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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 06 Jan 2010 02:56:35 -0700
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/Jan/06/t1262771950f69so48dns8cwke.htm/, Retrieved Sat, 04 May 2024 08:04:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71640, Retrieved Sat, 04 May 2024 08:04:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [] [2009-10-27 11:47:31] [e5e09c53da17fb7444fa9ceb236a5291]
- RMP   [Mean Plot] [] [2009-12-02 08:56:02] [e5e09c53da17fb7444fa9ceb236a5291]
- RMP     [(Partial) Autocorrelation Function] [] [2009-12-13 10:12:58] [e5e09c53da17fb7444fa9ceb236a5291]
-   PD        [(Partial) Autocorrelation Function] [] [2010-01-06 09:56:35] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
2.14
2.45
2.52
2.3
2.25
2.06
1.99
2.25
2.26
2.36
2.3
2.19
2.31
2.21
2.21
2.26
2.18
2.21
2.33
2.12
2.08
1.97
2.09
2.11
2.24
2.45
2.68
2.73
2.76
2.83
3.16
3.22
3.22
3.34
3.35
3.42
3.58
3.71
3.68
3.83
3.94
3.88
4.03
4.15
4.32
4.4
4.37
4.14
4.11
4.16
3.98
4.13
3.76
3.66
3.85
4.03
4.31
4.58
4.46
4.41
3.84
2.84
2.66
2.17
1.43
1.47
1.29
1.23
1.09
0.94
0.76
0.67




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=71640&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=71640&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71640&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
10.9406287.98150
20.8664627.35220
30.7833856.64720
40.685745.81870
50.5923095.02592e-06
60.4967464.2153.6e-05
70.4017273.40880.000536
80.3100732.63110.005202
90.2347231.99170.025099
100.1707831.44910.07582
110.1110480.94230.174601
120.0724140.61450.270427
130.0487970.41410.340031
140.0238770.20260.420008
15-0.003274-0.02780.488957
16-0.038-0.32240.374027
17-0.08226-0.6980.243713
18-0.131536-1.11610.134041
19-0.184997-1.56980.060428
20-0.234871-1.99290.025029
21-0.270949-2.29910.012202
22-0.308872-2.62090.005346
23-0.335181-2.84410.002897
24-0.361063-3.06370.001537
25-0.380325-3.22720.000941
26-0.386201-3.2770.000808
27-0.386212-3.27710.000808
28-0.383685-3.25570.000863
29-0.382019-3.24150.000901
30-0.383132-3.2510.000875
31-0.3815-3.23710.000913
32-0.372664-3.16220.001146
33-0.364961-3.09680.001394
34-0.356901-3.02840.001706
35-0.340278-2.88740.002563
36-0.320202-2.7170.004123
37-0.29746-2.5240.006904
38-0.27005-2.29140.012433
39-0.236524-2.0070.024254
40-0.201372-1.70870.045907
41-0.161556-1.37080.08734
42-0.124062-1.05270.147999
43-0.097309-0.82570.205852
44-0.070012-0.59410.277162
45-0.04301-0.36490.358109
46-0.016693-0.14160.443878
470.007080.06010.47613
480.0189610.16090.436315
490.0248860.21120.416679
500.030560.25930.398068
510.0275150.23350.408027
520.0321020.27240.393048
530.0377390.32020.374861
540.0489580.41540.339535
550.061310.52020.30225
560.0717380.60870.272314
570.084580.71770.237636
580.0984090.8350.203232
590.1066450.90490.184265
600.1184921.00540.159027

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.940628 & 7.9815 & 0 \tabularnewline
2 & 0.866462 & 7.3522 & 0 \tabularnewline
3 & 0.783385 & 6.6472 & 0 \tabularnewline
4 & 0.68574 & 5.8187 & 0 \tabularnewline
5 & 0.592309 & 5.0259 & 2e-06 \tabularnewline
6 & 0.496746 & 4.215 & 3.6e-05 \tabularnewline
7 & 0.401727 & 3.4088 & 0.000536 \tabularnewline
8 & 0.310073 & 2.6311 & 0.005202 \tabularnewline
9 & 0.234723 & 1.9917 & 0.025099 \tabularnewline
10 & 0.170783 & 1.4491 & 0.07582 \tabularnewline
11 & 0.111048 & 0.9423 & 0.174601 \tabularnewline
12 & 0.072414 & 0.6145 & 0.270427 \tabularnewline
13 & 0.048797 & 0.4141 & 0.340031 \tabularnewline
14 & 0.023877 & 0.2026 & 0.420008 \tabularnewline
15 & -0.003274 & -0.0278 & 0.488957 \tabularnewline
16 & -0.038 & -0.3224 & 0.374027 \tabularnewline
17 & -0.08226 & -0.698 & 0.243713 \tabularnewline
18 & -0.131536 & -1.1161 & 0.134041 \tabularnewline
19 & -0.184997 & -1.5698 & 0.060428 \tabularnewline
20 & -0.234871 & -1.9929 & 0.025029 \tabularnewline
21 & -0.270949 & -2.2991 & 0.012202 \tabularnewline
22 & -0.308872 & -2.6209 & 0.005346 \tabularnewline
23 & -0.335181 & -2.8441 & 0.002897 \tabularnewline
24 & -0.361063 & -3.0637 & 0.001537 \tabularnewline
25 & -0.380325 & -3.2272 & 0.000941 \tabularnewline
26 & -0.386201 & -3.277 & 0.000808 \tabularnewline
27 & -0.386212 & -3.2771 & 0.000808 \tabularnewline
28 & -0.383685 & -3.2557 & 0.000863 \tabularnewline
29 & -0.382019 & -3.2415 & 0.000901 \tabularnewline
30 & -0.383132 & -3.251 & 0.000875 \tabularnewline
31 & -0.3815 & -3.2371 & 0.000913 \tabularnewline
32 & -0.372664 & -3.1622 & 0.001146 \tabularnewline
33 & -0.364961 & -3.0968 & 0.001394 \tabularnewline
34 & -0.356901 & -3.0284 & 0.001706 \tabularnewline
35 & -0.340278 & -2.8874 & 0.002563 \tabularnewline
36 & -0.320202 & -2.717 & 0.004123 \tabularnewline
37 & -0.29746 & -2.524 & 0.006904 \tabularnewline
38 & -0.27005 & -2.2914 & 0.012433 \tabularnewline
39 & -0.236524 & -2.007 & 0.024254 \tabularnewline
40 & -0.201372 & -1.7087 & 0.045907 \tabularnewline
41 & -0.161556 & -1.3708 & 0.08734 \tabularnewline
42 & -0.124062 & -1.0527 & 0.147999 \tabularnewline
43 & -0.097309 & -0.8257 & 0.205852 \tabularnewline
44 & -0.070012 & -0.5941 & 0.277162 \tabularnewline
45 & -0.04301 & -0.3649 & 0.358109 \tabularnewline
46 & -0.016693 & -0.1416 & 0.443878 \tabularnewline
47 & 0.00708 & 0.0601 & 0.47613 \tabularnewline
48 & 0.018961 & 0.1609 & 0.436315 \tabularnewline
49 & 0.024886 & 0.2112 & 0.416679 \tabularnewline
50 & 0.03056 & 0.2593 & 0.398068 \tabularnewline
51 & 0.027515 & 0.2335 & 0.408027 \tabularnewline
52 & 0.032102 & 0.2724 & 0.393048 \tabularnewline
53 & 0.037739 & 0.3202 & 0.374861 \tabularnewline
54 & 0.048958 & 0.4154 & 0.339535 \tabularnewline
55 & 0.06131 & 0.5202 & 0.30225 \tabularnewline
56 & 0.071738 & 0.6087 & 0.272314 \tabularnewline
57 & 0.08458 & 0.7177 & 0.237636 \tabularnewline
58 & 0.098409 & 0.835 & 0.203232 \tabularnewline
59 & 0.106645 & 0.9049 & 0.184265 \tabularnewline
60 & 0.118492 & 1.0054 & 0.159027 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71640&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]0.940628[/C][C]7.9815[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.866462[/C][C]7.3522[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.783385[/C][C]6.6472[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.68574[/C][C]5.8187[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.592309[/C][C]5.0259[/C][C]2e-06[/C][/ROW]
[ROW][C]6[/C][C]0.496746[/C][C]4.215[/C][C]3.6e-05[/C][/ROW]
[ROW][C]7[/C][C]0.401727[/C][C]3.4088[/C][C]0.000536[/C][/ROW]
[ROW][C]8[/C][C]0.310073[/C][C]2.6311[/C][C]0.005202[/C][/ROW]
[ROW][C]9[/C][C]0.234723[/C][C]1.9917[/C][C]0.025099[/C][/ROW]
[ROW][C]10[/C][C]0.170783[/C][C]1.4491[/C][C]0.07582[/C][/ROW]
[ROW][C]11[/C][C]0.111048[/C][C]0.9423[/C][C]0.174601[/C][/ROW]
[ROW][C]12[/C][C]0.072414[/C][C]0.6145[/C][C]0.270427[/C][/ROW]
[ROW][C]13[/C][C]0.048797[/C][C]0.4141[/C][C]0.340031[/C][/ROW]
[ROW][C]14[/C][C]0.023877[/C][C]0.2026[/C][C]0.420008[/C][/ROW]
[ROW][C]15[/C][C]-0.003274[/C][C]-0.0278[/C][C]0.488957[/C][/ROW]
[ROW][C]16[/C][C]-0.038[/C][C]-0.3224[/C][C]0.374027[/C][/ROW]
[ROW][C]17[/C][C]-0.08226[/C][C]-0.698[/C][C]0.243713[/C][/ROW]
[ROW][C]18[/C][C]-0.131536[/C][C]-1.1161[/C][C]0.134041[/C][/ROW]
[ROW][C]19[/C][C]-0.184997[/C][C]-1.5698[/C][C]0.060428[/C][/ROW]
[ROW][C]20[/C][C]-0.234871[/C][C]-1.9929[/C][C]0.025029[/C][/ROW]
[ROW][C]21[/C][C]-0.270949[/C][C]-2.2991[/C][C]0.012202[/C][/ROW]
[ROW][C]22[/C][C]-0.308872[/C][C]-2.6209[/C][C]0.005346[/C][/ROW]
[ROW][C]23[/C][C]-0.335181[/C][C]-2.8441[/C][C]0.002897[/C][/ROW]
[ROW][C]24[/C][C]-0.361063[/C][C]-3.0637[/C][C]0.001537[/C][/ROW]
[ROW][C]25[/C][C]-0.380325[/C][C]-3.2272[/C][C]0.000941[/C][/ROW]
[ROW][C]26[/C][C]-0.386201[/C][C]-3.277[/C][C]0.000808[/C][/ROW]
[ROW][C]27[/C][C]-0.386212[/C][C]-3.2771[/C][C]0.000808[/C][/ROW]
[ROW][C]28[/C][C]-0.383685[/C][C]-3.2557[/C][C]0.000863[/C][/ROW]
[ROW][C]29[/C][C]-0.382019[/C][C]-3.2415[/C][C]0.000901[/C][/ROW]
[ROW][C]30[/C][C]-0.383132[/C][C]-3.251[/C][C]0.000875[/C][/ROW]
[ROW][C]31[/C][C]-0.3815[/C][C]-3.2371[/C][C]0.000913[/C][/ROW]
[ROW][C]32[/C][C]-0.372664[/C][C]-3.1622[/C][C]0.001146[/C][/ROW]
[ROW][C]33[/C][C]-0.364961[/C][C]-3.0968[/C][C]0.001394[/C][/ROW]
[ROW][C]34[/C][C]-0.356901[/C][C]-3.0284[/C][C]0.001706[/C][/ROW]
[ROW][C]35[/C][C]-0.340278[/C][C]-2.8874[/C][C]0.002563[/C][/ROW]
[ROW][C]36[/C][C]-0.320202[/C][C]-2.717[/C][C]0.004123[/C][/ROW]
[ROW][C]37[/C][C]-0.29746[/C][C]-2.524[/C][C]0.006904[/C][/ROW]
[ROW][C]38[/C][C]-0.27005[/C][C]-2.2914[/C][C]0.012433[/C][/ROW]
[ROW][C]39[/C][C]-0.236524[/C][C]-2.007[/C][C]0.024254[/C][/ROW]
[ROW][C]40[/C][C]-0.201372[/C][C]-1.7087[/C][C]0.045907[/C][/ROW]
[ROW][C]41[/C][C]-0.161556[/C][C]-1.3708[/C][C]0.08734[/C][/ROW]
[ROW][C]42[/C][C]-0.124062[/C][C]-1.0527[/C][C]0.147999[/C][/ROW]
[ROW][C]43[/C][C]-0.097309[/C][C]-0.8257[/C][C]0.205852[/C][/ROW]
[ROW][C]44[/C][C]-0.070012[/C][C]-0.5941[/C][C]0.277162[/C][/ROW]
[ROW][C]45[/C][C]-0.04301[/C][C]-0.3649[/C][C]0.358109[/C][/ROW]
[ROW][C]46[/C][C]-0.016693[/C][C]-0.1416[/C][C]0.443878[/C][/ROW]
[ROW][C]47[/C][C]0.00708[/C][C]0.0601[/C][C]0.47613[/C][/ROW]
[ROW][C]48[/C][C]0.018961[/C][C]0.1609[/C][C]0.436315[/C][/ROW]
[ROW][C]49[/C][C]0.024886[/C][C]0.2112[/C][C]0.416679[/C][/ROW]
[ROW][C]50[/C][C]0.03056[/C][C]0.2593[/C][C]0.398068[/C][/ROW]
[ROW][C]51[/C][C]0.027515[/C][C]0.2335[/C][C]0.408027[/C][/ROW]
[ROW][C]52[/C][C]0.032102[/C][C]0.2724[/C][C]0.393048[/C][/ROW]
[ROW][C]53[/C][C]0.037739[/C][C]0.3202[/C][C]0.374861[/C][/ROW]
[ROW][C]54[/C][C]0.048958[/C][C]0.4154[/C][C]0.339535[/C][/ROW]
[ROW][C]55[/C][C]0.06131[/C][C]0.5202[/C][C]0.30225[/C][/ROW]
[ROW][C]56[/C][C]0.071738[/C][C]0.6087[/C][C]0.272314[/C][/ROW]
[ROW][C]57[/C][C]0.08458[/C][C]0.7177[/C][C]0.237636[/C][/ROW]
[ROW][C]58[/C][C]0.098409[/C][C]0.835[/C][C]0.203232[/C][/ROW]
[ROW][C]59[/C][C]0.106645[/C][C]0.9049[/C][C]0.184265[/C][/ROW]
[ROW][C]60[/C][C]0.118492[/C][C]1.0054[/C][C]0.159027[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71640&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71640&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
10.9406287.98150
20.8664627.35220
30.7833856.64720
40.685745.81870
50.5923095.02592e-06
60.4967464.2153.6e-05
70.4017273.40880.000536
80.3100732.63110.005202
90.2347231.99170.025099
100.1707831.44910.07582
110.1110480.94230.174601
120.0724140.61450.270427
130.0487970.41410.340031
140.0238770.20260.420008
15-0.003274-0.02780.488957
16-0.038-0.32240.374027
17-0.08226-0.6980.243713
18-0.131536-1.11610.134041
19-0.184997-1.56980.060428
20-0.234871-1.99290.025029
21-0.270949-2.29910.012202
22-0.308872-2.62090.005346
23-0.335181-2.84410.002897
24-0.361063-3.06370.001537
25-0.380325-3.22720.000941
26-0.386201-3.2770.000808
27-0.386212-3.27710.000808
28-0.383685-3.25570.000863
29-0.382019-3.24150.000901
30-0.383132-3.2510.000875
31-0.3815-3.23710.000913
32-0.372664-3.16220.001146
33-0.364961-3.09680.001394
34-0.356901-3.02840.001706
35-0.340278-2.88740.002563
36-0.320202-2.7170.004123
37-0.29746-2.5240.006904
38-0.27005-2.29140.012433
39-0.236524-2.0070.024254
40-0.201372-1.70870.045907
41-0.161556-1.37080.08734
42-0.124062-1.05270.147999
43-0.097309-0.82570.205852
44-0.070012-0.59410.277162
45-0.04301-0.36490.358109
46-0.016693-0.14160.443878
470.007080.06010.47613
480.0189610.16090.436315
490.0248860.21120.416679
500.030560.25930.398068
510.0275150.23350.408027
520.0321020.27240.393048
530.0377390.32020.374861
540.0489580.41540.339535
550.061310.52020.30225
560.0717380.60870.272314
570.084580.71770.237636
580.0984090.8350.203232
590.1066450.90490.184265
600.1184921.00540.159027







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9406287.98150
2-0.158988-1.34910.090773
3-0.103847-0.88120.190578
4-0.162107-1.37550.086617
50.0085690.07270.471119
6-0.076379-0.64810.259492
7-0.047592-0.40380.343767
8-0.05027-0.42660.335489
90.0828240.70280.242228
100.0084540.07170.471506
11-0.052484-0.44530.328704
120.0957980.81290.209486
130.055530.47120.319466
14-0.092261-0.78290.218139
15-0.109872-0.93230.177149
16-0.11215-0.95160.172236
17-0.099247-0.84210.20125
18-0.079804-0.67720.250237
19-0.082224-0.69770.243808
200.0213460.18110.428389
210.1166840.99010.162722
22-0.090353-0.76670.222891
230.0407750.3460.365182
24-0.07722-0.65520.257203
25-0.006897-0.05850.476749
26-0.019588-0.16620.434229
27-0.052757-0.44770.327873
28-0.090821-0.77060.221721
29-0.062186-0.52770.299676
30-0.091171-0.77360.220848
310.0074560.06330.474864
320.0948650.8050.211747
33-0.027045-0.22950.409571
34-0.011245-0.09540.462125
350.0508160.43120.33381
36-0.027198-0.23080.40907
37-0.031874-0.27050.393789
38-0.032074-0.27220.393142
390.0072050.06110.475711
40-0.01317-0.11180.455665
41-0.002549-0.02160.491403
42-0.072471-0.61490.270266
43-0.03199-0.27140.393412
440.0186950.15860.4372
450.0346760.29420.384714
460.0445760.37820.353183
47-0.005381-0.04570.481855
48-0.125488-1.06480.145261
49-0.073062-0.620.268623
50-0.018768-0.15930.436958
51-0.09387-0.79650.214176
520.0809640.6870.247145
53-0.022103-0.18760.425877
540.056560.47990.316368
55-0.023963-0.20330.419724
56-0.022846-0.19390.423418
570.0369860.31380.377278
580.0442420.37540.35423
59-0.111334-0.94470.173986
600.00550.04670.481454

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.940628 & 7.9815 & 0 \tabularnewline
2 & -0.158988 & -1.3491 & 0.090773 \tabularnewline
3 & -0.103847 & -0.8812 & 0.190578 \tabularnewline
4 & -0.162107 & -1.3755 & 0.086617 \tabularnewline
5 & 0.008569 & 0.0727 & 0.471119 \tabularnewline
6 & -0.076379 & -0.6481 & 0.259492 \tabularnewline
7 & -0.047592 & -0.4038 & 0.343767 \tabularnewline
8 & -0.05027 & -0.4266 & 0.335489 \tabularnewline
9 & 0.082824 & 0.7028 & 0.242228 \tabularnewline
10 & 0.008454 & 0.0717 & 0.471506 \tabularnewline
11 & -0.052484 & -0.4453 & 0.328704 \tabularnewline
12 & 0.095798 & 0.8129 & 0.209486 \tabularnewline
13 & 0.05553 & 0.4712 & 0.319466 \tabularnewline
14 & -0.092261 & -0.7829 & 0.218139 \tabularnewline
15 & -0.109872 & -0.9323 & 0.177149 \tabularnewline
16 & -0.11215 & -0.9516 & 0.172236 \tabularnewline
17 & -0.099247 & -0.8421 & 0.20125 \tabularnewline
18 & -0.079804 & -0.6772 & 0.250237 \tabularnewline
19 & -0.082224 & -0.6977 & 0.243808 \tabularnewline
20 & 0.021346 & 0.1811 & 0.428389 \tabularnewline
21 & 0.116684 & 0.9901 & 0.162722 \tabularnewline
22 & -0.090353 & -0.7667 & 0.222891 \tabularnewline
23 & 0.040775 & 0.346 & 0.365182 \tabularnewline
24 & -0.07722 & -0.6552 & 0.257203 \tabularnewline
25 & -0.006897 & -0.0585 & 0.476749 \tabularnewline
26 & -0.019588 & -0.1662 & 0.434229 \tabularnewline
27 & -0.052757 & -0.4477 & 0.327873 \tabularnewline
28 & -0.090821 & -0.7706 & 0.221721 \tabularnewline
29 & -0.062186 & -0.5277 & 0.299676 \tabularnewline
30 & -0.091171 & -0.7736 & 0.220848 \tabularnewline
31 & 0.007456 & 0.0633 & 0.474864 \tabularnewline
32 & 0.094865 & 0.805 & 0.211747 \tabularnewline
33 & -0.027045 & -0.2295 & 0.409571 \tabularnewline
34 & -0.011245 & -0.0954 & 0.462125 \tabularnewline
35 & 0.050816 & 0.4312 & 0.33381 \tabularnewline
36 & -0.027198 & -0.2308 & 0.40907 \tabularnewline
37 & -0.031874 & -0.2705 & 0.393789 \tabularnewline
38 & -0.032074 & -0.2722 & 0.393142 \tabularnewline
39 & 0.007205 & 0.0611 & 0.475711 \tabularnewline
40 & -0.01317 & -0.1118 & 0.455665 \tabularnewline
41 & -0.002549 & -0.0216 & 0.491403 \tabularnewline
42 & -0.072471 & -0.6149 & 0.270266 \tabularnewline
43 & -0.03199 & -0.2714 & 0.393412 \tabularnewline
44 & 0.018695 & 0.1586 & 0.4372 \tabularnewline
45 & 0.034676 & 0.2942 & 0.384714 \tabularnewline
46 & 0.044576 & 0.3782 & 0.353183 \tabularnewline
47 & -0.005381 & -0.0457 & 0.481855 \tabularnewline
48 & -0.125488 & -1.0648 & 0.145261 \tabularnewline
49 & -0.073062 & -0.62 & 0.268623 \tabularnewline
50 & -0.018768 & -0.1593 & 0.436958 \tabularnewline
51 & -0.09387 & -0.7965 & 0.214176 \tabularnewline
52 & 0.080964 & 0.687 & 0.247145 \tabularnewline
53 & -0.022103 & -0.1876 & 0.425877 \tabularnewline
54 & 0.05656 & 0.4799 & 0.316368 \tabularnewline
55 & -0.023963 & -0.2033 & 0.419724 \tabularnewline
56 & -0.022846 & -0.1939 & 0.423418 \tabularnewline
57 & 0.036986 & 0.3138 & 0.377278 \tabularnewline
58 & 0.044242 & 0.3754 & 0.35423 \tabularnewline
59 & -0.111334 & -0.9447 & 0.173986 \tabularnewline
60 & 0.0055 & 0.0467 & 0.481454 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71640&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]0.940628[/C][C]7.9815[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.158988[/C][C]-1.3491[/C][C]0.090773[/C][/ROW]
[ROW][C]3[/C][C]-0.103847[/C][C]-0.8812[/C][C]0.190578[/C][/ROW]
[ROW][C]4[/C][C]-0.162107[/C][C]-1.3755[/C][C]0.086617[/C][/ROW]
[ROW][C]5[/C][C]0.008569[/C][C]0.0727[/C][C]0.471119[/C][/ROW]
[ROW][C]6[/C][C]-0.076379[/C][C]-0.6481[/C][C]0.259492[/C][/ROW]
[ROW][C]7[/C][C]-0.047592[/C][C]-0.4038[/C][C]0.343767[/C][/ROW]
[ROW][C]8[/C][C]-0.05027[/C][C]-0.4266[/C][C]0.335489[/C][/ROW]
[ROW][C]9[/C][C]0.082824[/C][C]0.7028[/C][C]0.242228[/C][/ROW]
[ROW][C]10[/C][C]0.008454[/C][C]0.0717[/C][C]0.471506[/C][/ROW]
[ROW][C]11[/C][C]-0.052484[/C][C]-0.4453[/C][C]0.328704[/C][/ROW]
[ROW][C]12[/C][C]0.095798[/C][C]0.8129[/C][C]0.209486[/C][/ROW]
[ROW][C]13[/C][C]0.05553[/C][C]0.4712[/C][C]0.319466[/C][/ROW]
[ROW][C]14[/C][C]-0.092261[/C][C]-0.7829[/C][C]0.218139[/C][/ROW]
[ROW][C]15[/C][C]-0.109872[/C][C]-0.9323[/C][C]0.177149[/C][/ROW]
[ROW][C]16[/C][C]-0.11215[/C][C]-0.9516[/C][C]0.172236[/C][/ROW]
[ROW][C]17[/C][C]-0.099247[/C][C]-0.8421[/C][C]0.20125[/C][/ROW]
[ROW][C]18[/C][C]-0.079804[/C][C]-0.6772[/C][C]0.250237[/C][/ROW]
[ROW][C]19[/C][C]-0.082224[/C][C]-0.6977[/C][C]0.243808[/C][/ROW]
[ROW][C]20[/C][C]0.021346[/C][C]0.1811[/C][C]0.428389[/C][/ROW]
[ROW][C]21[/C][C]0.116684[/C][C]0.9901[/C][C]0.162722[/C][/ROW]
[ROW][C]22[/C][C]-0.090353[/C][C]-0.7667[/C][C]0.222891[/C][/ROW]
[ROW][C]23[/C][C]0.040775[/C][C]0.346[/C][C]0.365182[/C][/ROW]
[ROW][C]24[/C][C]-0.07722[/C][C]-0.6552[/C][C]0.257203[/C][/ROW]
[ROW][C]25[/C][C]-0.006897[/C][C]-0.0585[/C][C]0.476749[/C][/ROW]
[ROW][C]26[/C][C]-0.019588[/C][C]-0.1662[/C][C]0.434229[/C][/ROW]
[ROW][C]27[/C][C]-0.052757[/C][C]-0.4477[/C][C]0.327873[/C][/ROW]
[ROW][C]28[/C][C]-0.090821[/C][C]-0.7706[/C][C]0.221721[/C][/ROW]
[ROW][C]29[/C][C]-0.062186[/C][C]-0.5277[/C][C]0.299676[/C][/ROW]
[ROW][C]30[/C][C]-0.091171[/C][C]-0.7736[/C][C]0.220848[/C][/ROW]
[ROW][C]31[/C][C]0.007456[/C][C]0.0633[/C][C]0.474864[/C][/ROW]
[ROW][C]32[/C][C]0.094865[/C][C]0.805[/C][C]0.211747[/C][/ROW]
[ROW][C]33[/C][C]-0.027045[/C][C]-0.2295[/C][C]0.409571[/C][/ROW]
[ROW][C]34[/C][C]-0.011245[/C][C]-0.0954[/C][C]0.462125[/C][/ROW]
[ROW][C]35[/C][C]0.050816[/C][C]0.4312[/C][C]0.33381[/C][/ROW]
[ROW][C]36[/C][C]-0.027198[/C][C]-0.2308[/C][C]0.40907[/C][/ROW]
[ROW][C]37[/C][C]-0.031874[/C][C]-0.2705[/C][C]0.393789[/C][/ROW]
[ROW][C]38[/C][C]-0.032074[/C][C]-0.2722[/C][C]0.393142[/C][/ROW]
[ROW][C]39[/C][C]0.007205[/C][C]0.0611[/C][C]0.475711[/C][/ROW]
[ROW][C]40[/C][C]-0.01317[/C][C]-0.1118[/C][C]0.455665[/C][/ROW]
[ROW][C]41[/C][C]-0.002549[/C][C]-0.0216[/C][C]0.491403[/C][/ROW]
[ROW][C]42[/C][C]-0.072471[/C][C]-0.6149[/C][C]0.270266[/C][/ROW]
[ROW][C]43[/C][C]-0.03199[/C][C]-0.2714[/C][C]0.393412[/C][/ROW]
[ROW][C]44[/C][C]0.018695[/C][C]0.1586[/C][C]0.4372[/C][/ROW]
[ROW][C]45[/C][C]0.034676[/C][C]0.2942[/C][C]0.384714[/C][/ROW]
[ROW][C]46[/C][C]0.044576[/C][C]0.3782[/C][C]0.353183[/C][/ROW]
[ROW][C]47[/C][C]-0.005381[/C][C]-0.0457[/C][C]0.481855[/C][/ROW]
[ROW][C]48[/C][C]-0.125488[/C][C]-1.0648[/C][C]0.145261[/C][/ROW]
[ROW][C]49[/C][C]-0.073062[/C][C]-0.62[/C][C]0.268623[/C][/ROW]
[ROW][C]50[/C][C]-0.018768[/C][C]-0.1593[/C][C]0.436958[/C][/ROW]
[ROW][C]51[/C][C]-0.09387[/C][C]-0.7965[/C][C]0.214176[/C][/ROW]
[ROW][C]52[/C][C]0.080964[/C][C]0.687[/C][C]0.247145[/C][/ROW]
[ROW][C]53[/C][C]-0.022103[/C][C]-0.1876[/C][C]0.425877[/C][/ROW]
[ROW][C]54[/C][C]0.05656[/C][C]0.4799[/C][C]0.316368[/C][/ROW]
[ROW][C]55[/C][C]-0.023963[/C][C]-0.2033[/C][C]0.419724[/C][/ROW]
[ROW][C]56[/C][C]-0.022846[/C][C]-0.1939[/C][C]0.423418[/C][/ROW]
[ROW][C]57[/C][C]0.036986[/C][C]0.3138[/C][C]0.377278[/C][/ROW]
[ROW][C]58[/C][C]0.044242[/C][C]0.3754[/C][C]0.35423[/C][/ROW]
[ROW][C]59[/C][C]-0.111334[/C][C]-0.9447[/C][C]0.173986[/C][/ROW]
[ROW][C]60[/C][C]0.0055[/C][C]0.0467[/C][C]0.481454[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71640&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71640&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
10.9406287.98150
2-0.158988-1.34910.090773
3-0.103847-0.88120.190578
4-0.162107-1.37550.086617
50.0085690.07270.471119
6-0.076379-0.64810.259492
7-0.047592-0.40380.343767
8-0.05027-0.42660.335489
90.0828240.70280.242228
100.0084540.07170.471506
11-0.052484-0.44530.328704
120.0957980.81290.209486
130.055530.47120.319466
14-0.092261-0.78290.218139
15-0.109872-0.93230.177149
16-0.11215-0.95160.172236
17-0.099247-0.84210.20125
18-0.079804-0.67720.250237
19-0.082224-0.69770.243808
200.0213460.18110.428389
210.1166840.99010.162722
22-0.090353-0.76670.222891
230.0407750.3460.365182
24-0.07722-0.65520.257203
25-0.006897-0.05850.476749
26-0.019588-0.16620.434229
27-0.052757-0.44770.327873
28-0.090821-0.77060.221721
29-0.062186-0.52770.299676
30-0.091171-0.77360.220848
310.0074560.06330.474864
320.0948650.8050.211747
33-0.027045-0.22950.409571
34-0.011245-0.09540.462125
350.0508160.43120.33381
36-0.027198-0.23080.40907
37-0.031874-0.27050.393789
38-0.032074-0.27220.393142
390.0072050.06110.475711
40-0.01317-0.11180.455665
41-0.002549-0.02160.491403
42-0.072471-0.61490.270266
43-0.03199-0.27140.393412
440.0186950.15860.4372
450.0346760.29420.384714
460.0445760.37820.353183
47-0.005381-0.04570.481855
48-0.125488-1.06480.145261
49-0.073062-0.620.268623
50-0.018768-0.15930.436958
51-0.09387-0.79650.214176
520.0809640.6870.247145
53-0.022103-0.18760.425877
540.056560.47990.316368
55-0.023963-0.20330.419724
56-0.022846-0.19390.423418
570.0369860.31380.377278
580.0442420.37540.35423
59-0.111334-0.94470.173986
600.00550.04670.481454



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; 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')