785
52760
44795
37348
32370
32717
40974
33591
21124
58608
46865
51378
46235
47206
45382
41227
33795
31295
42625
33625
21538
56421
53152
53536
52408
41454
38271
35306
26414
31917
38030
27534
18387
50556
43901
48572
43899
37532
40357
35489
29027
34485
42598
30306
26451
47460
50104
61465
53726
39477
43895
31481
29896
33842
39120
33702
25094
51442
45594
52518
48564
41745
49585
32747
33379
35645
37034
35681
20972
58552
54955
64540
51570
51145
46641
35704
33253
35193
41668
34865
21210
56126
49321
59723
48103
47472
50497
40059











Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7160&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7160&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7160&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
0110.29560
10.3550253.65520.000201
20.1657591.70660.045412
3-0.009376-0.09650.538359
4-0.191351-1.97010.974281
5-0.306745-3.15810.998966
6-0.481276-4.9550.999999
7-0.317863-3.27260.99928
8-0.169151-1.74150.957753
9-0.013264-0.13660.55418
100.0964650.99320.161445
110.2798122.88080.0024
120.7825138.05650
130.2839462.92340.002117
140.123451.2710.103257
15-0.033347-0.34330.633984
16-0.170302-1.75340.958785
17-0.280462-2.88750.997646
18-0.41858-4.30950.999982
19-0.267128-2.75030.996498
20-0.16157-1.66350.950414
21-0.013457-0.13850.554963
220.0661010.68050.248821
230.2433022.50490.006885
240.6583676.77830
250.2373652.44380.008092
260.0903230.92990.17726
27-0.042381-0.43630.66826
28-0.164272-1.69130.95314
29-0.246476-2.53760.993692
30-0.375689-3.8680.999905
31-0.25094-2.58360.99443
32-0.151568-1.56050.939187
33-0.043664-0.44950.673022
340.0309850.3190.375175
350.1733161.78440.03861
360.5194715.34830
370.1840681.89510.030402
380.0419940.43230.333183
39-0.059616-0.61380.729663
40-0.171179-1.76240.959558
41-0.220963-2.2750.98754
42-0.316816-3.26180.999255
43-0.21328-2.19590.984859
44-0.105799-1.08930.860746
45-0.035029-0.36060.640458
460.0258370.2660.395373
470.1450031.49290.069217

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 10.2956 & 0 \tabularnewline
1 & 0.355025 & 3.6552 & 0.000201 \tabularnewline
2 & 0.165759 & 1.7066 & 0.045412 \tabularnewline
3 & -0.009376 & -0.0965 & 0.538359 \tabularnewline
4 & -0.191351 & -1.9701 & 0.974281 \tabularnewline
5 & -0.306745 & -3.1581 & 0.998966 \tabularnewline
6 & -0.481276 & -4.955 & 0.999999 \tabularnewline
7 & -0.317863 & -3.2726 & 0.99928 \tabularnewline
8 & -0.169151 & -1.7415 & 0.957753 \tabularnewline
9 & -0.013264 & -0.1366 & 0.55418 \tabularnewline
10 & 0.096465 & 0.9932 & 0.161445 \tabularnewline
11 & 0.279812 & 2.8808 & 0.0024 \tabularnewline
12 & 0.782513 & 8.0565 & 0 \tabularnewline
13 & 0.283946 & 2.9234 & 0.002117 \tabularnewline
14 & 0.12345 & 1.271 & 0.103257 \tabularnewline
15 & -0.033347 & -0.3433 & 0.633984 \tabularnewline
16 & -0.170302 & -1.7534 & 0.958785 \tabularnewline
17 & -0.280462 & -2.8875 & 0.997646 \tabularnewline
18 & -0.41858 & -4.3095 & 0.999982 \tabularnewline
19 & -0.267128 & -2.7503 & 0.996498 \tabularnewline
20 & -0.16157 & -1.6635 & 0.950414 \tabularnewline
21 & -0.013457 & -0.1385 & 0.554963 \tabularnewline
22 & 0.066101 & 0.6805 & 0.248821 \tabularnewline
23 & 0.243302 & 2.5049 & 0.006885 \tabularnewline
24 & 0.658367 & 6.7783 & 0 \tabularnewline
25 & 0.237365 & 2.4438 & 0.008092 \tabularnewline
26 & 0.090323 & 0.9299 & 0.17726 \tabularnewline
27 & -0.042381 & -0.4363 & 0.66826 \tabularnewline
28 & -0.164272 & -1.6913 & 0.95314 \tabularnewline
29 & -0.246476 & -2.5376 & 0.993692 \tabularnewline
30 & -0.375689 & -3.868 & 0.999905 \tabularnewline
31 & -0.25094 & -2.5836 & 0.99443 \tabularnewline
32 & -0.151568 & -1.5605 & 0.939187 \tabularnewline
33 & -0.043664 & -0.4495 & 0.673022 \tabularnewline
34 & 0.030985 & 0.319 & 0.375175 \tabularnewline
35 & 0.173316 & 1.7844 & 0.03861 \tabularnewline
36 & 0.519471 & 5.3483 & 0 \tabularnewline
37 & 0.184068 & 1.8951 & 0.030402 \tabularnewline
38 & 0.041994 & 0.4323 & 0.333183 \tabularnewline
39 & -0.059616 & -0.6138 & 0.729663 \tabularnewline
40 & -0.171179 & -1.7624 & 0.959558 \tabularnewline
41 & -0.220963 & -2.275 & 0.98754 \tabularnewline
42 & -0.316816 & -3.2618 & 0.999255 \tabularnewline
43 & -0.21328 & -2.1959 & 0.984859 \tabularnewline
44 & -0.105799 & -1.0893 & 0.860746 \tabularnewline
45 & -0.035029 & -0.3606 & 0.640458 \tabularnewline
46 & 0.025837 & 0.266 & 0.395373 \tabularnewline
47 & 0.145003 & 1.4929 & 0.069217 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7160&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]0[/C][C]1[/C][C]10.2956[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]0.355025[/C][C]3.6552[/C][C]0.000201[/C][/ROW]
[ROW][C]2[/C][C]0.165759[/C][C]1.7066[/C][C]0.045412[/C][/ROW]
[ROW][C]3[/C][C]-0.009376[/C][C]-0.0965[/C][C]0.538359[/C][/ROW]
[ROW][C]4[/C][C]-0.191351[/C][C]-1.9701[/C][C]0.974281[/C][/ROW]
[ROW][C]5[/C][C]-0.306745[/C][C]-3.1581[/C][C]0.998966[/C][/ROW]
[ROW][C]6[/C][C]-0.481276[/C][C]-4.955[/C][C]0.999999[/C][/ROW]
[ROW][C]7[/C][C]-0.317863[/C][C]-3.2726[/C][C]0.99928[/C][/ROW]
[ROW][C]8[/C][C]-0.169151[/C][C]-1.7415[/C][C]0.957753[/C][/ROW]
[ROW][C]9[/C][C]-0.013264[/C][C]-0.1366[/C][C]0.55418[/C][/ROW]
[ROW][C]10[/C][C]0.096465[/C][C]0.9932[/C][C]0.161445[/C][/ROW]
[ROW][C]11[/C][C]0.279812[/C][C]2.8808[/C][C]0.0024[/C][/ROW]
[ROW][C]12[/C][C]0.782513[/C][C]8.0565[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.283946[/C][C]2.9234[/C][C]0.002117[/C][/ROW]
[ROW][C]14[/C][C]0.12345[/C][C]1.271[/C][C]0.103257[/C][/ROW]
[ROW][C]15[/C][C]-0.033347[/C][C]-0.3433[/C][C]0.633984[/C][/ROW]
[ROW][C]16[/C][C]-0.170302[/C][C]-1.7534[/C][C]0.958785[/C][/ROW]
[ROW][C]17[/C][C]-0.280462[/C][C]-2.8875[/C][C]0.997646[/C][/ROW]
[ROW][C]18[/C][C]-0.41858[/C][C]-4.3095[/C][C]0.999982[/C][/ROW]
[ROW][C]19[/C][C]-0.267128[/C][C]-2.7503[/C][C]0.996498[/C][/ROW]
[ROW][C]20[/C][C]-0.16157[/C][C]-1.6635[/C][C]0.950414[/C][/ROW]
[ROW][C]21[/C][C]-0.013457[/C][C]-0.1385[/C][C]0.554963[/C][/ROW]
[ROW][C]22[/C][C]0.066101[/C][C]0.6805[/C][C]0.248821[/C][/ROW]
[ROW][C]23[/C][C]0.243302[/C][C]2.5049[/C][C]0.006885[/C][/ROW]
[ROW][C]24[/C][C]0.658367[/C][C]6.7783[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.237365[/C][C]2.4438[/C][C]0.008092[/C][/ROW]
[ROW][C]26[/C][C]0.090323[/C][C]0.9299[/C][C]0.17726[/C][/ROW]
[ROW][C]27[/C][C]-0.042381[/C][C]-0.4363[/C][C]0.66826[/C][/ROW]
[ROW][C]28[/C][C]-0.164272[/C][C]-1.6913[/C][C]0.95314[/C][/ROW]
[ROW][C]29[/C][C]-0.246476[/C][C]-2.5376[/C][C]0.993692[/C][/ROW]
[ROW][C]30[/C][C]-0.375689[/C][C]-3.868[/C][C]0.999905[/C][/ROW]
[ROW][C]31[/C][C]-0.25094[/C][C]-2.5836[/C][C]0.99443[/C][/ROW]
[ROW][C]32[/C][C]-0.151568[/C][C]-1.5605[/C][C]0.939187[/C][/ROW]
[ROW][C]33[/C][C]-0.043664[/C][C]-0.4495[/C][C]0.673022[/C][/ROW]
[ROW][C]34[/C][C]0.030985[/C][C]0.319[/C][C]0.375175[/C][/ROW]
[ROW][C]35[/C][C]0.173316[/C][C]1.7844[/C][C]0.03861[/C][/ROW]
[ROW][C]36[/C][C]0.519471[/C][C]5.3483[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.184068[/C][C]1.8951[/C][C]0.030402[/C][/ROW]
[ROW][C]38[/C][C]0.041994[/C][C]0.4323[/C][C]0.333183[/C][/ROW]
[ROW][C]39[/C][C]-0.059616[/C][C]-0.6138[/C][C]0.729663[/C][/ROW]
[ROW][C]40[/C][C]-0.171179[/C][C]-1.7624[/C][C]0.959558[/C][/ROW]
[ROW][C]41[/C][C]-0.220963[/C][C]-2.275[/C][C]0.98754[/C][/ROW]
[ROW][C]42[/C][C]-0.316816[/C][C]-3.2618[/C][C]0.999255[/C][/ROW]
[ROW][C]43[/C][C]-0.21328[/C][C]-2.1959[/C][C]0.984859[/C][/ROW]
[ROW][C]44[/C][C]-0.105799[/C][C]-1.0893[/C][C]0.860746[/C][/ROW]
[ROW][C]45[/C][C]-0.035029[/C][C]-0.3606[/C][C]0.640458[/C][/ROW]
[ROW][C]46[/C][C]0.025837[/C][C]0.266[/C][C]0.395373[/C][/ROW]
[ROW][C]47[/C][C]0.145003[/C][C]1.4929[/C][C]0.069217[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7160&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7160&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
0110.29560
10.3550253.65520.000201
20.1657591.70660.045412
3-0.009376-0.09650.538359
4-0.191351-1.97010.974281
5-0.306745-3.15810.998966
6-0.481276-4.9550.999999
7-0.317863-3.27260.99928
8-0.169151-1.74150.957753
9-0.013264-0.13660.55418
100.0964650.99320.161445
110.2798122.88080.0024
120.7825138.05650
130.2839462.92340.002117
140.123451.2710.103257
15-0.033347-0.34330.633984
16-0.170302-1.75340.958785
17-0.280462-2.88750.997646
18-0.41858-4.30950.999982
19-0.267128-2.75030.996498
20-0.16157-1.66350.950414
21-0.013457-0.13850.554963
220.0661010.68050.248821
230.2433022.50490.006885
240.6583676.77830
250.2373652.44380.008092
260.0903230.92990.17726
27-0.042381-0.43630.66826
28-0.164272-1.69130.95314
29-0.246476-2.53760.993692
30-0.375689-3.8680.999905
31-0.25094-2.58360.99443
32-0.151568-1.56050.939187
33-0.043664-0.44950.673022
340.0309850.3190.375175
350.1733161.78440.03861
360.5194715.34830
370.1840681.89510.030402
380.0419940.43230.333183
39-0.059616-0.61380.729663
40-0.171179-1.76240.959558
41-0.220963-2.2750.98754
42-0.316816-3.26180.999255
43-0.21328-2.19590.984859
44-0.105799-1.08930.860746
45-0.035029-0.36060.640458
460.0258370.2660.395373
470.1450031.49290.069217







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.3550253.65520.000201
10.0454450.46790.320415
2-0.093658-0.96430.831447
3-0.193958-1.99690.975801
4-0.204745-2.1080.981305
5-0.35562-3.66130.999803
6-0.089919-0.92580.821667
7-0.049775-0.51250.695305
8-0.019328-0.1990.578675
9-0.05945-0.61210.729102
100.0974011.00280.159121
110.7003667.21070
12-0.274416-2.82530.997177
13-0.149042-1.53450.936054
140.0180680.1860.42639
150.0868710.89440.18657
16-0.067936-0.69940.757096
170.0685460.70570.240955
180.0592570.61010.271554
19-0.16493-1.69810.953785
20-0.020579-0.21190.583693
210.1046351.07730.1419
220.0297840.30660.379856
230.0316180.32550.372713
24-0.041403-0.42630.664612
25-0.064027-0.65920.744402
26-0.010697-0.11010.543743
27-0.000353-0.00360.501448
280.0566770.58350.280391
29-0.058251-0.59970.725017
30-0.094579-0.97380.833802
31-0.00328-0.03380.513438
32-0.07539-0.77620.780317
33-0.00483-0.04970.519782
34-0.091865-0.94580.826802
35-0.057136-0.58830.721194
36-0.057123-0.58810.721149
37-0.086434-0.88990.81223
38-0.036629-0.37710.646579
39-0.082663-0.85110.801673
40-0.040963-0.42170.662965
41-0.015619-0.16080.563723
42-0.04671-0.48090.684215
430.0162240.1670.433831
44-0.057625-0.59330.722874
45-0.057977-0.59690.724081
46-0.020905-0.21520.585001
470.1020811.0510.147827

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & 0.355025 & 3.6552 & 0.000201 \tabularnewline
1 & 0.045445 & 0.4679 & 0.320415 \tabularnewline
2 & -0.093658 & -0.9643 & 0.831447 \tabularnewline
3 & -0.193958 & -1.9969 & 0.975801 \tabularnewline
4 & -0.204745 & -2.108 & 0.981305 \tabularnewline
5 & -0.35562 & -3.6613 & 0.999803 \tabularnewline
6 & -0.089919 & -0.9258 & 0.821667 \tabularnewline
7 & -0.049775 & -0.5125 & 0.695305 \tabularnewline
8 & -0.019328 & -0.199 & 0.578675 \tabularnewline
9 & -0.05945 & -0.6121 & 0.729102 \tabularnewline
10 & 0.097401 & 1.0028 & 0.159121 \tabularnewline
11 & 0.700366 & 7.2107 & 0 \tabularnewline
12 & -0.274416 & -2.8253 & 0.997177 \tabularnewline
13 & -0.149042 & -1.5345 & 0.936054 \tabularnewline
14 & 0.018068 & 0.186 & 0.42639 \tabularnewline
15 & 0.086871 & 0.8944 & 0.18657 \tabularnewline
16 & -0.067936 & -0.6994 & 0.757096 \tabularnewline
17 & 0.068546 & 0.7057 & 0.240955 \tabularnewline
18 & 0.059257 & 0.6101 & 0.271554 \tabularnewline
19 & -0.16493 & -1.6981 & 0.953785 \tabularnewline
20 & -0.020579 & -0.2119 & 0.583693 \tabularnewline
21 & 0.104635 & 1.0773 & 0.1419 \tabularnewline
22 & 0.029784 & 0.3066 & 0.379856 \tabularnewline
23 & 0.031618 & 0.3255 & 0.372713 \tabularnewline
24 & -0.041403 & -0.4263 & 0.664612 \tabularnewline
25 & -0.064027 & -0.6592 & 0.744402 \tabularnewline
26 & -0.010697 & -0.1101 & 0.543743 \tabularnewline
27 & -0.000353 & -0.0036 & 0.501448 \tabularnewline
28 & 0.056677 & 0.5835 & 0.280391 \tabularnewline
29 & -0.058251 & -0.5997 & 0.725017 \tabularnewline
30 & -0.094579 & -0.9738 & 0.833802 \tabularnewline
31 & -0.00328 & -0.0338 & 0.513438 \tabularnewline
32 & -0.07539 & -0.7762 & 0.780317 \tabularnewline
33 & -0.00483 & -0.0497 & 0.519782 \tabularnewline
34 & -0.091865 & -0.9458 & 0.826802 \tabularnewline
35 & -0.057136 & -0.5883 & 0.721194 \tabularnewline
36 & -0.057123 & -0.5881 & 0.721149 \tabularnewline
37 & -0.086434 & -0.8899 & 0.81223 \tabularnewline
38 & -0.036629 & -0.3771 & 0.646579 \tabularnewline
39 & -0.082663 & -0.8511 & 0.801673 \tabularnewline
40 & -0.040963 & -0.4217 & 0.662965 \tabularnewline
41 & -0.015619 & -0.1608 & 0.563723 \tabularnewline
42 & -0.04671 & -0.4809 & 0.684215 \tabularnewline
43 & 0.016224 & 0.167 & 0.433831 \tabularnewline
44 & -0.057625 & -0.5933 & 0.722874 \tabularnewline
45 & -0.057977 & -0.5969 & 0.724081 \tabularnewline
46 & -0.020905 & -0.2152 & 0.585001 \tabularnewline
47 & 0.102081 & 1.051 & 0.147827 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7160&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]0[/C][C]0.355025[/C][C]3.6552[/C][C]0.000201[/C][/ROW]
[ROW][C]1[/C][C]0.045445[/C][C]0.4679[/C][C]0.320415[/C][/ROW]
[ROW][C]2[/C][C]-0.093658[/C][C]-0.9643[/C][C]0.831447[/C][/ROW]
[ROW][C]3[/C][C]-0.193958[/C][C]-1.9969[/C][C]0.975801[/C][/ROW]
[ROW][C]4[/C][C]-0.204745[/C][C]-2.108[/C][C]0.981305[/C][/ROW]
[ROW][C]5[/C][C]-0.35562[/C][C]-3.6613[/C][C]0.999803[/C][/ROW]
[ROW][C]6[/C][C]-0.089919[/C][C]-0.9258[/C][C]0.821667[/C][/ROW]
[ROW][C]7[/C][C]-0.049775[/C][C]-0.5125[/C][C]0.695305[/C][/ROW]
[ROW][C]8[/C][C]-0.019328[/C][C]-0.199[/C][C]0.578675[/C][/ROW]
[ROW][C]9[/C][C]-0.05945[/C][C]-0.6121[/C][C]0.729102[/C][/ROW]
[ROW][C]10[/C][C]0.097401[/C][C]1.0028[/C][C]0.159121[/C][/ROW]
[ROW][C]11[/C][C]0.700366[/C][C]7.2107[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]-0.274416[/C][C]-2.8253[/C][C]0.997177[/C][/ROW]
[ROW][C]13[/C][C]-0.149042[/C][C]-1.5345[/C][C]0.936054[/C][/ROW]
[ROW][C]14[/C][C]0.018068[/C][C]0.186[/C][C]0.42639[/C][/ROW]
[ROW][C]15[/C][C]0.086871[/C][C]0.8944[/C][C]0.18657[/C][/ROW]
[ROW][C]16[/C][C]-0.067936[/C][C]-0.6994[/C][C]0.757096[/C][/ROW]
[ROW][C]17[/C][C]0.068546[/C][C]0.7057[/C][C]0.240955[/C][/ROW]
[ROW][C]18[/C][C]0.059257[/C][C]0.6101[/C][C]0.271554[/C][/ROW]
[ROW][C]19[/C][C]-0.16493[/C][C]-1.6981[/C][C]0.953785[/C][/ROW]
[ROW][C]20[/C][C]-0.020579[/C][C]-0.2119[/C][C]0.583693[/C][/ROW]
[ROW][C]21[/C][C]0.104635[/C][C]1.0773[/C][C]0.1419[/C][/ROW]
[ROW][C]22[/C][C]0.029784[/C][C]0.3066[/C][C]0.379856[/C][/ROW]
[ROW][C]23[/C][C]0.031618[/C][C]0.3255[/C][C]0.372713[/C][/ROW]
[ROW][C]24[/C][C]-0.041403[/C][C]-0.4263[/C][C]0.664612[/C][/ROW]
[ROW][C]25[/C][C]-0.064027[/C][C]-0.6592[/C][C]0.744402[/C][/ROW]
[ROW][C]26[/C][C]-0.010697[/C][C]-0.1101[/C][C]0.543743[/C][/ROW]
[ROW][C]27[/C][C]-0.000353[/C][C]-0.0036[/C][C]0.501448[/C][/ROW]
[ROW][C]28[/C][C]0.056677[/C][C]0.5835[/C][C]0.280391[/C][/ROW]
[ROW][C]29[/C][C]-0.058251[/C][C]-0.5997[/C][C]0.725017[/C][/ROW]
[ROW][C]30[/C][C]-0.094579[/C][C]-0.9738[/C][C]0.833802[/C][/ROW]
[ROW][C]31[/C][C]-0.00328[/C][C]-0.0338[/C][C]0.513438[/C][/ROW]
[ROW][C]32[/C][C]-0.07539[/C][C]-0.7762[/C][C]0.780317[/C][/ROW]
[ROW][C]33[/C][C]-0.00483[/C][C]-0.0497[/C][C]0.519782[/C][/ROW]
[ROW][C]34[/C][C]-0.091865[/C][C]-0.9458[/C][C]0.826802[/C][/ROW]
[ROW][C]35[/C][C]-0.057136[/C][C]-0.5883[/C][C]0.721194[/C][/ROW]
[ROW][C]36[/C][C]-0.057123[/C][C]-0.5881[/C][C]0.721149[/C][/ROW]
[ROW][C]37[/C][C]-0.086434[/C][C]-0.8899[/C][C]0.81223[/C][/ROW]
[ROW][C]38[/C][C]-0.036629[/C][C]-0.3771[/C][C]0.646579[/C][/ROW]
[ROW][C]39[/C][C]-0.082663[/C][C]-0.8511[/C][C]0.801673[/C][/ROW]
[ROW][C]40[/C][C]-0.040963[/C][C]-0.4217[/C][C]0.662965[/C][/ROW]
[ROW][C]41[/C][C]-0.015619[/C][C]-0.1608[/C][C]0.563723[/C][/ROW]
[ROW][C]42[/C][C]-0.04671[/C][C]-0.4809[/C][C]0.684215[/C][/ROW]
[ROW][C]43[/C][C]0.016224[/C][C]0.167[/C][C]0.433831[/C][/ROW]
[ROW][C]44[/C][C]-0.057625[/C][C]-0.5933[/C][C]0.722874[/C][/ROW]
[ROW][C]45[/C][C]-0.057977[/C][C]-0.5969[/C][C]0.724081[/C][/ROW]
[ROW][C]46[/C][C]-0.020905[/C][C]-0.2152[/C][C]0.585001[/C][/ROW]
[ROW][C]47[/C][C]0.102081[/C][C]1.051[/C][C]0.147827[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7160&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7160&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
00.3550253.65520.000201
10.0454450.46790.320415
2-0.093658-0.96430.831447
3-0.193958-1.99690.975801
4-0.204745-2.1080.981305
5-0.35562-3.66130.999803
6-0.089919-0.92580.821667
7-0.049775-0.51250.695305
8-0.019328-0.1990.578675
9-0.05945-0.61210.729102
100.0974011.00280.159121
110.7003667.21070
12-0.274416-2.82530.997177
13-0.149042-1.53450.936054
140.0180680.1860.42639
150.0868710.89440.18657
16-0.067936-0.69940.757096
170.0685460.70570.240955
180.0592570.61010.271554
19-0.16493-1.69810.953785
20-0.020579-0.21190.583693
210.1046351.07730.1419
220.0297840.30660.379856
230.0316180.32550.372713
24-0.041403-0.42630.664612
25-0.064027-0.65920.744402
26-0.010697-0.11010.543743
27-0.000353-0.00360.501448
280.0566770.58350.280391
29-0.058251-0.59970.725017
30-0.094579-0.97380.833802
31-0.00328-0.03380.513438
32-0.07539-0.77620.780317
33-0.00483-0.04970.519782
34-0.091865-0.94580.826802
35-0.057136-0.58830.721194
36-0.057123-0.58810.721149
37-0.086434-0.88990.81223
38-0.036629-0.37710.646579
39-0.082663-0.85110.801673
40-0.040963-0.42170.662965
41-0.015619-0.16080.563723
42-0.04671-0.48090.684215
430.0162240.1670.433831
44-0.057625-0.59330.722874
45-0.057977-0.59690.724081
46-0.020905-0.21520.585001
470.1020811.0510.147827



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')