Free Statistics

of Irreproducible Research!

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 computationFri, 03 Dec 2010 09:48:24 +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/03/t1291369584k0qvjwgh90zx7q1.htm/, Retrieved Tue, 07 May 2024 12:11:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104576, Retrieved Tue, 07 May 2024 12:11:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158
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] [W9 autocorrelatie] [2010-12-03 08:22:12] [56d90b683fcd93137645f9226b43c62b]
-    D        [(Partial) Autocorrelation Function] [W9 d=1 D=1] [2010-12-03 09:48:24] [59f7d3e7fcb6374015f4e6b9053b0f01] [Current]
Feedback Forum

Post a new message
Dataseries X:
17848
19592
21092
20889
25890
24965
22225
20977
22897
22785
22769
19637
20203
20450
23083
21738
26766
25280
22574
22729
21378
22902
24989
21116
15169
15846
20927
18273
22538
15596
14034
11366
14861
15149
13577
13026
13190
13196
15826
14733
16307
15703
14589
12043
15057
14053
12698
10888
10045
11549
13767
12424
13116
14211
12266
12602
15714
13742
12745
10491
10057
10900
11771
11992
11993
14504
11727
11477
13578
11555
11846
11397
10066
10269
14279
13870
13695
14420
11424
9704
12464
14301
13464
9893
11572
12380
16692
16052
16459
14761
13654
13480
18068
16560
14530
10650
11651
13735
13360
17818
20613
16231
13862
12004
17734
15034
12609
12320
10833
11350
13648
14890
16325
18045
15616
11926
16855
15083
12520
12355




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104576&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104576&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104576&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'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.212943-2.20270.01488
2-0.26093-2.69910.004041
30.0039490.04080.483747
40.0645230.66740.252968
50.070250.72670.234506
6-0.014961-0.15480.438653
70.0356740.3690.356421
8-0.162582-1.68180.047765
90.0446660.4620.3225
100.1046761.08280.140671
110.0526450.54460.293593
12-0.321073-3.32120.000613
130.0180190.18640.426246
140.1896191.96140.026213
15-0.068069-0.70410.241447
160.0699790.72390.235364
17-0.111047-1.14870.126624
180.0470940.48710.313575
190.0440910.45610.32463
20-0.037725-0.39020.34857
21-0.001708-0.01770.492969
220.002410.02490.490081
230.0727570.75260.226672
24-0.145857-1.50880.067154
250.0342440.35420.361933
260.0127050.13140.447846
27-0.047649-0.49290.311553
280.0073380.07590.469816
290.0844650.87370.192115
30-0.037029-0.3830.351229
31-0.0969-1.00230.15922
320.0606050.62690.26603
330.0780110.80690.210743
34-0.058469-0.60480.273293
350.038460.39780.345771
36-0.042893-0.44370.329082
370.0082460.08530.466093
38-0.029802-0.30830.379237
390.1304261.34910.090071
40-0.064779-0.67010.252124
41-0.074655-0.77220.220837
420.0157480.16290.435451
43-0.018385-0.19020.424766
440.0773710.80030.212645
45-0.002401-0.02480.490115
46-0.008728-0.09030.464117
47-0.117291-1.21330.11385
480.0386560.39990.345029

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.212943 & -2.2027 & 0.01488 \tabularnewline
2 & -0.26093 & -2.6991 & 0.004041 \tabularnewline
3 & 0.003949 & 0.0408 & 0.483747 \tabularnewline
4 & 0.064523 & 0.6674 & 0.252968 \tabularnewline
5 & 0.07025 & 0.7267 & 0.234506 \tabularnewline
6 & -0.014961 & -0.1548 & 0.438653 \tabularnewline
7 & 0.035674 & 0.369 & 0.356421 \tabularnewline
8 & -0.162582 & -1.6818 & 0.047765 \tabularnewline
9 & 0.044666 & 0.462 & 0.3225 \tabularnewline
10 & 0.104676 & 1.0828 & 0.140671 \tabularnewline
11 & 0.052645 & 0.5446 & 0.293593 \tabularnewline
12 & -0.321073 & -3.3212 & 0.000613 \tabularnewline
13 & 0.018019 & 0.1864 & 0.426246 \tabularnewline
14 & 0.189619 & 1.9614 & 0.026213 \tabularnewline
15 & -0.068069 & -0.7041 & 0.241447 \tabularnewline
16 & 0.069979 & 0.7239 & 0.235364 \tabularnewline
17 & -0.111047 & -1.1487 & 0.126624 \tabularnewline
18 & 0.047094 & 0.4871 & 0.313575 \tabularnewline
19 & 0.044091 & 0.4561 & 0.32463 \tabularnewline
20 & -0.037725 & -0.3902 & 0.34857 \tabularnewline
21 & -0.001708 & -0.0177 & 0.492969 \tabularnewline
22 & 0.00241 & 0.0249 & 0.490081 \tabularnewline
23 & 0.072757 & 0.7526 & 0.226672 \tabularnewline
24 & -0.145857 & -1.5088 & 0.067154 \tabularnewline
25 & 0.034244 & 0.3542 & 0.361933 \tabularnewline
26 & 0.012705 & 0.1314 & 0.447846 \tabularnewline
27 & -0.047649 & -0.4929 & 0.311553 \tabularnewline
28 & 0.007338 & 0.0759 & 0.469816 \tabularnewline
29 & 0.084465 & 0.8737 & 0.192115 \tabularnewline
30 & -0.037029 & -0.383 & 0.351229 \tabularnewline
31 & -0.0969 & -1.0023 & 0.15922 \tabularnewline
32 & 0.060605 & 0.6269 & 0.26603 \tabularnewline
33 & 0.078011 & 0.8069 & 0.210743 \tabularnewline
34 & -0.058469 & -0.6048 & 0.273293 \tabularnewline
35 & 0.03846 & 0.3978 & 0.345771 \tabularnewline
36 & -0.042893 & -0.4437 & 0.329082 \tabularnewline
37 & 0.008246 & 0.0853 & 0.466093 \tabularnewline
38 & -0.029802 & -0.3083 & 0.379237 \tabularnewline
39 & 0.130426 & 1.3491 & 0.090071 \tabularnewline
40 & -0.064779 & -0.6701 & 0.252124 \tabularnewline
41 & -0.074655 & -0.7722 & 0.220837 \tabularnewline
42 & 0.015748 & 0.1629 & 0.435451 \tabularnewline
43 & -0.018385 & -0.1902 & 0.424766 \tabularnewline
44 & 0.077371 & 0.8003 & 0.212645 \tabularnewline
45 & -0.002401 & -0.0248 & 0.490115 \tabularnewline
46 & -0.008728 & -0.0903 & 0.464117 \tabularnewline
47 & -0.117291 & -1.2133 & 0.11385 \tabularnewline
48 & 0.038656 & 0.3999 & 0.345029 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104576&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]-0.212943[/C][C]-2.2027[/C][C]0.01488[/C][/ROW]
[ROW][C]2[/C][C]-0.26093[/C][C]-2.6991[/C][C]0.004041[/C][/ROW]
[ROW][C]3[/C][C]0.003949[/C][C]0.0408[/C][C]0.483747[/C][/ROW]
[ROW][C]4[/C][C]0.064523[/C][C]0.6674[/C][C]0.252968[/C][/ROW]
[ROW][C]5[/C][C]0.07025[/C][C]0.7267[/C][C]0.234506[/C][/ROW]
[ROW][C]6[/C][C]-0.014961[/C][C]-0.1548[/C][C]0.438653[/C][/ROW]
[ROW][C]7[/C][C]0.035674[/C][C]0.369[/C][C]0.356421[/C][/ROW]
[ROW][C]8[/C][C]-0.162582[/C][C]-1.6818[/C][C]0.047765[/C][/ROW]
[ROW][C]9[/C][C]0.044666[/C][C]0.462[/C][C]0.3225[/C][/ROW]
[ROW][C]10[/C][C]0.104676[/C][C]1.0828[/C][C]0.140671[/C][/ROW]
[ROW][C]11[/C][C]0.052645[/C][C]0.5446[/C][C]0.293593[/C][/ROW]
[ROW][C]12[/C][C]-0.321073[/C][C]-3.3212[/C][C]0.000613[/C][/ROW]
[ROW][C]13[/C][C]0.018019[/C][C]0.1864[/C][C]0.426246[/C][/ROW]
[ROW][C]14[/C][C]0.189619[/C][C]1.9614[/C][C]0.026213[/C][/ROW]
[ROW][C]15[/C][C]-0.068069[/C][C]-0.7041[/C][C]0.241447[/C][/ROW]
[ROW][C]16[/C][C]0.069979[/C][C]0.7239[/C][C]0.235364[/C][/ROW]
[ROW][C]17[/C][C]-0.111047[/C][C]-1.1487[/C][C]0.126624[/C][/ROW]
[ROW][C]18[/C][C]0.047094[/C][C]0.4871[/C][C]0.313575[/C][/ROW]
[ROW][C]19[/C][C]0.044091[/C][C]0.4561[/C][C]0.32463[/C][/ROW]
[ROW][C]20[/C][C]-0.037725[/C][C]-0.3902[/C][C]0.34857[/C][/ROW]
[ROW][C]21[/C][C]-0.001708[/C][C]-0.0177[/C][C]0.492969[/C][/ROW]
[ROW][C]22[/C][C]0.00241[/C][C]0.0249[/C][C]0.490081[/C][/ROW]
[ROW][C]23[/C][C]0.072757[/C][C]0.7526[/C][C]0.226672[/C][/ROW]
[ROW][C]24[/C][C]-0.145857[/C][C]-1.5088[/C][C]0.067154[/C][/ROW]
[ROW][C]25[/C][C]0.034244[/C][C]0.3542[/C][C]0.361933[/C][/ROW]
[ROW][C]26[/C][C]0.012705[/C][C]0.1314[/C][C]0.447846[/C][/ROW]
[ROW][C]27[/C][C]-0.047649[/C][C]-0.4929[/C][C]0.311553[/C][/ROW]
[ROW][C]28[/C][C]0.007338[/C][C]0.0759[/C][C]0.469816[/C][/ROW]
[ROW][C]29[/C][C]0.084465[/C][C]0.8737[/C][C]0.192115[/C][/ROW]
[ROW][C]30[/C][C]-0.037029[/C][C]-0.383[/C][C]0.351229[/C][/ROW]
[ROW][C]31[/C][C]-0.0969[/C][C]-1.0023[/C][C]0.15922[/C][/ROW]
[ROW][C]32[/C][C]0.060605[/C][C]0.6269[/C][C]0.26603[/C][/ROW]
[ROW][C]33[/C][C]0.078011[/C][C]0.8069[/C][C]0.210743[/C][/ROW]
[ROW][C]34[/C][C]-0.058469[/C][C]-0.6048[/C][C]0.273293[/C][/ROW]
[ROW][C]35[/C][C]0.03846[/C][C]0.3978[/C][C]0.345771[/C][/ROW]
[ROW][C]36[/C][C]-0.042893[/C][C]-0.4437[/C][C]0.329082[/C][/ROW]
[ROW][C]37[/C][C]0.008246[/C][C]0.0853[/C][C]0.466093[/C][/ROW]
[ROW][C]38[/C][C]-0.029802[/C][C]-0.3083[/C][C]0.379237[/C][/ROW]
[ROW][C]39[/C][C]0.130426[/C][C]1.3491[/C][C]0.090071[/C][/ROW]
[ROW][C]40[/C][C]-0.064779[/C][C]-0.6701[/C][C]0.252124[/C][/ROW]
[ROW][C]41[/C][C]-0.074655[/C][C]-0.7722[/C][C]0.220837[/C][/ROW]
[ROW][C]42[/C][C]0.015748[/C][C]0.1629[/C][C]0.435451[/C][/ROW]
[ROW][C]43[/C][C]-0.018385[/C][C]-0.1902[/C][C]0.424766[/C][/ROW]
[ROW][C]44[/C][C]0.077371[/C][C]0.8003[/C][C]0.212645[/C][/ROW]
[ROW][C]45[/C][C]-0.002401[/C][C]-0.0248[/C][C]0.490115[/C][/ROW]
[ROW][C]46[/C][C]-0.008728[/C][C]-0.0903[/C][C]0.464117[/C][/ROW]
[ROW][C]47[/C][C]-0.117291[/C][C]-1.2133[/C][C]0.11385[/C][/ROW]
[ROW][C]48[/C][C]0.038656[/C][C]0.3999[/C][C]0.345029[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104576&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104576&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
1-0.212943-2.20270.01488
2-0.26093-2.69910.004041
30.0039490.04080.483747
40.0645230.66740.252968
50.070250.72670.234506
6-0.014961-0.15480.438653
70.0356740.3690.356421
8-0.162582-1.68180.047765
90.0446660.4620.3225
100.1046761.08280.140671
110.0526450.54460.293593
12-0.321073-3.32120.000613
130.0180190.18640.426246
140.1896191.96140.026213
15-0.068069-0.70410.241447
160.0699790.72390.235364
17-0.111047-1.14870.126624
180.0470940.48710.313575
190.0440910.45610.32463
20-0.037725-0.39020.34857
21-0.001708-0.01770.492969
220.002410.02490.490081
230.0727570.75260.226672
24-0.145857-1.50880.067154
250.0342440.35420.361933
260.0127050.13140.447846
27-0.047649-0.49290.311553
280.0073380.07590.469816
290.0844650.87370.192115
30-0.037029-0.3830.351229
31-0.0969-1.00230.15922
320.0606050.62690.26603
330.0780110.80690.210743
34-0.058469-0.60480.273293
350.038460.39780.345771
36-0.042893-0.44370.329082
370.0082460.08530.466093
38-0.029802-0.30830.379237
390.1304261.34910.090071
40-0.064779-0.67010.252124
41-0.074655-0.77220.220837
420.0157480.16290.435451
43-0.018385-0.19020.424766
440.0773710.80030.212645
45-0.002401-0.02480.490115
46-0.008728-0.09030.464117
47-0.117291-1.21330.11385
480.0386560.39990.345029







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.212943-2.20270.01488
2-0.320823-3.31860.000619
3-0.160857-1.66390.049527
4-0.076638-0.79270.21484
50.0351260.36330.358532
60.0307070.31760.375689
70.1052141.08830.139444
8-0.125766-1.30090.098038
9-0.012984-0.13430.446705
100.0247410.25590.39925
110.1014661.04960.14814
12-0.28609-2.95930.001898
13-0.112011-1.15870.124589
14-0.015204-0.15730.437663
15-0.072463-0.74960.227581
160.0950130.98280.163957
17-0.04024-0.41630.33903
180.0839690.86860.193509
190.0905360.93650.17556
20-0.076034-0.78650.216656
21-0.037101-0.38380.350952
220.0299270.30960.378747
230.0880040.91030.18235
24-0.221301-2.28920.012017
25-0.095531-0.98820.162648
26-0.020922-0.21640.414539
27-0.102308-1.05830.146154
28-0.005916-0.06120.475658
290.0714870.73950.230623
300.0394580.40820.341985
310.0426740.44140.329899
32-0.081793-0.84610.1997
330.0607940.62890.26539
34-0.009812-0.10150.459673
350.1252231.29530.098999
36-0.181968-1.88230.031257
37-0.054238-0.5610.287971
38-0.058563-0.60580.27297
390.0636630.65850.255806
40-0.022688-0.23470.407451
410.0479030.49550.310628
42-0.01225-0.12670.4497
43-0.03766-0.38960.348819
44-0.03435-0.35530.361524
450.0863660.89340.186829
460.0458240.4740.318231
47-0.025563-0.26440.395982
48-0.168502-1.7430.042103

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.212943 & -2.2027 & 0.01488 \tabularnewline
2 & -0.320823 & -3.3186 & 0.000619 \tabularnewline
3 & -0.160857 & -1.6639 & 0.049527 \tabularnewline
4 & -0.076638 & -0.7927 & 0.21484 \tabularnewline
5 & 0.035126 & 0.3633 & 0.358532 \tabularnewline
6 & 0.030707 & 0.3176 & 0.375689 \tabularnewline
7 & 0.105214 & 1.0883 & 0.139444 \tabularnewline
8 & -0.125766 & -1.3009 & 0.098038 \tabularnewline
9 & -0.012984 & -0.1343 & 0.446705 \tabularnewline
10 & 0.024741 & 0.2559 & 0.39925 \tabularnewline
11 & 0.101466 & 1.0496 & 0.14814 \tabularnewline
12 & -0.28609 & -2.9593 & 0.001898 \tabularnewline
13 & -0.112011 & -1.1587 & 0.124589 \tabularnewline
14 & -0.015204 & -0.1573 & 0.437663 \tabularnewline
15 & -0.072463 & -0.7496 & 0.227581 \tabularnewline
16 & 0.095013 & 0.9828 & 0.163957 \tabularnewline
17 & -0.04024 & -0.4163 & 0.33903 \tabularnewline
18 & 0.083969 & 0.8686 & 0.193509 \tabularnewline
19 & 0.090536 & 0.9365 & 0.17556 \tabularnewline
20 & -0.076034 & -0.7865 & 0.216656 \tabularnewline
21 & -0.037101 & -0.3838 & 0.350952 \tabularnewline
22 & 0.029927 & 0.3096 & 0.378747 \tabularnewline
23 & 0.088004 & 0.9103 & 0.18235 \tabularnewline
24 & -0.221301 & -2.2892 & 0.012017 \tabularnewline
25 & -0.095531 & -0.9882 & 0.162648 \tabularnewline
26 & -0.020922 & -0.2164 & 0.414539 \tabularnewline
27 & -0.102308 & -1.0583 & 0.146154 \tabularnewline
28 & -0.005916 & -0.0612 & 0.475658 \tabularnewline
29 & 0.071487 & 0.7395 & 0.230623 \tabularnewline
30 & 0.039458 & 0.4082 & 0.341985 \tabularnewline
31 & 0.042674 & 0.4414 & 0.329899 \tabularnewline
32 & -0.081793 & -0.8461 & 0.1997 \tabularnewline
33 & 0.060794 & 0.6289 & 0.26539 \tabularnewline
34 & -0.009812 & -0.1015 & 0.459673 \tabularnewline
35 & 0.125223 & 1.2953 & 0.098999 \tabularnewline
36 & -0.181968 & -1.8823 & 0.031257 \tabularnewline
37 & -0.054238 & -0.561 & 0.287971 \tabularnewline
38 & -0.058563 & -0.6058 & 0.27297 \tabularnewline
39 & 0.063663 & 0.6585 & 0.255806 \tabularnewline
40 & -0.022688 & -0.2347 & 0.407451 \tabularnewline
41 & 0.047903 & 0.4955 & 0.310628 \tabularnewline
42 & -0.01225 & -0.1267 & 0.4497 \tabularnewline
43 & -0.03766 & -0.3896 & 0.348819 \tabularnewline
44 & -0.03435 & -0.3553 & 0.361524 \tabularnewline
45 & 0.086366 & 0.8934 & 0.186829 \tabularnewline
46 & 0.045824 & 0.474 & 0.318231 \tabularnewline
47 & -0.025563 & -0.2644 & 0.395982 \tabularnewline
48 & -0.168502 & -1.743 & 0.042103 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104576&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]-0.212943[/C][C]-2.2027[/C][C]0.01488[/C][/ROW]
[ROW][C]2[/C][C]-0.320823[/C][C]-3.3186[/C][C]0.000619[/C][/ROW]
[ROW][C]3[/C][C]-0.160857[/C][C]-1.6639[/C][C]0.049527[/C][/ROW]
[ROW][C]4[/C][C]-0.076638[/C][C]-0.7927[/C][C]0.21484[/C][/ROW]
[ROW][C]5[/C][C]0.035126[/C][C]0.3633[/C][C]0.358532[/C][/ROW]
[ROW][C]6[/C][C]0.030707[/C][C]0.3176[/C][C]0.375689[/C][/ROW]
[ROW][C]7[/C][C]0.105214[/C][C]1.0883[/C][C]0.139444[/C][/ROW]
[ROW][C]8[/C][C]-0.125766[/C][C]-1.3009[/C][C]0.098038[/C][/ROW]
[ROW][C]9[/C][C]-0.012984[/C][C]-0.1343[/C][C]0.446705[/C][/ROW]
[ROW][C]10[/C][C]0.024741[/C][C]0.2559[/C][C]0.39925[/C][/ROW]
[ROW][C]11[/C][C]0.101466[/C][C]1.0496[/C][C]0.14814[/C][/ROW]
[ROW][C]12[/C][C]-0.28609[/C][C]-2.9593[/C][C]0.001898[/C][/ROW]
[ROW][C]13[/C][C]-0.112011[/C][C]-1.1587[/C][C]0.124589[/C][/ROW]
[ROW][C]14[/C][C]-0.015204[/C][C]-0.1573[/C][C]0.437663[/C][/ROW]
[ROW][C]15[/C][C]-0.072463[/C][C]-0.7496[/C][C]0.227581[/C][/ROW]
[ROW][C]16[/C][C]0.095013[/C][C]0.9828[/C][C]0.163957[/C][/ROW]
[ROW][C]17[/C][C]-0.04024[/C][C]-0.4163[/C][C]0.33903[/C][/ROW]
[ROW][C]18[/C][C]0.083969[/C][C]0.8686[/C][C]0.193509[/C][/ROW]
[ROW][C]19[/C][C]0.090536[/C][C]0.9365[/C][C]0.17556[/C][/ROW]
[ROW][C]20[/C][C]-0.076034[/C][C]-0.7865[/C][C]0.216656[/C][/ROW]
[ROW][C]21[/C][C]-0.037101[/C][C]-0.3838[/C][C]0.350952[/C][/ROW]
[ROW][C]22[/C][C]0.029927[/C][C]0.3096[/C][C]0.378747[/C][/ROW]
[ROW][C]23[/C][C]0.088004[/C][C]0.9103[/C][C]0.18235[/C][/ROW]
[ROW][C]24[/C][C]-0.221301[/C][C]-2.2892[/C][C]0.012017[/C][/ROW]
[ROW][C]25[/C][C]-0.095531[/C][C]-0.9882[/C][C]0.162648[/C][/ROW]
[ROW][C]26[/C][C]-0.020922[/C][C]-0.2164[/C][C]0.414539[/C][/ROW]
[ROW][C]27[/C][C]-0.102308[/C][C]-1.0583[/C][C]0.146154[/C][/ROW]
[ROW][C]28[/C][C]-0.005916[/C][C]-0.0612[/C][C]0.475658[/C][/ROW]
[ROW][C]29[/C][C]0.071487[/C][C]0.7395[/C][C]0.230623[/C][/ROW]
[ROW][C]30[/C][C]0.039458[/C][C]0.4082[/C][C]0.341985[/C][/ROW]
[ROW][C]31[/C][C]0.042674[/C][C]0.4414[/C][C]0.329899[/C][/ROW]
[ROW][C]32[/C][C]-0.081793[/C][C]-0.8461[/C][C]0.1997[/C][/ROW]
[ROW][C]33[/C][C]0.060794[/C][C]0.6289[/C][C]0.26539[/C][/ROW]
[ROW][C]34[/C][C]-0.009812[/C][C]-0.1015[/C][C]0.459673[/C][/ROW]
[ROW][C]35[/C][C]0.125223[/C][C]1.2953[/C][C]0.098999[/C][/ROW]
[ROW][C]36[/C][C]-0.181968[/C][C]-1.8823[/C][C]0.031257[/C][/ROW]
[ROW][C]37[/C][C]-0.054238[/C][C]-0.561[/C][C]0.287971[/C][/ROW]
[ROW][C]38[/C][C]-0.058563[/C][C]-0.6058[/C][C]0.27297[/C][/ROW]
[ROW][C]39[/C][C]0.063663[/C][C]0.6585[/C][C]0.255806[/C][/ROW]
[ROW][C]40[/C][C]-0.022688[/C][C]-0.2347[/C][C]0.407451[/C][/ROW]
[ROW][C]41[/C][C]0.047903[/C][C]0.4955[/C][C]0.310628[/C][/ROW]
[ROW][C]42[/C][C]-0.01225[/C][C]-0.1267[/C][C]0.4497[/C][/ROW]
[ROW][C]43[/C][C]-0.03766[/C][C]-0.3896[/C][C]0.348819[/C][/ROW]
[ROW][C]44[/C][C]-0.03435[/C][C]-0.3553[/C][C]0.361524[/C][/ROW]
[ROW][C]45[/C][C]0.086366[/C][C]0.8934[/C][C]0.186829[/C][/ROW]
[ROW][C]46[/C][C]0.045824[/C][C]0.474[/C][C]0.318231[/C][/ROW]
[ROW][C]47[/C][C]-0.025563[/C][C]-0.2644[/C][C]0.395982[/C][/ROW]
[ROW][C]48[/C][C]-0.168502[/C][C]-1.743[/C][C]0.042103[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104576&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104576&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
1-0.212943-2.20270.01488
2-0.320823-3.31860.000619
3-0.160857-1.66390.049527
4-0.076638-0.79270.21484
50.0351260.36330.358532
60.0307070.31760.375689
70.1052141.08830.139444
8-0.125766-1.30090.098038
9-0.012984-0.13430.446705
100.0247410.25590.39925
110.1014661.04960.14814
12-0.28609-2.95930.001898
13-0.112011-1.15870.124589
14-0.015204-0.15730.437663
15-0.072463-0.74960.227581
160.0950130.98280.163957
17-0.04024-0.41630.33903
180.0839690.86860.193509
190.0905360.93650.17556
20-0.076034-0.78650.216656
21-0.037101-0.38380.350952
220.0299270.30960.378747
230.0880040.91030.18235
24-0.221301-2.28920.012017
25-0.095531-0.98820.162648
26-0.020922-0.21640.414539
27-0.102308-1.05830.146154
28-0.005916-0.06120.475658
290.0714870.73950.230623
300.0394580.40820.341985
310.0426740.44140.329899
32-0.081793-0.84610.1997
330.0607940.62890.26539
34-0.009812-0.10150.459673
350.1252231.29530.098999
36-0.181968-1.88230.031257
37-0.054238-0.5610.287971
38-0.058563-0.60580.27297
390.0636630.65850.255806
40-0.022688-0.23470.407451
410.0479030.49550.310628
42-0.01225-0.12670.4497
43-0.03766-0.38960.348819
44-0.03435-0.35530.361524
450.0863660.89340.186829
460.0458240.4740.318231
47-0.025563-0.26440.395982
48-0.168502-1.7430.042103



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