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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 computationMon, 26 Nov 2012 05:43:20 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/26/t13539267083gzw1ed2gv26s97.htm/, Retrieved Tue, 30 Apr 2024 01:14:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=192973, Retrieved Tue, 30 Apr 2024 01:14:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Spectral Analysis] [Births] [2010-11-29 09:38:20] [b98453cac15ba1066b407e146608df68]
- RMPD            [(Partial) Autocorrelation Function] [WS 9 ACF] [2012-11-26 10:43:20] [5bcb27a14a37b739141501b3993fea08] [Current]
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Dataseries X:
9.676
8.642
9.402
9.610
9.294
9.448
10.319
9.548
9.801
9.596
8.923
9.746
9.829
9.125
9.782
9.441
9.162
9.915
10.444
10.209
9.985
9.842
9.429
10.132
9.849
9.172
10.313
9.819
9.955
10.048
10.082
10.541
10.208
10.233
9.439
9.963
10.158
9.225
10.474
9.757
10.490
10.281
10.444
10.640
10.695
10.786
9.832
9.747
10.411
9.511
10.402
9.701
10.540
10.112
10.915
11.183
10.384
10.834
9.886
10.216
10.943
9.867
10.203
10.837
10.573
10.647
11.502
10.656
10.866
10.835
9.945
10.331
10.718
9.462
10.579
10.633
10.346
10.757
11.207
11.013
11.015
10.765
10.042
10.661




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192973&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192973&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192973&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 time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.526715-4.79863e-06
2-0.024961-0.22740.410334
30.2974152.70960.004091
4-0.310849-2.8320.002902
50.0386470.35210.36283
60.1061040.96670.168262
7-0.121776-1.10940.135225
8-0.152745-1.39160.083885
90.2890032.63290.005047
10-0.130746-1.19120.118494
11-0.241446-2.19970.015305
120.6084575.54330
13-0.415504-3.78540.000145
140.1145061.04320.149942
150.1662871.5150.066792
16-0.269709-2.45720.008043
170.1193221.08710.140075
18-0.079389-0.72330.235774
19-0.000563-0.00510.497961
20-0.060471-0.55090.291585
210.092020.83830.202124
220.0213420.19440.423154
23-0.207111-1.88690.031337
240.385253.50980.000364
25-0.206325-1.87970.031828
260.0560380.51050.305518
270.0400660.3650.358014
28-0.079393-0.72330.235764
29-0.002828-0.02580.489753
30-0.045014-0.41010.341397
310.0572240.52130.301761
32-0.127021-1.15720.125252
330.0876150.79820.213513
340.0790830.72050.236626
35-0.217645-1.98280.025346
360.2688312.44920.008212
37-0.03894-0.35480.361834
38-0.06708-0.61110.271393
390.0306210.2790.390481
400.0251420.22910.409693
41-0.102514-0.93390.176521
420.0335580.30570.38029
430.0698590.63640.263119
44-0.185431-1.68940.047452
450.1055090.96120.169615
460.1025950.93470.17633
47-0.236377-2.15350.01709
480.2398922.18550.015834

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.526715 & -4.7986 & 3e-06 \tabularnewline
2 & -0.024961 & -0.2274 & 0.410334 \tabularnewline
3 & 0.297415 & 2.7096 & 0.004091 \tabularnewline
4 & -0.310849 & -2.832 & 0.002902 \tabularnewline
5 & 0.038647 & 0.3521 & 0.36283 \tabularnewline
6 & 0.106104 & 0.9667 & 0.168262 \tabularnewline
7 & -0.121776 & -1.1094 & 0.135225 \tabularnewline
8 & -0.152745 & -1.3916 & 0.083885 \tabularnewline
9 & 0.289003 & 2.6329 & 0.005047 \tabularnewline
10 & -0.130746 & -1.1912 & 0.118494 \tabularnewline
11 & -0.241446 & -2.1997 & 0.015305 \tabularnewline
12 & 0.608457 & 5.5433 & 0 \tabularnewline
13 & -0.415504 & -3.7854 & 0.000145 \tabularnewline
14 & 0.114506 & 1.0432 & 0.149942 \tabularnewline
15 & 0.166287 & 1.515 & 0.066792 \tabularnewline
16 & -0.269709 & -2.4572 & 0.008043 \tabularnewline
17 & 0.119322 & 1.0871 & 0.140075 \tabularnewline
18 & -0.079389 & -0.7233 & 0.235774 \tabularnewline
19 & -0.000563 & -0.0051 & 0.497961 \tabularnewline
20 & -0.060471 & -0.5509 & 0.291585 \tabularnewline
21 & 0.09202 & 0.8383 & 0.202124 \tabularnewline
22 & 0.021342 & 0.1944 & 0.423154 \tabularnewline
23 & -0.207111 & -1.8869 & 0.031337 \tabularnewline
24 & 0.38525 & 3.5098 & 0.000364 \tabularnewline
25 & -0.206325 & -1.8797 & 0.031828 \tabularnewline
26 & 0.056038 & 0.5105 & 0.305518 \tabularnewline
27 & 0.040066 & 0.365 & 0.358014 \tabularnewline
28 & -0.079393 & -0.7233 & 0.235764 \tabularnewline
29 & -0.002828 & -0.0258 & 0.489753 \tabularnewline
30 & -0.045014 & -0.4101 & 0.341397 \tabularnewline
31 & 0.057224 & 0.5213 & 0.301761 \tabularnewline
32 & -0.127021 & -1.1572 & 0.125252 \tabularnewline
33 & 0.087615 & 0.7982 & 0.213513 \tabularnewline
34 & 0.079083 & 0.7205 & 0.236626 \tabularnewline
35 & -0.217645 & -1.9828 & 0.025346 \tabularnewline
36 & 0.268831 & 2.4492 & 0.008212 \tabularnewline
37 & -0.03894 & -0.3548 & 0.361834 \tabularnewline
38 & -0.06708 & -0.6111 & 0.271393 \tabularnewline
39 & 0.030621 & 0.279 & 0.390481 \tabularnewline
40 & 0.025142 & 0.2291 & 0.409693 \tabularnewline
41 & -0.102514 & -0.9339 & 0.176521 \tabularnewline
42 & 0.033558 & 0.3057 & 0.38029 \tabularnewline
43 & 0.069859 & 0.6364 & 0.263119 \tabularnewline
44 & -0.185431 & -1.6894 & 0.047452 \tabularnewline
45 & 0.105509 & 0.9612 & 0.169615 \tabularnewline
46 & 0.102595 & 0.9347 & 0.17633 \tabularnewline
47 & -0.236377 & -2.1535 & 0.01709 \tabularnewline
48 & 0.239892 & 2.1855 & 0.015834 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192973&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]-0.526715[/C][C]-4.7986[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.024961[/C][C]-0.2274[/C][C]0.410334[/C][/ROW]
[ROW][C]3[/C][C]0.297415[/C][C]2.7096[/C][C]0.004091[/C][/ROW]
[ROW][C]4[/C][C]-0.310849[/C][C]-2.832[/C][C]0.002902[/C][/ROW]
[ROW][C]5[/C][C]0.038647[/C][C]0.3521[/C][C]0.36283[/C][/ROW]
[ROW][C]6[/C][C]0.106104[/C][C]0.9667[/C][C]0.168262[/C][/ROW]
[ROW][C]7[/C][C]-0.121776[/C][C]-1.1094[/C][C]0.135225[/C][/ROW]
[ROW][C]8[/C][C]-0.152745[/C][C]-1.3916[/C][C]0.083885[/C][/ROW]
[ROW][C]9[/C][C]0.289003[/C][C]2.6329[/C][C]0.005047[/C][/ROW]
[ROW][C]10[/C][C]-0.130746[/C][C]-1.1912[/C][C]0.118494[/C][/ROW]
[ROW][C]11[/C][C]-0.241446[/C][C]-2.1997[/C][C]0.015305[/C][/ROW]
[ROW][C]12[/C][C]0.608457[/C][C]5.5433[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.415504[/C][C]-3.7854[/C][C]0.000145[/C][/ROW]
[ROW][C]14[/C][C]0.114506[/C][C]1.0432[/C][C]0.149942[/C][/ROW]
[ROW][C]15[/C][C]0.166287[/C][C]1.515[/C][C]0.066792[/C][/ROW]
[ROW][C]16[/C][C]-0.269709[/C][C]-2.4572[/C][C]0.008043[/C][/ROW]
[ROW][C]17[/C][C]0.119322[/C][C]1.0871[/C][C]0.140075[/C][/ROW]
[ROW][C]18[/C][C]-0.079389[/C][C]-0.7233[/C][C]0.235774[/C][/ROW]
[ROW][C]19[/C][C]-0.000563[/C][C]-0.0051[/C][C]0.497961[/C][/ROW]
[ROW][C]20[/C][C]-0.060471[/C][C]-0.5509[/C][C]0.291585[/C][/ROW]
[ROW][C]21[/C][C]0.09202[/C][C]0.8383[/C][C]0.202124[/C][/ROW]
[ROW][C]22[/C][C]0.021342[/C][C]0.1944[/C][C]0.423154[/C][/ROW]
[ROW][C]23[/C][C]-0.207111[/C][C]-1.8869[/C][C]0.031337[/C][/ROW]
[ROW][C]24[/C][C]0.38525[/C][C]3.5098[/C][C]0.000364[/C][/ROW]
[ROW][C]25[/C][C]-0.206325[/C][C]-1.8797[/C][C]0.031828[/C][/ROW]
[ROW][C]26[/C][C]0.056038[/C][C]0.5105[/C][C]0.305518[/C][/ROW]
[ROW][C]27[/C][C]0.040066[/C][C]0.365[/C][C]0.358014[/C][/ROW]
[ROW][C]28[/C][C]-0.079393[/C][C]-0.7233[/C][C]0.235764[/C][/ROW]
[ROW][C]29[/C][C]-0.002828[/C][C]-0.0258[/C][C]0.489753[/C][/ROW]
[ROW][C]30[/C][C]-0.045014[/C][C]-0.4101[/C][C]0.341397[/C][/ROW]
[ROW][C]31[/C][C]0.057224[/C][C]0.5213[/C][C]0.301761[/C][/ROW]
[ROW][C]32[/C][C]-0.127021[/C][C]-1.1572[/C][C]0.125252[/C][/ROW]
[ROW][C]33[/C][C]0.087615[/C][C]0.7982[/C][C]0.213513[/C][/ROW]
[ROW][C]34[/C][C]0.079083[/C][C]0.7205[/C][C]0.236626[/C][/ROW]
[ROW][C]35[/C][C]-0.217645[/C][C]-1.9828[/C][C]0.025346[/C][/ROW]
[ROW][C]36[/C][C]0.268831[/C][C]2.4492[/C][C]0.008212[/C][/ROW]
[ROW][C]37[/C][C]-0.03894[/C][C]-0.3548[/C][C]0.361834[/C][/ROW]
[ROW][C]38[/C][C]-0.06708[/C][C]-0.6111[/C][C]0.271393[/C][/ROW]
[ROW][C]39[/C][C]0.030621[/C][C]0.279[/C][C]0.390481[/C][/ROW]
[ROW][C]40[/C][C]0.025142[/C][C]0.2291[/C][C]0.409693[/C][/ROW]
[ROW][C]41[/C][C]-0.102514[/C][C]-0.9339[/C][C]0.176521[/C][/ROW]
[ROW][C]42[/C][C]0.033558[/C][C]0.3057[/C][C]0.38029[/C][/ROW]
[ROW][C]43[/C][C]0.069859[/C][C]0.6364[/C][C]0.263119[/C][/ROW]
[ROW][C]44[/C][C]-0.185431[/C][C]-1.6894[/C][C]0.047452[/C][/ROW]
[ROW][C]45[/C][C]0.105509[/C][C]0.9612[/C][C]0.169615[/C][/ROW]
[ROW][C]46[/C][C]0.102595[/C][C]0.9347[/C][C]0.17633[/C][/ROW]
[ROW][C]47[/C][C]-0.236377[/C][C]-2.1535[/C][C]0.01709[/C][/ROW]
[ROW][C]48[/C][C]0.239892[/C][C]2.1855[/C][C]0.015834[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192973&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192973&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
1-0.526715-4.79863e-06
2-0.024961-0.22740.410334
30.2974152.70960.004091
4-0.310849-2.8320.002902
50.0386470.35210.36283
60.1061040.96670.168262
7-0.121776-1.10940.135225
8-0.152745-1.39160.083885
90.2890032.63290.005047
10-0.130746-1.19120.118494
11-0.241446-2.19970.015305
120.6084575.54330
13-0.415504-3.78540.000145
140.1145061.04320.149942
150.1662871.5150.066792
16-0.269709-2.45720.008043
170.1193221.08710.140075
18-0.079389-0.72330.235774
19-0.000563-0.00510.497961
20-0.060471-0.55090.291585
210.092020.83830.202124
220.0213420.19440.423154
23-0.207111-1.88690.031337
240.385253.50980.000364
25-0.206325-1.87970.031828
260.0560380.51050.305518
270.0400660.3650.358014
28-0.079393-0.72330.235764
29-0.002828-0.02580.489753
30-0.045014-0.41010.341397
310.0572240.52130.301761
32-0.127021-1.15720.125252
330.0876150.79820.213513
340.0790830.72050.236626
35-0.217645-1.98280.025346
360.2688312.44920.008212
37-0.03894-0.35480.361834
38-0.06708-0.61110.271393
390.0306210.2790.390481
400.0251420.22910.409693
41-0.102514-0.93390.176521
420.0335580.30570.38029
430.0698590.63640.263119
44-0.185431-1.68940.047452
450.1055090.96120.169615
460.1025950.93470.17633
47-0.236377-2.15350.01709
480.2398922.18550.015834







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.526715-4.79863e-06
2-0.41849-3.81260.000132
30.0978840.89180.187549
4-0.098058-0.89340.187126
5-0.198466-1.80810.037106
6-0.140494-1.280.102062
7-0.071257-0.64920.259005
8-0.423621-3.85940.000112
9-0.194221-1.76940.040247
10-0.08416-0.76670.222707
11-0.566709-5.1631e-06
12-0.020615-0.18780.42574
13-0.06176-0.56270.28759
140.0650950.5930.277381
15-0.040746-0.37120.355714
160.0627460.57160.284553
170.161691.47310.072258
18-0.223825-2.03910.022309
19-0.075821-0.69080.245821
200.090740.82670.205393
21-0.135546-1.23490.11018
220.0245680.22380.41172
23-0.07388-0.67310.251384
24-0.031834-0.290.38626
250.0326340.29730.383485
260.0535740.48810.31339
27-0.047541-0.43310.333025
280.0445920.40630.3428
29-0.084219-0.76730.222549
300.0833180.75910.224983
310.0121850.1110.455938
320.0354350.32280.373819
330.0465150.42380.336415
34-0.013247-0.12070.452115
350.0057380.05230.479218
36-0.159301-1.45130.075233
370.039250.35760.360782
380.0691680.63020.265164
39-0.205789-1.87480.032167
40-0.062973-0.57370.283857
41-0.036708-0.33440.36945
42-0.018152-0.16540.434525
430.0478190.43570.332109
440.0409910.37340.354883
45-0.008181-0.07450.470384
46-0.010028-0.09140.463714
47-0.059064-0.53810.295973
480.0630520.57440.283616

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.526715 & -4.7986 & 3e-06 \tabularnewline
2 & -0.41849 & -3.8126 & 0.000132 \tabularnewline
3 & 0.097884 & 0.8918 & 0.187549 \tabularnewline
4 & -0.098058 & -0.8934 & 0.187126 \tabularnewline
5 & -0.198466 & -1.8081 & 0.037106 \tabularnewline
6 & -0.140494 & -1.28 & 0.102062 \tabularnewline
7 & -0.071257 & -0.6492 & 0.259005 \tabularnewline
8 & -0.423621 & -3.8594 & 0.000112 \tabularnewline
9 & -0.194221 & -1.7694 & 0.040247 \tabularnewline
10 & -0.08416 & -0.7667 & 0.222707 \tabularnewline
11 & -0.566709 & -5.163 & 1e-06 \tabularnewline
12 & -0.020615 & -0.1878 & 0.42574 \tabularnewline
13 & -0.06176 & -0.5627 & 0.28759 \tabularnewline
14 & 0.065095 & 0.593 & 0.277381 \tabularnewline
15 & -0.040746 & -0.3712 & 0.355714 \tabularnewline
16 & 0.062746 & 0.5716 & 0.284553 \tabularnewline
17 & 0.16169 & 1.4731 & 0.072258 \tabularnewline
18 & -0.223825 & -2.0391 & 0.022309 \tabularnewline
19 & -0.075821 & -0.6908 & 0.245821 \tabularnewline
20 & 0.09074 & 0.8267 & 0.205393 \tabularnewline
21 & -0.135546 & -1.2349 & 0.11018 \tabularnewline
22 & 0.024568 & 0.2238 & 0.41172 \tabularnewline
23 & -0.07388 & -0.6731 & 0.251384 \tabularnewline
24 & -0.031834 & -0.29 & 0.38626 \tabularnewline
25 & 0.032634 & 0.2973 & 0.383485 \tabularnewline
26 & 0.053574 & 0.4881 & 0.31339 \tabularnewline
27 & -0.047541 & -0.4331 & 0.333025 \tabularnewline
28 & 0.044592 & 0.4063 & 0.3428 \tabularnewline
29 & -0.084219 & -0.7673 & 0.222549 \tabularnewline
30 & 0.083318 & 0.7591 & 0.224983 \tabularnewline
31 & 0.012185 & 0.111 & 0.455938 \tabularnewline
32 & 0.035435 & 0.3228 & 0.373819 \tabularnewline
33 & 0.046515 & 0.4238 & 0.336415 \tabularnewline
34 & -0.013247 & -0.1207 & 0.452115 \tabularnewline
35 & 0.005738 & 0.0523 & 0.479218 \tabularnewline
36 & -0.159301 & -1.4513 & 0.075233 \tabularnewline
37 & 0.03925 & 0.3576 & 0.360782 \tabularnewline
38 & 0.069168 & 0.6302 & 0.265164 \tabularnewline
39 & -0.205789 & -1.8748 & 0.032167 \tabularnewline
40 & -0.062973 & -0.5737 & 0.283857 \tabularnewline
41 & -0.036708 & -0.3344 & 0.36945 \tabularnewline
42 & -0.018152 & -0.1654 & 0.434525 \tabularnewline
43 & 0.047819 & 0.4357 & 0.332109 \tabularnewline
44 & 0.040991 & 0.3734 & 0.354883 \tabularnewline
45 & -0.008181 & -0.0745 & 0.470384 \tabularnewline
46 & -0.010028 & -0.0914 & 0.463714 \tabularnewline
47 & -0.059064 & -0.5381 & 0.295973 \tabularnewline
48 & 0.063052 & 0.5744 & 0.283616 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=192973&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]-0.526715[/C][C]-4.7986[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.41849[/C][C]-3.8126[/C][C]0.000132[/C][/ROW]
[ROW][C]3[/C][C]0.097884[/C][C]0.8918[/C][C]0.187549[/C][/ROW]
[ROW][C]4[/C][C]-0.098058[/C][C]-0.8934[/C][C]0.187126[/C][/ROW]
[ROW][C]5[/C][C]-0.198466[/C][C]-1.8081[/C][C]0.037106[/C][/ROW]
[ROW][C]6[/C][C]-0.140494[/C][C]-1.28[/C][C]0.102062[/C][/ROW]
[ROW][C]7[/C][C]-0.071257[/C][C]-0.6492[/C][C]0.259005[/C][/ROW]
[ROW][C]8[/C][C]-0.423621[/C][C]-3.8594[/C][C]0.000112[/C][/ROW]
[ROW][C]9[/C][C]-0.194221[/C][C]-1.7694[/C][C]0.040247[/C][/ROW]
[ROW][C]10[/C][C]-0.08416[/C][C]-0.7667[/C][C]0.222707[/C][/ROW]
[ROW][C]11[/C][C]-0.566709[/C][C]-5.163[/C][C]1e-06[/C][/ROW]
[ROW][C]12[/C][C]-0.020615[/C][C]-0.1878[/C][C]0.42574[/C][/ROW]
[ROW][C]13[/C][C]-0.06176[/C][C]-0.5627[/C][C]0.28759[/C][/ROW]
[ROW][C]14[/C][C]0.065095[/C][C]0.593[/C][C]0.277381[/C][/ROW]
[ROW][C]15[/C][C]-0.040746[/C][C]-0.3712[/C][C]0.355714[/C][/ROW]
[ROW][C]16[/C][C]0.062746[/C][C]0.5716[/C][C]0.284553[/C][/ROW]
[ROW][C]17[/C][C]0.16169[/C][C]1.4731[/C][C]0.072258[/C][/ROW]
[ROW][C]18[/C][C]-0.223825[/C][C]-2.0391[/C][C]0.022309[/C][/ROW]
[ROW][C]19[/C][C]-0.075821[/C][C]-0.6908[/C][C]0.245821[/C][/ROW]
[ROW][C]20[/C][C]0.09074[/C][C]0.8267[/C][C]0.205393[/C][/ROW]
[ROW][C]21[/C][C]-0.135546[/C][C]-1.2349[/C][C]0.11018[/C][/ROW]
[ROW][C]22[/C][C]0.024568[/C][C]0.2238[/C][C]0.41172[/C][/ROW]
[ROW][C]23[/C][C]-0.07388[/C][C]-0.6731[/C][C]0.251384[/C][/ROW]
[ROW][C]24[/C][C]-0.031834[/C][C]-0.29[/C][C]0.38626[/C][/ROW]
[ROW][C]25[/C][C]0.032634[/C][C]0.2973[/C][C]0.383485[/C][/ROW]
[ROW][C]26[/C][C]0.053574[/C][C]0.4881[/C][C]0.31339[/C][/ROW]
[ROW][C]27[/C][C]-0.047541[/C][C]-0.4331[/C][C]0.333025[/C][/ROW]
[ROW][C]28[/C][C]0.044592[/C][C]0.4063[/C][C]0.3428[/C][/ROW]
[ROW][C]29[/C][C]-0.084219[/C][C]-0.7673[/C][C]0.222549[/C][/ROW]
[ROW][C]30[/C][C]0.083318[/C][C]0.7591[/C][C]0.224983[/C][/ROW]
[ROW][C]31[/C][C]0.012185[/C][C]0.111[/C][C]0.455938[/C][/ROW]
[ROW][C]32[/C][C]0.035435[/C][C]0.3228[/C][C]0.373819[/C][/ROW]
[ROW][C]33[/C][C]0.046515[/C][C]0.4238[/C][C]0.336415[/C][/ROW]
[ROW][C]34[/C][C]-0.013247[/C][C]-0.1207[/C][C]0.452115[/C][/ROW]
[ROW][C]35[/C][C]0.005738[/C][C]0.0523[/C][C]0.479218[/C][/ROW]
[ROW][C]36[/C][C]-0.159301[/C][C]-1.4513[/C][C]0.075233[/C][/ROW]
[ROW][C]37[/C][C]0.03925[/C][C]0.3576[/C][C]0.360782[/C][/ROW]
[ROW][C]38[/C][C]0.069168[/C][C]0.6302[/C][C]0.265164[/C][/ROW]
[ROW][C]39[/C][C]-0.205789[/C][C]-1.8748[/C][C]0.032167[/C][/ROW]
[ROW][C]40[/C][C]-0.062973[/C][C]-0.5737[/C][C]0.283857[/C][/ROW]
[ROW][C]41[/C][C]-0.036708[/C][C]-0.3344[/C][C]0.36945[/C][/ROW]
[ROW][C]42[/C][C]-0.018152[/C][C]-0.1654[/C][C]0.434525[/C][/ROW]
[ROW][C]43[/C][C]0.047819[/C][C]0.4357[/C][C]0.332109[/C][/ROW]
[ROW][C]44[/C][C]0.040991[/C][C]0.3734[/C][C]0.354883[/C][/ROW]
[ROW][C]45[/C][C]-0.008181[/C][C]-0.0745[/C][C]0.470384[/C][/ROW]
[ROW][C]46[/C][C]-0.010028[/C][C]-0.0914[/C][C]0.463714[/C][/ROW]
[ROW][C]47[/C][C]-0.059064[/C][C]-0.5381[/C][C]0.295973[/C][/ROW]
[ROW][C]48[/C][C]0.063052[/C][C]0.5744[/C][C]0.283616[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=192973&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=192973&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
1-0.526715-4.79863e-06
2-0.41849-3.81260.000132
30.0978840.89180.187549
4-0.098058-0.89340.187126
5-0.198466-1.80810.037106
6-0.140494-1.280.102062
7-0.071257-0.64920.259005
8-0.423621-3.85940.000112
9-0.194221-1.76940.040247
10-0.08416-0.76670.222707
11-0.566709-5.1631e-06
12-0.020615-0.18780.42574
13-0.06176-0.56270.28759
140.0650950.5930.277381
15-0.040746-0.37120.355714
160.0627460.57160.284553
170.161691.47310.072258
18-0.223825-2.03910.022309
19-0.075821-0.69080.245821
200.090740.82670.205393
21-0.135546-1.23490.11018
220.0245680.22380.41172
23-0.07388-0.67310.251384
24-0.031834-0.290.38626
250.0326340.29730.383485
260.0535740.48810.31339
27-0.047541-0.43310.333025
280.0445920.40630.3428
29-0.084219-0.76730.222549
300.0833180.75910.224983
310.0121850.1110.455938
320.0354350.32280.373819
330.0465150.42380.336415
34-0.013247-0.12070.452115
350.0057380.05230.479218
36-0.159301-1.45130.075233
370.039250.35760.360782
380.0691680.63020.265164
39-0.205789-1.87480.032167
40-0.062973-0.57370.283857
41-0.036708-0.33440.36945
42-0.018152-0.16540.434525
430.0478190.43570.332109
440.0409910.37340.354883
45-0.008181-0.07450.470384
46-0.010028-0.09140.463714
47-0.059064-0.53810.295973
480.0630520.57440.283616



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 ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')