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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 computationSun, 19 Dec 2010 14:17:58 +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/19/t1292768165vmd7gubdui718sj.htm/, Retrieved Sat, 04 May 2024 22:49:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112412, Retrieved Sat, 04 May 2024 22:49:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [] [2010-12-14 13:36:04] [c91278f1cd2d8b4eeb874e50bb706c21]
-   PD    [(Partial) Autocorrelation Function] [] [2010-12-19 14:17:58] [4dbe485270073769796ed1462cddce37] [Current]
-   P       [(Partial) Autocorrelation Function] [] [2010-12-28 00:12:43] [2e1e44f0ae3cb9513dc28781dfdb387b]
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Dataseries X:
364
351
380
319
322
386
221
187
343
342
365
313
356
337
389
326
343
357
220
218
391
425
332
298
360
336
325
393
301
426
265
210
429
440
357
431
442
422
544
420
396
482
261
211
448
468
464
425
415
433
531
457
380
481
302
216
509
417
370




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112412&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112412&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112412&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2062691.41410.08196
20.2317011.58850.059444
30.2456751.68430.049381
4-0.072065-0.49410.311785
50.1587651.08840.140975
60.1174450.80520.21239
7-0.162382-1.11320.135634
80.2084421.4290.079808
90.0364230.24970.401951
10-0.081678-0.560.289085
110.0747910.51270.305267
12-0.413371-2.83390.003378
13-0.143638-0.98470.164899
14-0.086352-0.5920.278343
15-0.131096-0.89880.186683
160.019360.13270.447487
17-0.031698-0.21730.414453
18-0.12381-0.84880.200149
19-0.043202-0.29620.3842
20-0.28588-1.95990.027976
21-0.153617-1.05310.14883
22-0.138683-0.95080.173294
23-0.25856-1.77260.041388
24-0.026531-0.18190.428228
25-0.009281-0.06360.474769
26-0.007056-0.04840.480813
270.0327350.22440.411701
28-0.115751-0.79350.215724
29-0.024065-0.1650.434833
300.057690.39550.34713
310.0077930.05340.47881
320.0668940.45860.324316
330.0229770.15750.437755
340.0102590.07030.472115
350.1208430.82850.2058
360.042720.29290.385453
37-0.053251-0.36510.358349
38-0.017147-0.11760.453462
39-0.002508-0.01720.493176
400.0625410.42880.335028
410.0423750.29050.386352
420.0059020.04050.483949
430.0137370.09420.462686
440.0224090.15360.439281
450.0477580.32740.372405
460.0261160.1790.429336
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.206269 & 1.4141 & 0.08196 \tabularnewline
2 & 0.231701 & 1.5885 & 0.059444 \tabularnewline
3 & 0.245675 & 1.6843 & 0.049381 \tabularnewline
4 & -0.072065 & -0.4941 & 0.311785 \tabularnewline
5 & 0.158765 & 1.0884 & 0.140975 \tabularnewline
6 & 0.117445 & 0.8052 & 0.21239 \tabularnewline
7 & -0.162382 & -1.1132 & 0.135634 \tabularnewline
8 & 0.208442 & 1.429 & 0.079808 \tabularnewline
9 & 0.036423 & 0.2497 & 0.401951 \tabularnewline
10 & -0.081678 & -0.56 & 0.289085 \tabularnewline
11 & 0.074791 & 0.5127 & 0.305267 \tabularnewline
12 & -0.413371 & -2.8339 & 0.003378 \tabularnewline
13 & -0.143638 & -0.9847 & 0.164899 \tabularnewline
14 & -0.086352 & -0.592 & 0.278343 \tabularnewline
15 & -0.131096 & -0.8988 & 0.186683 \tabularnewline
16 & 0.01936 & 0.1327 & 0.447487 \tabularnewline
17 & -0.031698 & -0.2173 & 0.414453 \tabularnewline
18 & -0.12381 & -0.8488 & 0.200149 \tabularnewline
19 & -0.043202 & -0.2962 & 0.3842 \tabularnewline
20 & -0.28588 & -1.9599 & 0.027976 \tabularnewline
21 & -0.153617 & -1.0531 & 0.14883 \tabularnewline
22 & -0.138683 & -0.9508 & 0.173294 \tabularnewline
23 & -0.25856 & -1.7726 & 0.041388 \tabularnewline
24 & -0.026531 & -0.1819 & 0.428228 \tabularnewline
25 & -0.009281 & -0.0636 & 0.474769 \tabularnewline
26 & -0.007056 & -0.0484 & 0.480813 \tabularnewline
27 & 0.032735 & 0.2244 & 0.411701 \tabularnewline
28 & -0.115751 & -0.7935 & 0.215724 \tabularnewline
29 & -0.024065 & -0.165 & 0.434833 \tabularnewline
30 & 0.05769 & 0.3955 & 0.34713 \tabularnewline
31 & 0.007793 & 0.0534 & 0.47881 \tabularnewline
32 & 0.066894 & 0.4586 & 0.324316 \tabularnewline
33 & 0.022977 & 0.1575 & 0.437755 \tabularnewline
34 & 0.010259 & 0.0703 & 0.472115 \tabularnewline
35 & 0.120843 & 0.8285 & 0.2058 \tabularnewline
36 & 0.04272 & 0.2929 & 0.385453 \tabularnewline
37 & -0.053251 & -0.3651 & 0.358349 \tabularnewline
38 & -0.017147 & -0.1176 & 0.453462 \tabularnewline
39 & -0.002508 & -0.0172 & 0.493176 \tabularnewline
40 & 0.062541 & 0.4288 & 0.335028 \tabularnewline
41 & 0.042375 & 0.2905 & 0.386352 \tabularnewline
42 & 0.005902 & 0.0405 & 0.483949 \tabularnewline
43 & 0.013737 & 0.0942 & 0.462686 \tabularnewline
44 & 0.022409 & 0.1536 & 0.439281 \tabularnewline
45 & 0.047758 & 0.3274 & 0.372405 \tabularnewline
46 & 0.026116 & 0.179 & 0.429336 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112412&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]0.206269[/C][C]1.4141[/C][C]0.08196[/C][/ROW]
[ROW][C]2[/C][C]0.231701[/C][C]1.5885[/C][C]0.059444[/C][/ROW]
[ROW][C]3[/C][C]0.245675[/C][C]1.6843[/C][C]0.049381[/C][/ROW]
[ROW][C]4[/C][C]-0.072065[/C][C]-0.4941[/C][C]0.311785[/C][/ROW]
[ROW][C]5[/C][C]0.158765[/C][C]1.0884[/C][C]0.140975[/C][/ROW]
[ROW][C]6[/C][C]0.117445[/C][C]0.8052[/C][C]0.21239[/C][/ROW]
[ROW][C]7[/C][C]-0.162382[/C][C]-1.1132[/C][C]0.135634[/C][/ROW]
[ROW][C]8[/C][C]0.208442[/C][C]1.429[/C][C]0.079808[/C][/ROW]
[ROW][C]9[/C][C]0.036423[/C][C]0.2497[/C][C]0.401951[/C][/ROW]
[ROW][C]10[/C][C]-0.081678[/C][C]-0.56[/C][C]0.289085[/C][/ROW]
[ROW][C]11[/C][C]0.074791[/C][C]0.5127[/C][C]0.305267[/C][/ROW]
[ROW][C]12[/C][C]-0.413371[/C][C]-2.8339[/C][C]0.003378[/C][/ROW]
[ROW][C]13[/C][C]-0.143638[/C][C]-0.9847[/C][C]0.164899[/C][/ROW]
[ROW][C]14[/C][C]-0.086352[/C][C]-0.592[/C][C]0.278343[/C][/ROW]
[ROW][C]15[/C][C]-0.131096[/C][C]-0.8988[/C][C]0.186683[/C][/ROW]
[ROW][C]16[/C][C]0.01936[/C][C]0.1327[/C][C]0.447487[/C][/ROW]
[ROW][C]17[/C][C]-0.031698[/C][C]-0.2173[/C][C]0.414453[/C][/ROW]
[ROW][C]18[/C][C]-0.12381[/C][C]-0.8488[/C][C]0.200149[/C][/ROW]
[ROW][C]19[/C][C]-0.043202[/C][C]-0.2962[/C][C]0.3842[/C][/ROW]
[ROW][C]20[/C][C]-0.28588[/C][C]-1.9599[/C][C]0.027976[/C][/ROW]
[ROW][C]21[/C][C]-0.153617[/C][C]-1.0531[/C][C]0.14883[/C][/ROW]
[ROW][C]22[/C][C]-0.138683[/C][C]-0.9508[/C][C]0.173294[/C][/ROW]
[ROW][C]23[/C][C]-0.25856[/C][C]-1.7726[/C][C]0.041388[/C][/ROW]
[ROW][C]24[/C][C]-0.026531[/C][C]-0.1819[/C][C]0.428228[/C][/ROW]
[ROW][C]25[/C][C]-0.009281[/C][C]-0.0636[/C][C]0.474769[/C][/ROW]
[ROW][C]26[/C][C]-0.007056[/C][C]-0.0484[/C][C]0.480813[/C][/ROW]
[ROW][C]27[/C][C]0.032735[/C][C]0.2244[/C][C]0.411701[/C][/ROW]
[ROW][C]28[/C][C]-0.115751[/C][C]-0.7935[/C][C]0.215724[/C][/ROW]
[ROW][C]29[/C][C]-0.024065[/C][C]-0.165[/C][C]0.434833[/C][/ROW]
[ROW][C]30[/C][C]0.05769[/C][C]0.3955[/C][C]0.34713[/C][/ROW]
[ROW][C]31[/C][C]0.007793[/C][C]0.0534[/C][C]0.47881[/C][/ROW]
[ROW][C]32[/C][C]0.066894[/C][C]0.4586[/C][C]0.324316[/C][/ROW]
[ROW][C]33[/C][C]0.022977[/C][C]0.1575[/C][C]0.437755[/C][/ROW]
[ROW][C]34[/C][C]0.010259[/C][C]0.0703[/C][C]0.472115[/C][/ROW]
[ROW][C]35[/C][C]0.120843[/C][C]0.8285[/C][C]0.2058[/C][/ROW]
[ROW][C]36[/C][C]0.04272[/C][C]0.2929[/C][C]0.385453[/C][/ROW]
[ROW][C]37[/C][C]-0.053251[/C][C]-0.3651[/C][C]0.358349[/C][/ROW]
[ROW][C]38[/C][C]-0.017147[/C][C]-0.1176[/C][C]0.453462[/C][/ROW]
[ROW][C]39[/C][C]-0.002508[/C][C]-0.0172[/C][C]0.493176[/C][/ROW]
[ROW][C]40[/C][C]0.062541[/C][C]0.4288[/C][C]0.335028[/C][/ROW]
[ROW][C]41[/C][C]0.042375[/C][C]0.2905[/C][C]0.386352[/C][/ROW]
[ROW][C]42[/C][C]0.005902[/C][C]0.0405[/C][C]0.483949[/C][/ROW]
[ROW][C]43[/C][C]0.013737[/C][C]0.0942[/C][C]0.462686[/C][/ROW]
[ROW][C]44[/C][C]0.022409[/C][C]0.1536[/C][C]0.439281[/C][/ROW]
[ROW][C]45[/C][C]0.047758[/C][C]0.3274[/C][C]0.372405[/C][/ROW]
[ROW][C]46[/C][C]0.026116[/C][C]0.179[/C][C]0.429336[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112412&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112412&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
10.2062691.41410.08196
20.2317011.58850.059444
30.2456751.68430.049381
4-0.072065-0.49410.311785
50.1587651.08840.140975
60.1174450.80520.21239
7-0.162382-1.11320.135634
80.2084421.4290.079808
90.0364230.24970.401951
10-0.081678-0.560.289085
110.0747910.51270.305267
12-0.413371-2.83390.003378
13-0.143638-0.98470.164899
14-0.086352-0.5920.278343
15-0.131096-0.89880.186683
160.019360.13270.447487
17-0.031698-0.21730.414453
18-0.12381-0.84880.200149
19-0.043202-0.29620.3842
20-0.28588-1.95990.027976
21-0.153617-1.05310.14883
22-0.138683-0.95080.173294
23-0.25856-1.77260.041388
24-0.026531-0.18190.428228
25-0.009281-0.06360.474769
26-0.007056-0.04840.480813
270.0327350.22440.411701
28-0.115751-0.79350.215724
29-0.024065-0.1650.434833
300.057690.39550.34713
310.0077930.05340.47881
320.0668940.45860.324316
330.0229770.15750.437755
340.0102590.07030.472115
350.1208430.82850.2058
360.042720.29290.385453
37-0.053251-0.36510.358349
38-0.017147-0.11760.453462
39-0.002508-0.01720.493176
400.0625410.42880.335028
410.0423750.29050.386352
420.0059020.04050.483949
430.0137370.09420.462686
440.0224090.15360.439281
450.0477580.32740.372405
460.0261160.1790.429336
47NANANA
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2062691.41410.08196
20.197561.35440.091042
30.1810411.24120.110353
4-0.202395-1.38750.085909
50.1347030.92350.180238
60.0945740.64840.259951
7-0.228807-1.56860.061723
80.202841.39060.085448
90.0547690.37550.354498
10-0.140746-0.96490.169765
11-0.054549-0.3740.355054
12-0.382835-2.62460.005833
130.0517240.35460.362237
14-0.023105-0.15840.437409
150.1772431.21510.115195
16-0.038671-0.26510.39604
17-0.016947-0.11620.454001
18-0.012881-0.08830.465004
19-0.260065-1.78290.04053
20-0.15647-1.07270.144441
210.0787740.540.295858
22-0.038661-0.2650.396067
23-0.144647-0.99170.163222
24-0.129717-0.88930.189187
250.1605111.10040.138379
260.0015110.01040.495889
27-0.035349-0.24230.404784
28-0.036256-0.24860.402394
290.1102810.7560.226697
300.0174090.11930.452754
31-0.064188-0.44010.330958
32-0.188322-1.29110.101497
33-0.027251-0.18680.426301
34-0.041024-0.28120.389878
35-0.038851-0.26640.395567
36-0.007421-0.05090.479819
37-0.010659-0.07310.471028
380.010310.07070.471976
39-0.028945-0.19840.421781
40-0.068596-0.47030.320167
410.0319230.21890.413855
42-0.030439-0.20870.4178
43-0.04734-0.32450.373482
44-0.134403-0.92140.180769
450.0878830.60250.27487
46-0.030873-0.21170.416646
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.206269 & 1.4141 & 0.08196 \tabularnewline
2 & 0.19756 & 1.3544 & 0.091042 \tabularnewline
3 & 0.181041 & 1.2412 & 0.110353 \tabularnewline
4 & -0.202395 & -1.3875 & 0.085909 \tabularnewline
5 & 0.134703 & 0.9235 & 0.180238 \tabularnewline
6 & 0.094574 & 0.6484 & 0.259951 \tabularnewline
7 & -0.228807 & -1.5686 & 0.061723 \tabularnewline
8 & 0.20284 & 1.3906 & 0.085448 \tabularnewline
9 & 0.054769 & 0.3755 & 0.354498 \tabularnewline
10 & -0.140746 & -0.9649 & 0.169765 \tabularnewline
11 & -0.054549 & -0.374 & 0.355054 \tabularnewline
12 & -0.382835 & -2.6246 & 0.005833 \tabularnewline
13 & 0.051724 & 0.3546 & 0.362237 \tabularnewline
14 & -0.023105 & -0.1584 & 0.437409 \tabularnewline
15 & 0.177243 & 1.2151 & 0.115195 \tabularnewline
16 & -0.038671 & -0.2651 & 0.39604 \tabularnewline
17 & -0.016947 & -0.1162 & 0.454001 \tabularnewline
18 & -0.012881 & -0.0883 & 0.465004 \tabularnewline
19 & -0.260065 & -1.7829 & 0.04053 \tabularnewline
20 & -0.15647 & -1.0727 & 0.144441 \tabularnewline
21 & 0.078774 & 0.54 & 0.295858 \tabularnewline
22 & -0.038661 & -0.265 & 0.396067 \tabularnewline
23 & -0.144647 & -0.9917 & 0.163222 \tabularnewline
24 & -0.129717 & -0.8893 & 0.189187 \tabularnewline
25 & 0.160511 & 1.1004 & 0.138379 \tabularnewline
26 & 0.001511 & 0.0104 & 0.495889 \tabularnewline
27 & -0.035349 & -0.2423 & 0.404784 \tabularnewline
28 & -0.036256 & -0.2486 & 0.402394 \tabularnewline
29 & 0.110281 & 0.756 & 0.226697 \tabularnewline
30 & 0.017409 & 0.1193 & 0.452754 \tabularnewline
31 & -0.064188 & -0.4401 & 0.330958 \tabularnewline
32 & -0.188322 & -1.2911 & 0.101497 \tabularnewline
33 & -0.027251 & -0.1868 & 0.426301 \tabularnewline
34 & -0.041024 & -0.2812 & 0.389878 \tabularnewline
35 & -0.038851 & -0.2664 & 0.395567 \tabularnewline
36 & -0.007421 & -0.0509 & 0.479819 \tabularnewline
37 & -0.010659 & -0.0731 & 0.471028 \tabularnewline
38 & 0.01031 & 0.0707 & 0.471976 \tabularnewline
39 & -0.028945 & -0.1984 & 0.421781 \tabularnewline
40 & -0.068596 & -0.4703 & 0.320167 \tabularnewline
41 & 0.031923 & 0.2189 & 0.413855 \tabularnewline
42 & -0.030439 & -0.2087 & 0.4178 \tabularnewline
43 & -0.04734 & -0.3245 & 0.373482 \tabularnewline
44 & -0.134403 & -0.9214 & 0.180769 \tabularnewline
45 & 0.087883 & 0.6025 & 0.27487 \tabularnewline
46 & -0.030873 & -0.2117 & 0.416646 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112412&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]0.206269[/C][C]1.4141[/C][C]0.08196[/C][/ROW]
[ROW][C]2[/C][C]0.19756[/C][C]1.3544[/C][C]0.091042[/C][/ROW]
[ROW][C]3[/C][C]0.181041[/C][C]1.2412[/C][C]0.110353[/C][/ROW]
[ROW][C]4[/C][C]-0.202395[/C][C]-1.3875[/C][C]0.085909[/C][/ROW]
[ROW][C]5[/C][C]0.134703[/C][C]0.9235[/C][C]0.180238[/C][/ROW]
[ROW][C]6[/C][C]0.094574[/C][C]0.6484[/C][C]0.259951[/C][/ROW]
[ROW][C]7[/C][C]-0.228807[/C][C]-1.5686[/C][C]0.061723[/C][/ROW]
[ROW][C]8[/C][C]0.20284[/C][C]1.3906[/C][C]0.085448[/C][/ROW]
[ROW][C]9[/C][C]0.054769[/C][C]0.3755[/C][C]0.354498[/C][/ROW]
[ROW][C]10[/C][C]-0.140746[/C][C]-0.9649[/C][C]0.169765[/C][/ROW]
[ROW][C]11[/C][C]-0.054549[/C][C]-0.374[/C][C]0.355054[/C][/ROW]
[ROW][C]12[/C][C]-0.382835[/C][C]-2.6246[/C][C]0.005833[/C][/ROW]
[ROW][C]13[/C][C]0.051724[/C][C]0.3546[/C][C]0.362237[/C][/ROW]
[ROW][C]14[/C][C]-0.023105[/C][C]-0.1584[/C][C]0.437409[/C][/ROW]
[ROW][C]15[/C][C]0.177243[/C][C]1.2151[/C][C]0.115195[/C][/ROW]
[ROW][C]16[/C][C]-0.038671[/C][C]-0.2651[/C][C]0.39604[/C][/ROW]
[ROW][C]17[/C][C]-0.016947[/C][C]-0.1162[/C][C]0.454001[/C][/ROW]
[ROW][C]18[/C][C]-0.012881[/C][C]-0.0883[/C][C]0.465004[/C][/ROW]
[ROW][C]19[/C][C]-0.260065[/C][C]-1.7829[/C][C]0.04053[/C][/ROW]
[ROW][C]20[/C][C]-0.15647[/C][C]-1.0727[/C][C]0.144441[/C][/ROW]
[ROW][C]21[/C][C]0.078774[/C][C]0.54[/C][C]0.295858[/C][/ROW]
[ROW][C]22[/C][C]-0.038661[/C][C]-0.265[/C][C]0.396067[/C][/ROW]
[ROW][C]23[/C][C]-0.144647[/C][C]-0.9917[/C][C]0.163222[/C][/ROW]
[ROW][C]24[/C][C]-0.129717[/C][C]-0.8893[/C][C]0.189187[/C][/ROW]
[ROW][C]25[/C][C]0.160511[/C][C]1.1004[/C][C]0.138379[/C][/ROW]
[ROW][C]26[/C][C]0.001511[/C][C]0.0104[/C][C]0.495889[/C][/ROW]
[ROW][C]27[/C][C]-0.035349[/C][C]-0.2423[/C][C]0.404784[/C][/ROW]
[ROW][C]28[/C][C]-0.036256[/C][C]-0.2486[/C][C]0.402394[/C][/ROW]
[ROW][C]29[/C][C]0.110281[/C][C]0.756[/C][C]0.226697[/C][/ROW]
[ROW][C]30[/C][C]0.017409[/C][C]0.1193[/C][C]0.452754[/C][/ROW]
[ROW][C]31[/C][C]-0.064188[/C][C]-0.4401[/C][C]0.330958[/C][/ROW]
[ROW][C]32[/C][C]-0.188322[/C][C]-1.2911[/C][C]0.101497[/C][/ROW]
[ROW][C]33[/C][C]-0.027251[/C][C]-0.1868[/C][C]0.426301[/C][/ROW]
[ROW][C]34[/C][C]-0.041024[/C][C]-0.2812[/C][C]0.389878[/C][/ROW]
[ROW][C]35[/C][C]-0.038851[/C][C]-0.2664[/C][C]0.395567[/C][/ROW]
[ROW][C]36[/C][C]-0.007421[/C][C]-0.0509[/C][C]0.479819[/C][/ROW]
[ROW][C]37[/C][C]-0.010659[/C][C]-0.0731[/C][C]0.471028[/C][/ROW]
[ROW][C]38[/C][C]0.01031[/C][C]0.0707[/C][C]0.471976[/C][/ROW]
[ROW][C]39[/C][C]-0.028945[/C][C]-0.1984[/C][C]0.421781[/C][/ROW]
[ROW][C]40[/C][C]-0.068596[/C][C]-0.4703[/C][C]0.320167[/C][/ROW]
[ROW][C]41[/C][C]0.031923[/C][C]0.2189[/C][C]0.413855[/C][/ROW]
[ROW][C]42[/C][C]-0.030439[/C][C]-0.2087[/C][C]0.4178[/C][/ROW]
[ROW][C]43[/C][C]-0.04734[/C][C]-0.3245[/C][C]0.373482[/C][/ROW]
[ROW][C]44[/C][C]-0.134403[/C][C]-0.9214[/C][C]0.180769[/C][/ROW]
[ROW][C]45[/C][C]0.087883[/C][C]0.6025[/C][C]0.27487[/C][/ROW]
[ROW][C]46[/C][C]-0.030873[/C][C]-0.2117[/C][C]0.416646[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112412&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112412&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
10.2062691.41410.08196
20.197561.35440.091042
30.1810411.24120.110353
4-0.202395-1.38750.085909
50.1347030.92350.180238
60.0945740.64840.259951
7-0.228807-1.56860.061723
80.202841.39060.085448
90.0547690.37550.354498
10-0.140746-0.96490.169765
11-0.054549-0.3740.355054
12-0.382835-2.62460.005833
130.0517240.35460.362237
14-0.023105-0.15840.437409
150.1772431.21510.115195
16-0.038671-0.26510.39604
17-0.016947-0.11620.454001
18-0.012881-0.08830.465004
19-0.260065-1.78290.04053
20-0.15647-1.07270.144441
210.0787740.540.295858
22-0.038661-0.2650.396067
23-0.144647-0.99170.163222
24-0.129717-0.88930.189187
250.1605111.10040.138379
260.0015110.01040.495889
27-0.035349-0.24230.404784
28-0.036256-0.24860.402394
290.1102810.7560.226697
300.0174090.11930.452754
31-0.064188-0.44010.330958
32-0.188322-1.29110.101497
33-0.027251-0.18680.426301
34-0.041024-0.28120.389878
35-0.038851-0.26640.395567
36-0.007421-0.05090.479819
37-0.010659-0.07310.471028
380.010310.07070.471976
39-0.028945-0.19840.421781
40-0.068596-0.47030.320167
410.0319230.21890.413855
42-0.030439-0.20870.4178
43-0.04734-0.32450.373482
44-0.134403-0.92140.180769
450.0878830.60250.27487
46-0.030873-0.21170.416646
47NANANA
48NANANA



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