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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 computationWed, 22 Dec 2010 14:21:53 +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/22/t1293027600hyrsxuhtr9vl1oj.htm/, Retrieved Sun, 05 May 2024 20:36:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114243, Retrieved Sun, 05 May 2024 20:36:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
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] [] [2010-12-07 16:47:16] [0175b38674e1402e67841c9c82e4a5a3]
-   PD        [(Partial) Autocorrelation Function] [] [2010-12-22 14:21:53] [c2e23af56713b360851e64c7775b3f2b] [Current]
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Dataseries X:
13.193
15.234
14.718
16.961
13.945
15.876
16.226
18.316
16.748
17.904
17.209
18.950
17.225
18.710
17.236
18.687
17.580
19.568
17.381
19.580
17.260
18.661
15.658
18.674
15.908
17.475
17.725
19.562
16.368
19.555
17.743
19.867
15.703
19.324
18.162
19.074
15.323
19.704
18.375
18.352
13.927
17.795
16.761
18.902
16.239
19.158
18.279
15.698
16.239
18.431
18.414
19.801
14.995
18.706
18.232
19.409
16.263
19.017
20.298
19.891
15.203
17.845
17.502
18.532
15.737
17.770
17.224
17.601
14.940
18.507
17.635
19.392
15.699
17.661
18.243
19.643
15.770
17.344
17.229
17.322
16.152
17.919
16.918
18.114
16.308
17.759
16.021
17.952
15.954
17.762
16.610
17.751
15.458
18.106
15.990
15.349
13.185
15.409
16.007
16.633
14.800
15.974
15.693




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=114243&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=114243&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114243&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
10.0210710.21380.415546
20.3780253.83650.000108
3-0.118303-1.20060.116322
40.6404576.49990
5-0.128761-1.30680.097099
60.2446642.48310.00732
7-0.217718-2.20960.014674
80.4790934.86232e-06
9-0.280364-2.84540.002676
100.1600551.62440.053675
11-0.298926-3.03380.001529
120.4164194.22622.6e-05
13-0.256093-2.59910.00536
140.1541231.56420.060421
15-0.277048-2.81170.00295
160.4045984.10624e-05
17-0.241014-2.4460.008069
180.175291.7790.039094
19-0.244057-2.47690.00744
200.4314764.3791.4e-05
21-0.220589-2.23870.013662
220.1541361.56430.060406
23-0.257061-2.60890.005217
240.3610813.66460.000197
25-0.228862-2.32270.011081
260.0949450.96360.168755
27-0.276588-2.80710.00299
280.293272.97640.001818
29-0.269386-2.7340.003684
300.1039951.05540.146848
31-0.259926-2.6380.004817
320.3025363.07040.001367
33-0.279099-2.83250.002778
340.0897030.91040.182372
35-0.209837-2.12960.017793
360.2647892.68730.0042
37-0.245478-2.49130.007162
380.0963950.97830.165108
39-0.186197-1.88970.030805
400.2565382.60360.005294
41-0.225216-2.28570.01216
420.0842440.8550.197271
43-0.192649-1.95520.026636
440.1717241.74280.042176
45-0.216595-2.19820.015087
460.0594330.60320.273858
47-0.162578-1.650.050996
480.1844611.87210.032017

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.021071 & 0.2138 & 0.415546 \tabularnewline
2 & 0.378025 & 3.8365 & 0.000108 \tabularnewline
3 & -0.118303 & -1.2006 & 0.116322 \tabularnewline
4 & 0.640457 & 6.4999 & 0 \tabularnewline
5 & -0.128761 & -1.3068 & 0.097099 \tabularnewline
6 & 0.244664 & 2.4831 & 0.00732 \tabularnewline
7 & -0.217718 & -2.2096 & 0.014674 \tabularnewline
8 & 0.479093 & 4.8623 & 2e-06 \tabularnewline
9 & -0.280364 & -2.8454 & 0.002676 \tabularnewline
10 & 0.160055 & 1.6244 & 0.053675 \tabularnewline
11 & -0.298926 & -3.0338 & 0.001529 \tabularnewline
12 & 0.416419 & 4.2262 & 2.6e-05 \tabularnewline
13 & -0.256093 & -2.5991 & 0.00536 \tabularnewline
14 & 0.154123 & 1.5642 & 0.060421 \tabularnewline
15 & -0.277048 & -2.8117 & 0.00295 \tabularnewline
16 & 0.404598 & 4.1062 & 4e-05 \tabularnewline
17 & -0.241014 & -2.446 & 0.008069 \tabularnewline
18 & 0.17529 & 1.779 & 0.039094 \tabularnewline
19 & -0.244057 & -2.4769 & 0.00744 \tabularnewline
20 & 0.431476 & 4.379 & 1.4e-05 \tabularnewline
21 & -0.220589 & -2.2387 & 0.013662 \tabularnewline
22 & 0.154136 & 1.5643 & 0.060406 \tabularnewline
23 & -0.257061 & -2.6089 & 0.005217 \tabularnewline
24 & 0.361081 & 3.6646 & 0.000197 \tabularnewline
25 & -0.228862 & -2.3227 & 0.011081 \tabularnewline
26 & 0.094945 & 0.9636 & 0.168755 \tabularnewline
27 & -0.276588 & -2.8071 & 0.00299 \tabularnewline
28 & 0.29327 & 2.9764 & 0.001818 \tabularnewline
29 & -0.269386 & -2.734 & 0.003684 \tabularnewline
30 & 0.103995 & 1.0554 & 0.146848 \tabularnewline
31 & -0.259926 & -2.638 & 0.004817 \tabularnewline
32 & 0.302536 & 3.0704 & 0.001367 \tabularnewline
33 & -0.279099 & -2.8325 & 0.002778 \tabularnewline
34 & 0.089703 & 0.9104 & 0.182372 \tabularnewline
35 & -0.209837 & -2.1296 & 0.017793 \tabularnewline
36 & 0.264789 & 2.6873 & 0.0042 \tabularnewline
37 & -0.245478 & -2.4913 & 0.007162 \tabularnewline
38 & 0.096395 & 0.9783 & 0.165108 \tabularnewline
39 & -0.186197 & -1.8897 & 0.030805 \tabularnewline
40 & 0.256538 & 2.6036 & 0.005294 \tabularnewline
41 & -0.225216 & -2.2857 & 0.01216 \tabularnewline
42 & 0.084244 & 0.855 & 0.197271 \tabularnewline
43 & -0.192649 & -1.9552 & 0.026636 \tabularnewline
44 & 0.171724 & 1.7428 & 0.042176 \tabularnewline
45 & -0.216595 & -2.1982 & 0.015087 \tabularnewline
46 & 0.059433 & 0.6032 & 0.273858 \tabularnewline
47 & -0.162578 & -1.65 & 0.050996 \tabularnewline
48 & 0.184461 & 1.8721 & 0.032017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114243&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]0.021071[/C][C]0.2138[/C][C]0.415546[/C][/ROW]
[ROW][C]2[/C][C]0.378025[/C][C]3.8365[/C][C]0.000108[/C][/ROW]
[ROW][C]3[/C][C]-0.118303[/C][C]-1.2006[/C][C]0.116322[/C][/ROW]
[ROW][C]4[/C][C]0.640457[/C][C]6.4999[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]-0.128761[/C][C]-1.3068[/C][C]0.097099[/C][/ROW]
[ROW][C]6[/C][C]0.244664[/C][C]2.4831[/C][C]0.00732[/C][/ROW]
[ROW][C]7[/C][C]-0.217718[/C][C]-2.2096[/C][C]0.014674[/C][/ROW]
[ROW][C]8[/C][C]0.479093[/C][C]4.8623[/C][C]2e-06[/C][/ROW]
[ROW][C]9[/C][C]-0.280364[/C][C]-2.8454[/C][C]0.002676[/C][/ROW]
[ROW][C]10[/C][C]0.160055[/C][C]1.6244[/C][C]0.053675[/C][/ROW]
[ROW][C]11[/C][C]-0.298926[/C][C]-3.0338[/C][C]0.001529[/C][/ROW]
[ROW][C]12[/C][C]0.416419[/C][C]4.2262[/C][C]2.6e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.256093[/C][C]-2.5991[/C][C]0.00536[/C][/ROW]
[ROW][C]14[/C][C]0.154123[/C][C]1.5642[/C][C]0.060421[/C][/ROW]
[ROW][C]15[/C][C]-0.277048[/C][C]-2.8117[/C][C]0.00295[/C][/ROW]
[ROW][C]16[/C][C]0.404598[/C][C]4.1062[/C][C]4e-05[/C][/ROW]
[ROW][C]17[/C][C]-0.241014[/C][C]-2.446[/C][C]0.008069[/C][/ROW]
[ROW][C]18[/C][C]0.17529[/C][C]1.779[/C][C]0.039094[/C][/ROW]
[ROW][C]19[/C][C]-0.244057[/C][C]-2.4769[/C][C]0.00744[/C][/ROW]
[ROW][C]20[/C][C]0.431476[/C][C]4.379[/C][C]1.4e-05[/C][/ROW]
[ROW][C]21[/C][C]-0.220589[/C][C]-2.2387[/C][C]0.013662[/C][/ROW]
[ROW][C]22[/C][C]0.154136[/C][C]1.5643[/C][C]0.060406[/C][/ROW]
[ROW][C]23[/C][C]-0.257061[/C][C]-2.6089[/C][C]0.005217[/C][/ROW]
[ROW][C]24[/C][C]0.361081[/C][C]3.6646[/C][C]0.000197[/C][/ROW]
[ROW][C]25[/C][C]-0.228862[/C][C]-2.3227[/C][C]0.011081[/C][/ROW]
[ROW][C]26[/C][C]0.094945[/C][C]0.9636[/C][C]0.168755[/C][/ROW]
[ROW][C]27[/C][C]-0.276588[/C][C]-2.8071[/C][C]0.00299[/C][/ROW]
[ROW][C]28[/C][C]0.29327[/C][C]2.9764[/C][C]0.001818[/C][/ROW]
[ROW][C]29[/C][C]-0.269386[/C][C]-2.734[/C][C]0.003684[/C][/ROW]
[ROW][C]30[/C][C]0.103995[/C][C]1.0554[/C][C]0.146848[/C][/ROW]
[ROW][C]31[/C][C]-0.259926[/C][C]-2.638[/C][C]0.004817[/C][/ROW]
[ROW][C]32[/C][C]0.302536[/C][C]3.0704[/C][C]0.001367[/C][/ROW]
[ROW][C]33[/C][C]-0.279099[/C][C]-2.8325[/C][C]0.002778[/C][/ROW]
[ROW][C]34[/C][C]0.089703[/C][C]0.9104[/C][C]0.182372[/C][/ROW]
[ROW][C]35[/C][C]-0.209837[/C][C]-2.1296[/C][C]0.017793[/C][/ROW]
[ROW][C]36[/C][C]0.264789[/C][C]2.6873[/C][C]0.0042[/C][/ROW]
[ROW][C]37[/C][C]-0.245478[/C][C]-2.4913[/C][C]0.007162[/C][/ROW]
[ROW][C]38[/C][C]0.096395[/C][C]0.9783[/C][C]0.165108[/C][/ROW]
[ROW][C]39[/C][C]-0.186197[/C][C]-1.8897[/C][C]0.030805[/C][/ROW]
[ROW][C]40[/C][C]0.256538[/C][C]2.6036[/C][C]0.005294[/C][/ROW]
[ROW][C]41[/C][C]-0.225216[/C][C]-2.2857[/C][C]0.01216[/C][/ROW]
[ROW][C]42[/C][C]0.084244[/C][C]0.855[/C][C]0.197271[/C][/ROW]
[ROW][C]43[/C][C]-0.192649[/C][C]-1.9552[/C][C]0.026636[/C][/ROW]
[ROW][C]44[/C][C]0.171724[/C][C]1.7428[/C][C]0.042176[/C][/ROW]
[ROW][C]45[/C][C]-0.216595[/C][C]-2.1982[/C][C]0.015087[/C][/ROW]
[ROW][C]46[/C][C]0.059433[/C][C]0.6032[/C][C]0.273858[/C][/ROW]
[ROW][C]47[/C][C]-0.162578[/C][C]-1.65[/C][C]0.050996[/C][/ROW]
[ROW][C]48[/C][C]0.184461[/C][C]1.8721[/C][C]0.032017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114243&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114243&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
10.0210710.21380.415546
20.3780253.83650.000108
3-0.118303-1.20060.116322
40.6404576.49990
5-0.128761-1.30680.097099
60.2446642.48310.00732
7-0.217718-2.20960.014674
80.4790934.86232e-06
9-0.280364-2.84540.002676
100.1600551.62440.053675
11-0.298926-3.03380.001529
120.4164194.22622.6e-05
13-0.256093-2.59910.00536
140.1541231.56420.060421
15-0.277048-2.81170.00295
160.4045984.10624e-05
17-0.241014-2.4460.008069
180.175291.7790.039094
19-0.244057-2.47690.00744
200.4314764.3791.4e-05
21-0.220589-2.23870.013662
220.1541361.56430.060406
23-0.257061-2.60890.005217
240.3610813.66460.000197
25-0.228862-2.32270.011081
260.0949450.96360.168755
27-0.276588-2.80710.00299
280.293272.97640.001818
29-0.269386-2.7340.003684
300.1039951.05540.146848
31-0.259926-2.6380.004817
320.3025363.07040.001367
33-0.279099-2.83250.002778
340.0897030.91040.182372
35-0.209837-2.12960.017793
360.2647892.68730.0042
37-0.245478-2.49130.007162
380.0963950.97830.165108
39-0.186197-1.88970.030805
400.2565382.60360.005294
41-0.225216-2.28570.01216
420.0842440.8550.197271
43-0.192649-1.95520.026636
440.1717241.74280.042176
45-0.216595-2.19820.015087
460.0594330.60320.273858
47-0.162578-1.650.050996
480.1844611.87210.032017







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0210710.21380.415546
20.3777493.83370.000109
3-0.153127-1.55410.061618
40.6076736.16720
5-0.293268-2.97630.001818
6-0.061355-0.62270.267435
70.0126260.12810.449144
80.1291161.31040.09649
9-0.28932-2.93630.002049
100.0667360.67730.249869
11-0.025034-0.25410.399976
120.1137191.15410.12556
130.0221460.22480.411306
14-0.052414-0.53190.297953
150.0366570.3720.355318
160.0848680.86130.195532
17-0.073655-0.74750.228228
18-0.004305-0.04370.482618
190.0702510.7130.238739
200.0612570.62170.26776
21-0.064947-0.65910.255638
22-0.05059-0.51340.304373
230.0142590.14470.442611
24-0.047906-0.48620.313931
250.0192190.19510.422867
26-0.113685-1.15380.125631
270.0519750.52750.299494
28-0.040197-0.4080.342077
29-0.037068-0.37620.35377
300.0879510.89260.187075
310.0071190.07220.471273
320.0002980.0030.498798
33-0.107848-1.09450.138136
340.0285680.28990.386226
350.0807460.81950.2072
36-0.140119-1.42210.079015
370.0339230.34430.365669
380.0244410.2480.402296
390.0090160.09150.463637
40-0.049821-0.50560.307097
410.0562080.57050.284807
42-0.068113-0.69130.245476
43-0.027313-0.27720.391092
44-0.114983-1.1670.122962
450.0740430.75150.227047
460.0186980.18980.424933
470.0166940.16940.432896
480.0240090.24370.403989

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.021071 & 0.2138 & 0.415546 \tabularnewline
2 & 0.377749 & 3.8337 & 0.000109 \tabularnewline
3 & -0.153127 & -1.5541 & 0.061618 \tabularnewline
4 & 0.607673 & 6.1672 & 0 \tabularnewline
5 & -0.293268 & -2.9763 & 0.001818 \tabularnewline
6 & -0.061355 & -0.6227 & 0.267435 \tabularnewline
7 & 0.012626 & 0.1281 & 0.449144 \tabularnewline
8 & 0.129116 & 1.3104 & 0.09649 \tabularnewline
9 & -0.28932 & -2.9363 & 0.002049 \tabularnewline
10 & 0.066736 & 0.6773 & 0.249869 \tabularnewline
11 & -0.025034 & -0.2541 & 0.399976 \tabularnewline
12 & 0.113719 & 1.1541 & 0.12556 \tabularnewline
13 & 0.022146 & 0.2248 & 0.411306 \tabularnewline
14 & -0.052414 & -0.5319 & 0.297953 \tabularnewline
15 & 0.036657 & 0.372 & 0.355318 \tabularnewline
16 & 0.084868 & 0.8613 & 0.195532 \tabularnewline
17 & -0.073655 & -0.7475 & 0.228228 \tabularnewline
18 & -0.004305 & -0.0437 & 0.482618 \tabularnewline
19 & 0.070251 & 0.713 & 0.238739 \tabularnewline
20 & 0.061257 & 0.6217 & 0.26776 \tabularnewline
21 & -0.064947 & -0.6591 & 0.255638 \tabularnewline
22 & -0.05059 & -0.5134 & 0.304373 \tabularnewline
23 & 0.014259 & 0.1447 & 0.442611 \tabularnewline
24 & -0.047906 & -0.4862 & 0.313931 \tabularnewline
25 & 0.019219 & 0.1951 & 0.422867 \tabularnewline
26 & -0.113685 & -1.1538 & 0.125631 \tabularnewline
27 & 0.051975 & 0.5275 & 0.299494 \tabularnewline
28 & -0.040197 & -0.408 & 0.342077 \tabularnewline
29 & -0.037068 & -0.3762 & 0.35377 \tabularnewline
30 & 0.087951 & 0.8926 & 0.187075 \tabularnewline
31 & 0.007119 & 0.0722 & 0.471273 \tabularnewline
32 & 0.000298 & 0.003 & 0.498798 \tabularnewline
33 & -0.107848 & -1.0945 & 0.138136 \tabularnewline
34 & 0.028568 & 0.2899 & 0.386226 \tabularnewline
35 & 0.080746 & 0.8195 & 0.2072 \tabularnewline
36 & -0.140119 & -1.4221 & 0.079015 \tabularnewline
37 & 0.033923 & 0.3443 & 0.365669 \tabularnewline
38 & 0.024441 & 0.248 & 0.402296 \tabularnewline
39 & 0.009016 & 0.0915 & 0.463637 \tabularnewline
40 & -0.049821 & -0.5056 & 0.307097 \tabularnewline
41 & 0.056208 & 0.5705 & 0.284807 \tabularnewline
42 & -0.068113 & -0.6913 & 0.245476 \tabularnewline
43 & -0.027313 & -0.2772 & 0.391092 \tabularnewline
44 & -0.114983 & -1.167 & 0.122962 \tabularnewline
45 & 0.074043 & 0.7515 & 0.227047 \tabularnewline
46 & 0.018698 & 0.1898 & 0.424933 \tabularnewline
47 & 0.016694 & 0.1694 & 0.432896 \tabularnewline
48 & 0.024009 & 0.2437 & 0.403989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114243&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]0.021071[/C][C]0.2138[/C][C]0.415546[/C][/ROW]
[ROW][C]2[/C][C]0.377749[/C][C]3.8337[/C][C]0.000109[/C][/ROW]
[ROW][C]3[/C][C]-0.153127[/C][C]-1.5541[/C][C]0.061618[/C][/ROW]
[ROW][C]4[/C][C]0.607673[/C][C]6.1672[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]-0.293268[/C][C]-2.9763[/C][C]0.001818[/C][/ROW]
[ROW][C]6[/C][C]-0.061355[/C][C]-0.6227[/C][C]0.267435[/C][/ROW]
[ROW][C]7[/C][C]0.012626[/C][C]0.1281[/C][C]0.449144[/C][/ROW]
[ROW][C]8[/C][C]0.129116[/C][C]1.3104[/C][C]0.09649[/C][/ROW]
[ROW][C]9[/C][C]-0.28932[/C][C]-2.9363[/C][C]0.002049[/C][/ROW]
[ROW][C]10[/C][C]0.066736[/C][C]0.6773[/C][C]0.249869[/C][/ROW]
[ROW][C]11[/C][C]-0.025034[/C][C]-0.2541[/C][C]0.399976[/C][/ROW]
[ROW][C]12[/C][C]0.113719[/C][C]1.1541[/C][C]0.12556[/C][/ROW]
[ROW][C]13[/C][C]0.022146[/C][C]0.2248[/C][C]0.411306[/C][/ROW]
[ROW][C]14[/C][C]-0.052414[/C][C]-0.5319[/C][C]0.297953[/C][/ROW]
[ROW][C]15[/C][C]0.036657[/C][C]0.372[/C][C]0.355318[/C][/ROW]
[ROW][C]16[/C][C]0.084868[/C][C]0.8613[/C][C]0.195532[/C][/ROW]
[ROW][C]17[/C][C]-0.073655[/C][C]-0.7475[/C][C]0.228228[/C][/ROW]
[ROW][C]18[/C][C]-0.004305[/C][C]-0.0437[/C][C]0.482618[/C][/ROW]
[ROW][C]19[/C][C]0.070251[/C][C]0.713[/C][C]0.238739[/C][/ROW]
[ROW][C]20[/C][C]0.061257[/C][C]0.6217[/C][C]0.26776[/C][/ROW]
[ROW][C]21[/C][C]-0.064947[/C][C]-0.6591[/C][C]0.255638[/C][/ROW]
[ROW][C]22[/C][C]-0.05059[/C][C]-0.5134[/C][C]0.304373[/C][/ROW]
[ROW][C]23[/C][C]0.014259[/C][C]0.1447[/C][C]0.442611[/C][/ROW]
[ROW][C]24[/C][C]-0.047906[/C][C]-0.4862[/C][C]0.313931[/C][/ROW]
[ROW][C]25[/C][C]0.019219[/C][C]0.1951[/C][C]0.422867[/C][/ROW]
[ROW][C]26[/C][C]-0.113685[/C][C]-1.1538[/C][C]0.125631[/C][/ROW]
[ROW][C]27[/C][C]0.051975[/C][C]0.5275[/C][C]0.299494[/C][/ROW]
[ROW][C]28[/C][C]-0.040197[/C][C]-0.408[/C][C]0.342077[/C][/ROW]
[ROW][C]29[/C][C]-0.037068[/C][C]-0.3762[/C][C]0.35377[/C][/ROW]
[ROW][C]30[/C][C]0.087951[/C][C]0.8926[/C][C]0.187075[/C][/ROW]
[ROW][C]31[/C][C]0.007119[/C][C]0.0722[/C][C]0.471273[/C][/ROW]
[ROW][C]32[/C][C]0.000298[/C][C]0.003[/C][C]0.498798[/C][/ROW]
[ROW][C]33[/C][C]-0.107848[/C][C]-1.0945[/C][C]0.138136[/C][/ROW]
[ROW][C]34[/C][C]0.028568[/C][C]0.2899[/C][C]0.386226[/C][/ROW]
[ROW][C]35[/C][C]0.080746[/C][C]0.8195[/C][C]0.2072[/C][/ROW]
[ROW][C]36[/C][C]-0.140119[/C][C]-1.4221[/C][C]0.079015[/C][/ROW]
[ROW][C]37[/C][C]0.033923[/C][C]0.3443[/C][C]0.365669[/C][/ROW]
[ROW][C]38[/C][C]0.024441[/C][C]0.248[/C][C]0.402296[/C][/ROW]
[ROW][C]39[/C][C]0.009016[/C][C]0.0915[/C][C]0.463637[/C][/ROW]
[ROW][C]40[/C][C]-0.049821[/C][C]-0.5056[/C][C]0.307097[/C][/ROW]
[ROW][C]41[/C][C]0.056208[/C][C]0.5705[/C][C]0.284807[/C][/ROW]
[ROW][C]42[/C][C]-0.068113[/C][C]-0.6913[/C][C]0.245476[/C][/ROW]
[ROW][C]43[/C][C]-0.027313[/C][C]-0.2772[/C][C]0.391092[/C][/ROW]
[ROW][C]44[/C][C]-0.114983[/C][C]-1.167[/C][C]0.122962[/C][/ROW]
[ROW][C]45[/C][C]0.074043[/C][C]0.7515[/C][C]0.227047[/C][/ROW]
[ROW][C]46[/C][C]0.018698[/C][C]0.1898[/C][C]0.424933[/C][/ROW]
[ROW][C]47[/C][C]0.016694[/C][C]0.1694[/C][C]0.432896[/C][/ROW]
[ROW][C]48[/C][C]0.024009[/C][C]0.2437[/C][C]0.403989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114243&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114243&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
10.0210710.21380.415546
20.3777493.83370.000109
3-0.153127-1.55410.061618
40.6076736.16720
5-0.293268-2.97630.001818
6-0.061355-0.62270.267435
70.0126260.12810.449144
80.1291161.31040.09649
9-0.28932-2.93630.002049
100.0667360.67730.249869
11-0.025034-0.25410.399976
120.1137191.15410.12556
130.0221460.22480.411306
14-0.052414-0.53190.297953
150.0366570.3720.355318
160.0848680.86130.195532
17-0.073655-0.74750.228228
18-0.004305-0.04370.482618
190.0702510.7130.238739
200.0612570.62170.26776
21-0.064947-0.65910.255638
22-0.05059-0.51340.304373
230.0142590.14470.442611
24-0.047906-0.48620.313931
250.0192190.19510.422867
26-0.113685-1.15380.125631
270.0519750.52750.299494
28-0.040197-0.4080.342077
29-0.037068-0.37620.35377
300.0879510.89260.187075
310.0071190.07220.471273
320.0002980.0030.498798
33-0.107848-1.09450.138136
340.0285680.28990.386226
350.0807460.81950.2072
36-0.140119-1.42210.079015
370.0339230.34430.365669
380.0244410.2480.402296
390.0090160.09150.463637
40-0.049821-0.50560.307097
410.0562080.57050.284807
42-0.068113-0.69130.245476
43-0.027313-0.27720.391092
44-0.114983-1.1670.122962
450.0740430.75150.227047
460.0186980.18980.424933
470.0166940.16940.432896
480.0240090.24370.403989



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 4 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 4 ; 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')