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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, 05 Dec 2010 14:08:10 +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/05/t1291558033tt9b7bh7hfjhpiv.htm/, Retrieved Wed, 01 May 2024 20:07:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105404, Retrieved Wed, 01 May 2024 20:07:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [Ws 9 - ACF] [2010-12-05 13:32:17] [603e2f5305d3a2a4e062624458fa1155]
-   P       [(Partial) Autocorrelation Function] [Ws 9 - ACF (d = 1)] [2010-12-05 13:40:03] [603e2f5305d3a2a4e062624458fa1155]
-   P           [(Partial) Autocorrelation Function] [Ws 9 - ACF (d = 1)] [2010-12-05 14:08:10] [0829c729852d8a4b1b0c41cf0848af95] [Current]
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Dataseries X:
167.16
179.84
174.44
180.35
193.17
195.16
202.43
189.91
195.98
212.09
205.81
204.31
196.07
199.98
199.10
198.31
195.72
223.04
238.41
259.73
326.54
335.15
321.81
368.62
369.59
425.00
439.72
362.23
328.76
348.55
328.18
329.34
295.55
237.38
226.85
220.14
239.36
224.69
230.98
233.47
256.70
253.41
224.95
210.37
191.09
198.85
211.04
206.25
201.51
194.54
191.07
192.82
181.88
157.67
195.82
246.25
271.69
270.29




Summary of computational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105404&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105404&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105404&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2467741.86310.033802
2-0.051665-0.39010.348972
30.0676630.51080.305717
4-0.055001-0.41520.33976
50.2329681.75890.041983
60.1974461.49070.070779
7-0.264446-1.99650.025331
8-0.186958-1.41150.081766
9-0.017229-0.13010.448482
10-0.084249-0.63610.26364
110.0397670.30020.382547
12-0.164394-1.24120.109817
13-0.314141-2.37170.010553
14-0.027717-0.20930.417496
150.1276450.96370.169635
160.1167470.88140.190897
170.0464750.35090.363486
18-0.104144-0.78630.217482
19-0.020068-0.15150.440055
200.1681741.26970.104677
21-0.027453-0.20730.41827
22-0.124957-0.94340.174728
23-0.132208-0.99810.161213
24-0.186257-1.40620.082546
250.0351070.26510.395962
260.011620.08770.465199
27-0.185603-1.40130.083277
28-0.183291-1.38380.085905
29-0.049741-0.37550.354328
300.0516110.38970.349122
310.0912250.68870.246893
320.0092560.06990.472268
33-0.066016-0.49840.310057
340.035850.27070.393814
350.1134010.85620.197747
360.0731470.55220.291468
370.0778490.58770.279513
380.0246090.18580.426633
390.0031920.02410.490428
40-0.012938-0.09770.461264
41-0.002479-0.01870.492567
420.0014710.01110.495588
43-0.023949-0.18080.428579
44-0.037926-0.28630.38783
450.0056360.04250.483105
460.0256210.19340.423653
47-0.003728-0.02810.488823
48-0.019382-0.14630.442088

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.246774 & 1.8631 & 0.033802 \tabularnewline
2 & -0.051665 & -0.3901 & 0.348972 \tabularnewline
3 & 0.067663 & 0.5108 & 0.305717 \tabularnewline
4 & -0.055001 & -0.4152 & 0.33976 \tabularnewline
5 & 0.232968 & 1.7589 & 0.041983 \tabularnewline
6 & 0.197446 & 1.4907 & 0.070779 \tabularnewline
7 & -0.264446 & -1.9965 & 0.025331 \tabularnewline
8 & -0.186958 & -1.4115 & 0.081766 \tabularnewline
9 & -0.017229 & -0.1301 & 0.448482 \tabularnewline
10 & -0.084249 & -0.6361 & 0.26364 \tabularnewline
11 & 0.039767 & 0.3002 & 0.382547 \tabularnewline
12 & -0.164394 & -1.2412 & 0.109817 \tabularnewline
13 & -0.314141 & -2.3717 & 0.010553 \tabularnewline
14 & -0.027717 & -0.2093 & 0.417496 \tabularnewline
15 & 0.127645 & 0.9637 & 0.169635 \tabularnewline
16 & 0.116747 & 0.8814 & 0.190897 \tabularnewline
17 & 0.046475 & 0.3509 & 0.363486 \tabularnewline
18 & -0.104144 & -0.7863 & 0.217482 \tabularnewline
19 & -0.020068 & -0.1515 & 0.440055 \tabularnewline
20 & 0.168174 & 1.2697 & 0.104677 \tabularnewline
21 & -0.027453 & -0.2073 & 0.41827 \tabularnewline
22 & -0.124957 & -0.9434 & 0.174728 \tabularnewline
23 & -0.132208 & -0.9981 & 0.161213 \tabularnewline
24 & -0.186257 & -1.4062 & 0.082546 \tabularnewline
25 & 0.035107 & 0.2651 & 0.395962 \tabularnewline
26 & 0.01162 & 0.0877 & 0.465199 \tabularnewline
27 & -0.185603 & -1.4013 & 0.083277 \tabularnewline
28 & -0.183291 & -1.3838 & 0.085905 \tabularnewline
29 & -0.049741 & -0.3755 & 0.354328 \tabularnewline
30 & 0.051611 & 0.3897 & 0.349122 \tabularnewline
31 & 0.091225 & 0.6887 & 0.246893 \tabularnewline
32 & 0.009256 & 0.0699 & 0.472268 \tabularnewline
33 & -0.066016 & -0.4984 & 0.310057 \tabularnewline
34 & 0.03585 & 0.2707 & 0.393814 \tabularnewline
35 & 0.113401 & 0.8562 & 0.197747 \tabularnewline
36 & 0.073147 & 0.5522 & 0.291468 \tabularnewline
37 & 0.077849 & 0.5877 & 0.279513 \tabularnewline
38 & 0.024609 & 0.1858 & 0.426633 \tabularnewline
39 & 0.003192 & 0.0241 & 0.490428 \tabularnewline
40 & -0.012938 & -0.0977 & 0.461264 \tabularnewline
41 & -0.002479 & -0.0187 & 0.492567 \tabularnewline
42 & 0.001471 & 0.0111 & 0.495588 \tabularnewline
43 & -0.023949 & -0.1808 & 0.428579 \tabularnewline
44 & -0.037926 & -0.2863 & 0.38783 \tabularnewline
45 & 0.005636 & 0.0425 & 0.483105 \tabularnewline
46 & 0.025621 & 0.1934 & 0.423653 \tabularnewline
47 & -0.003728 & -0.0281 & 0.488823 \tabularnewline
48 & -0.019382 & -0.1463 & 0.442088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105404&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]0.246774[/C][C]1.8631[/C][C]0.033802[/C][/ROW]
[ROW][C]2[/C][C]-0.051665[/C][C]-0.3901[/C][C]0.348972[/C][/ROW]
[ROW][C]3[/C][C]0.067663[/C][C]0.5108[/C][C]0.305717[/C][/ROW]
[ROW][C]4[/C][C]-0.055001[/C][C]-0.4152[/C][C]0.33976[/C][/ROW]
[ROW][C]5[/C][C]0.232968[/C][C]1.7589[/C][C]0.041983[/C][/ROW]
[ROW][C]6[/C][C]0.197446[/C][C]1.4907[/C][C]0.070779[/C][/ROW]
[ROW][C]7[/C][C]-0.264446[/C][C]-1.9965[/C][C]0.025331[/C][/ROW]
[ROW][C]8[/C][C]-0.186958[/C][C]-1.4115[/C][C]0.081766[/C][/ROW]
[ROW][C]9[/C][C]-0.017229[/C][C]-0.1301[/C][C]0.448482[/C][/ROW]
[ROW][C]10[/C][C]-0.084249[/C][C]-0.6361[/C][C]0.26364[/C][/ROW]
[ROW][C]11[/C][C]0.039767[/C][C]0.3002[/C][C]0.382547[/C][/ROW]
[ROW][C]12[/C][C]-0.164394[/C][C]-1.2412[/C][C]0.109817[/C][/ROW]
[ROW][C]13[/C][C]-0.314141[/C][C]-2.3717[/C][C]0.010553[/C][/ROW]
[ROW][C]14[/C][C]-0.027717[/C][C]-0.2093[/C][C]0.417496[/C][/ROW]
[ROW][C]15[/C][C]0.127645[/C][C]0.9637[/C][C]0.169635[/C][/ROW]
[ROW][C]16[/C][C]0.116747[/C][C]0.8814[/C][C]0.190897[/C][/ROW]
[ROW][C]17[/C][C]0.046475[/C][C]0.3509[/C][C]0.363486[/C][/ROW]
[ROW][C]18[/C][C]-0.104144[/C][C]-0.7863[/C][C]0.217482[/C][/ROW]
[ROW][C]19[/C][C]-0.020068[/C][C]-0.1515[/C][C]0.440055[/C][/ROW]
[ROW][C]20[/C][C]0.168174[/C][C]1.2697[/C][C]0.104677[/C][/ROW]
[ROW][C]21[/C][C]-0.027453[/C][C]-0.2073[/C][C]0.41827[/C][/ROW]
[ROW][C]22[/C][C]-0.124957[/C][C]-0.9434[/C][C]0.174728[/C][/ROW]
[ROW][C]23[/C][C]-0.132208[/C][C]-0.9981[/C][C]0.161213[/C][/ROW]
[ROW][C]24[/C][C]-0.186257[/C][C]-1.4062[/C][C]0.082546[/C][/ROW]
[ROW][C]25[/C][C]0.035107[/C][C]0.2651[/C][C]0.395962[/C][/ROW]
[ROW][C]26[/C][C]0.01162[/C][C]0.0877[/C][C]0.465199[/C][/ROW]
[ROW][C]27[/C][C]-0.185603[/C][C]-1.4013[/C][C]0.083277[/C][/ROW]
[ROW][C]28[/C][C]-0.183291[/C][C]-1.3838[/C][C]0.085905[/C][/ROW]
[ROW][C]29[/C][C]-0.049741[/C][C]-0.3755[/C][C]0.354328[/C][/ROW]
[ROW][C]30[/C][C]0.051611[/C][C]0.3897[/C][C]0.349122[/C][/ROW]
[ROW][C]31[/C][C]0.091225[/C][C]0.6887[/C][C]0.246893[/C][/ROW]
[ROW][C]32[/C][C]0.009256[/C][C]0.0699[/C][C]0.472268[/C][/ROW]
[ROW][C]33[/C][C]-0.066016[/C][C]-0.4984[/C][C]0.310057[/C][/ROW]
[ROW][C]34[/C][C]0.03585[/C][C]0.2707[/C][C]0.393814[/C][/ROW]
[ROW][C]35[/C][C]0.113401[/C][C]0.8562[/C][C]0.197747[/C][/ROW]
[ROW][C]36[/C][C]0.073147[/C][C]0.5522[/C][C]0.291468[/C][/ROW]
[ROW][C]37[/C][C]0.077849[/C][C]0.5877[/C][C]0.279513[/C][/ROW]
[ROW][C]38[/C][C]0.024609[/C][C]0.1858[/C][C]0.426633[/C][/ROW]
[ROW][C]39[/C][C]0.003192[/C][C]0.0241[/C][C]0.490428[/C][/ROW]
[ROW][C]40[/C][C]-0.012938[/C][C]-0.0977[/C][C]0.461264[/C][/ROW]
[ROW][C]41[/C][C]-0.002479[/C][C]-0.0187[/C][C]0.492567[/C][/ROW]
[ROW][C]42[/C][C]0.001471[/C][C]0.0111[/C][C]0.495588[/C][/ROW]
[ROW][C]43[/C][C]-0.023949[/C][C]-0.1808[/C][C]0.428579[/C][/ROW]
[ROW][C]44[/C][C]-0.037926[/C][C]-0.2863[/C][C]0.38783[/C][/ROW]
[ROW][C]45[/C][C]0.005636[/C][C]0.0425[/C][C]0.483105[/C][/ROW]
[ROW][C]46[/C][C]0.025621[/C][C]0.1934[/C][C]0.423653[/C][/ROW]
[ROW][C]47[/C][C]-0.003728[/C][C]-0.0281[/C][C]0.488823[/C][/ROW]
[ROW][C]48[/C][C]-0.019382[/C][C]-0.1463[/C][C]0.442088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105404&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105404&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
10.2467741.86310.033802
2-0.051665-0.39010.348972
30.0676630.51080.305717
4-0.055001-0.41520.33976
50.2329681.75890.041983
60.1974461.49070.070779
7-0.264446-1.99650.025331
8-0.186958-1.41150.081766
9-0.017229-0.13010.448482
10-0.084249-0.63610.26364
110.0397670.30020.382547
12-0.164394-1.24120.109817
13-0.314141-2.37170.010553
14-0.027717-0.20930.417496
150.1276450.96370.169635
160.1167470.88140.190897
170.0464750.35090.363486
18-0.104144-0.78630.217482
19-0.020068-0.15150.440055
200.1681741.26970.104677
21-0.027453-0.20730.41827
22-0.124957-0.94340.174728
23-0.132208-0.99810.161213
24-0.186257-1.40620.082546
250.0351070.26510.395962
260.011620.08770.465199
27-0.185603-1.40130.083277
28-0.183291-1.38380.085905
29-0.049741-0.37550.354328
300.0516110.38970.349122
310.0912250.68870.246893
320.0092560.06990.472268
33-0.066016-0.49840.310057
340.035850.27070.393814
350.1134010.85620.197747
360.0731470.55220.291468
370.0778490.58770.279513
380.0246090.18580.426633
390.0031920.02410.490428
40-0.012938-0.09770.461264
41-0.002479-0.01870.492567
420.0014710.01110.495588
43-0.023949-0.18080.428579
44-0.037926-0.28630.38783
450.0056360.04250.483105
460.0256210.19340.423653
47-0.003728-0.02810.488823
48-0.019382-0.14630.442088







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2467741.86310.033802
2-0.119862-0.90490.184654
30.1204820.90960.183427
4-0.123136-0.92970.178235
50.3338132.52020.007276
6-0.005176-0.03910.484483
7-0.294409-2.22270.015108
8-0.074415-0.56180.28822
90.0462660.34930.364077
10-0.109227-0.82460.206506
11-0.012277-0.09270.463237
12-0.14358-1.0840.141464
13-0.075973-0.57360.284253
14-0.000727-0.00550.49782
150.1451121.09560.138936
160.0880940.66510.254335
17-0.025435-0.1920.424199
18-0.013053-0.09860.46092
190.034750.26240.396995
20-0.010557-0.07970.468377
21-0.247956-1.8720.033168
22-0.098326-0.74230.230464
23-0.065135-0.49180.31239
24-0.130168-0.98270.164943
250.0009290.0070.497214
26-0.036597-0.27630.391658
27-0.02373-0.17920.429224
28-0.100878-0.76160.224716
290.1263450.95390.172084
300.0580880.43860.331321
31-0.103247-0.77950.219454
32-0.001363-0.01030.495911
330.0165460.12490.450514
34-0.098184-0.74130.230786
35-0.131087-0.98970.163256
36-0.068295-0.51560.304059
370.1150280.86840.194398
38-0.006468-0.04880.48061
390.0339110.2560.399426
40-0.113491-0.85680.197562
410.0102620.07750.469257
420.0269980.20380.419606
430.0254750.19230.424084
44-0.045794-0.34570.365405
45-0.058385-0.44080.330513
460.0112280.08480.46637
47-0.025606-0.19330.423697
48-0.116082-0.87640.192245

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.246774 & 1.8631 & 0.033802 \tabularnewline
2 & -0.119862 & -0.9049 & 0.184654 \tabularnewline
3 & 0.120482 & 0.9096 & 0.183427 \tabularnewline
4 & -0.123136 & -0.9297 & 0.178235 \tabularnewline
5 & 0.333813 & 2.5202 & 0.007276 \tabularnewline
6 & -0.005176 & -0.0391 & 0.484483 \tabularnewline
7 & -0.294409 & -2.2227 & 0.015108 \tabularnewline
8 & -0.074415 & -0.5618 & 0.28822 \tabularnewline
9 & 0.046266 & 0.3493 & 0.364077 \tabularnewline
10 & -0.109227 & -0.8246 & 0.206506 \tabularnewline
11 & -0.012277 & -0.0927 & 0.463237 \tabularnewline
12 & -0.14358 & -1.084 & 0.141464 \tabularnewline
13 & -0.075973 & -0.5736 & 0.284253 \tabularnewline
14 & -0.000727 & -0.0055 & 0.49782 \tabularnewline
15 & 0.145112 & 1.0956 & 0.138936 \tabularnewline
16 & 0.088094 & 0.6651 & 0.254335 \tabularnewline
17 & -0.025435 & -0.192 & 0.424199 \tabularnewline
18 & -0.013053 & -0.0986 & 0.46092 \tabularnewline
19 & 0.03475 & 0.2624 & 0.396995 \tabularnewline
20 & -0.010557 & -0.0797 & 0.468377 \tabularnewline
21 & -0.247956 & -1.872 & 0.033168 \tabularnewline
22 & -0.098326 & -0.7423 & 0.230464 \tabularnewline
23 & -0.065135 & -0.4918 & 0.31239 \tabularnewline
24 & -0.130168 & -0.9827 & 0.164943 \tabularnewline
25 & 0.000929 & 0.007 & 0.497214 \tabularnewline
26 & -0.036597 & -0.2763 & 0.391658 \tabularnewline
27 & -0.02373 & -0.1792 & 0.429224 \tabularnewline
28 & -0.100878 & -0.7616 & 0.224716 \tabularnewline
29 & 0.126345 & 0.9539 & 0.172084 \tabularnewline
30 & 0.058088 & 0.4386 & 0.331321 \tabularnewline
31 & -0.103247 & -0.7795 & 0.219454 \tabularnewline
32 & -0.001363 & -0.0103 & 0.495911 \tabularnewline
33 & 0.016546 & 0.1249 & 0.450514 \tabularnewline
34 & -0.098184 & -0.7413 & 0.230786 \tabularnewline
35 & -0.131087 & -0.9897 & 0.163256 \tabularnewline
36 & -0.068295 & -0.5156 & 0.304059 \tabularnewline
37 & 0.115028 & 0.8684 & 0.194398 \tabularnewline
38 & -0.006468 & -0.0488 & 0.48061 \tabularnewline
39 & 0.033911 & 0.256 & 0.399426 \tabularnewline
40 & -0.113491 & -0.8568 & 0.197562 \tabularnewline
41 & 0.010262 & 0.0775 & 0.469257 \tabularnewline
42 & 0.026998 & 0.2038 & 0.419606 \tabularnewline
43 & 0.025475 & 0.1923 & 0.424084 \tabularnewline
44 & -0.045794 & -0.3457 & 0.365405 \tabularnewline
45 & -0.058385 & -0.4408 & 0.330513 \tabularnewline
46 & 0.011228 & 0.0848 & 0.46637 \tabularnewline
47 & -0.025606 & -0.1933 & 0.423697 \tabularnewline
48 & -0.116082 & -0.8764 & 0.192245 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105404&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]0.246774[/C][C]1.8631[/C][C]0.033802[/C][/ROW]
[ROW][C]2[/C][C]-0.119862[/C][C]-0.9049[/C][C]0.184654[/C][/ROW]
[ROW][C]3[/C][C]0.120482[/C][C]0.9096[/C][C]0.183427[/C][/ROW]
[ROW][C]4[/C][C]-0.123136[/C][C]-0.9297[/C][C]0.178235[/C][/ROW]
[ROW][C]5[/C][C]0.333813[/C][C]2.5202[/C][C]0.007276[/C][/ROW]
[ROW][C]6[/C][C]-0.005176[/C][C]-0.0391[/C][C]0.484483[/C][/ROW]
[ROW][C]7[/C][C]-0.294409[/C][C]-2.2227[/C][C]0.015108[/C][/ROW]
[ROW][C]8[/C][C]-0.074415[/C][C]-0.5618[/C][C]0.28822[/C][/ROW]
[ROW][C]9[/C][C]0.046266[/C][C]0.3493[/C][C]0.364077[/C][/ROW]
[ROW][C]10[/C][C]-0.109227[/C][C]-0.8246[/C][C]0.206506[/C][/ROW]
[ROW][C]11[/C][C]-0.012277[/C][C]-0.0927[/C][C]0.463237[/C][/ROW]
[ROW][C]12[/C][C]-0.14358[/C][C]-1.084[/C][C]0.141464[/C][/ROW]
[ROW][C]13[/C][C]-0.075973[/C][C]-0.5736[/C][C]0.284253[/C][/ROW]
[ROW][C]14[/C][C]-0.000727[/C][C]-0.0055[/C][C]0.49782[/C][/ROW]
[ROW][C]15[/C][C]0.145112[/C][C]1.0956[/C][C]0.138936[/C][/ROW]
[ROW][C]16[/C][C]0.088094[/C][C]0.6651[/C][C]0.254335[/C][/ROW]
[ROW][C]17[/C][C]-0.025435[/C][C]-0.192[/C][C]0.424199[/C][/ROW]
[ROW][C]18[/C][C]-0.013053[/C][C]-0.0986[/C][C]0.46092[/C][/ROW]
[ROW][C]19[/C][C]0.03475[/C][C]0.2624[/C][C]0.396995[/C][/ROW]
[ROW][C]20[/C][C]-0.010557[/C][C]-0.0797[/C][C]0.468377[/C][/ROW]
[ROW][C]21[/C][C]-0.247956[/C][C]-1.872[/C][C]0.033168[/C][/ROW]
[ROW][C]22[/C][C]-0.098326[/C][C]-0.7423[/C][C]0.230464[/C][/ROW]
[ROW][C]23[/C][C]-0.065135[/C][C]-0.4918[/C][C]0.31239[/C][/ROW]
[ROW][C]24[/C][C]-0.130168[/C][C]-0.9827[/C][C]0.164943[/C][/ROW]
[ROW][C]25[/C][C]0.000929[/C][C]0.007[/C][C]0.497214[/C][/ROW]
[ROW][C]26[/C][C]-0.036597[/C][C]-0.2763[/C][C]0.391658[/C][/ROW]
[ROW][C]27[/C][C]-0.02373[/C][C]-0.1792[/C][C]0.429224[/C][/ROW]
[ROW][C]28[/C][C]-0.100878[/C][C]-0.7616[/C][C]0.224716[/C][/ROW]
[ROW][C]29[/C][C]0.126345[/C][C]0.9539[/C][C]0.172084[/C][/ROW]
[ROW][C]30[/C][C]0.058088[/C][C]0.4386[/C][C]0.331321[/C][/ROW]
[ROW][C]31[/C][C]-0.103247[/C][C]-0.7795[/C][C]0.219454[/C][/ROW]
[ROW][C]32[/C][C]-0.001363[/C][C]-0.0103[/C][C]0.495911[/C][/ROW]
[ROW][C]33[/C][C]0.016546[/C][C]0.1249[/C][C]0.450514[/C][/ROW]
[ROW][C]34[/C][C]-0.098184[/C][C]-0.7413[/C][C]0.230786[/C][/ROW]
[ROW][C]35[/C][C]-0.131087[/C][C]-0.9897[/C][C]0.163256[/C][/ROW]
[ROW][C]36[/C][C]-0.068295[/C][C]-0.5156[/C][C]0.304059[/C][/ROW]
[ROW][C]37[/C][C]0.115028[/C][C]0.8684[/C][C]0.194398[/C][/ROW]
[ROW][C]38[/C][C]-0.006468[/C][C]-0.0488[/C][C]0.48061[/C][/ROW]
[ROW][C]39[/C][C]0.033911[/C][C]0.256[/C][C]0.399426[/C][/ROW]
[ROW][C]40[/C][C]-0.113491[/C][C]-0.8568[/C][C]0.197562[/C][/ROW]
[ROW][C]41[/C][C]0.010262[/C][C]0.0775[/C][C]0.469257[/C][/ROW]
[ROW][C]42[/C][C]0.026998[/C][C]0.2038[/C][C]0.419606[/C][/ROW]
[ROW][C]43[/C][C]0.025475[/C][C]0.1923[/C][C]0.424084[/C][/ROW]
[ROW][C]44[/C][C]-0.045794[/C][C]-0.3457[/C][C]0.365405[/C][/ROW]
[ROW][C]45[/C][C]-0.058385[/C][C]-0.4408[/C][C]0.330513[/C][/ROW]
[ROW][C]46[/C][C]0.011228[/C][C]0.0848[/C][C]0.46637[/C][/ROW]
[ROW][C]47[/C][C]-0.025606[/C][C]-0.1933[/C][C]0.423697[/C][/ROW]
[ROW][C]48[/C][C]-0.116082[/C][C]-0.8764[/C][C]0.192245[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105404&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105404&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
10.2467741.86310.033802
2-0.119862-0.90490.184654
30.1204820.90960.183427
4-0.123136-0.92970.178235
50.3338132.52020.007276
6-0.005176-0.03910.484483
7-0.294409-2.22270.015108
8-0.074415-0.56180.28822
90.0462660.34930.364077
10-0.109227-0.82460.206506
11-0.012277-0.09270.463237
12-0.14358-1.0840.141464
13-0.075973-0.57360.284253
14-0.000727-0.00550.49782
150.1451121.09560.138936
160.0880940.66510.254335
17-0.025435-0.1920.424199
18-0.013053-0.09860.46092
190.034750.26240.396995
20-0.010557-0.07970.468377
21-0.247956-1.8720.033168
22-0.098326-0.74230.230464
23-0.065135-0.49180.31239
24-0.130168-0.98270.164943
250.0009290.0070.497214
26-0.036597-0.27630.391658
27-0.02373-0.17920.429224
28-0.100878-0.76160.224716
290.1263450.95390.172084
300.0580880.43860.331321
31-0.103247-0.77950.219454
32-0.001363-0.01030.495911
330.0165460.12490.450514
34-0.098184-0.74130.230786
35-0.131087-0.98970.163256
36-0.068295-0.51560.304059
370.1150280.86840.194398
38-0.006468-0.04880.48061
390.0339110.2560.399426
40-0.113491-0.85680.197562
410.0102620.07750.469257
420.0269980.20380.419606
430.0254750.19230.424084
44-0.045794-0.34570.365405
45-0.058385-0.44080.330513
460.0112280.08480.46637
47-0.025606-0.19330.423697
48-0.116082-0.87640.192245



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')