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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, 17 Nov 2010 16:17:19 +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/Nov/17/t1290010590og5wvznghyqzk5d.htm/, Retrieved Fri, 29 Mar 2024 09:05:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=96772, Retrieved Fri, 29 Mar 2024 09:05:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Aantal personen l...] [2010-11-17 16:17:19] [5815de052410d7754c978b0de903e641] [Current]
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Dataseries X:
100,4
97,7
97
96,5
98,4
106,3
103,1
102,4
95
98,1
106,1
99,1
101,2
95,5
99,8
97,1
97,5
96,8
97,7
100,9
94,3
99,5
100,8
97
99,2
101
102,3
97
91,2
97,6
95,7
100,5
94,4
102,9
105,1
98,8
100,7
99,6
107,7
102,9
101,6
102,7
110,5
109,8
94,3
102,5
105
102,3
107,7
100,3
99,5
95
97,7
96,3
97,8
106,4
96,1
106,2
114,7
111,9
121
117,7
115,4
114,3
109,5
108,1
108,2
99,1
101,2
98,1
95,5
97,9
98,2
98,7
95,6
95,8
94,4
96,5
103,3
104,3
104,5
102,3
103,8
103,1
102,2
106,3
102,1
94
102,6
102,6
106,7
107,9
109,3
105,9
109,1
108,5
111,7
109,8
109,1
108,5
108,5
106,2
117,1
109,8
115,2
115,9
119,2
121
118,6
117,6
114,6
110,6
102,5
101,6
107,4
105,8
102,8
104
100,4
100,6




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=96772&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=96772&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96772&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
10.7534148.25320
20.6636847.27030
30.5839826.39720
40.4743895.19670
50.4170554.56866e-06
60.2716792.97610.001766
70.2163752.37030.009684
80.1276761.39860.082252
90.0720920.78970.215621
100.0348530.38180.351646
110.0272920.2990.382738
120.1160391.27110.103069
130.0523850.57380.283573
140.0476710.52220.301242
150.0536110.58730.279059
160.0716610.7850.217
170.1028771.1270.131003
180.0521260.5710.28453
190.0820160.89840.185376
200.0682490.74760.228074
210.0377180.41320.340104
22-0.000279-0.00310.498781
230.0035530.03890.484507
240.0347410.38060.352099
25-0.039375-0.43130.3335
26-0.048544-0.53180.297933
27-0.093565-1.0250.153724
28-0.096658-1.05880.145902
29-0.115373-1.26380.104367
30-0.129552-1.41920.079221
31-0.101799-1.11520.133506
32-0.120191-1.31660.095237
33-0.105438-1.1550.125189
34-0.122671-1.34380.090775
35-0.085509-0.93670.175397
366.1e-057e-040.499734
37-0.012293-0.13470.446551
38-0.016414-0.17980.428804
39-0.011506-0.1260.449953
400.015890.17410.431055
410.058660.64260.260858
420.122051.3370.091878
430.1592181.74410.041847
440.1624591.77970.038832
450.1621021.77570.039156
460.1569141.71890.044105
470.1883182.06290.020639
480.1783031.95320.026561

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.753414 & 8.2532 & 0 \tabularnewline
2 & 0.663684 & 7.2703 & 0 \tabularnewline
3 & 0.583982 & 6.3972 & 0 \tabularnewline
4 & 0.474389 & 5.1967 & 0 \tabularnewline
5 & 0.417055 & 4.5686 & 6e-06 \tabularnewline
6 & 0.271679 & 2.9761 & 0.001766 \tabularnewline
7 & 0.216375 & 2.3703 & 0.009684 \tabularnewline
8 & 0.127676 & 1.3986 & 0.082252 \tabularnewline
9 & 0.072092 & 0.7897 & 0.215621 \tabularnewline
10 & 0.034853 & 0.3818 & 0.351646 \tabularnewline
11 & 0.027292 & 0.299 & 0.382738 \tabularnewline
12 & 0.116039 & 1.2711 & 0.103069 \tabularnewline
13 & 0.052385 & 0.5738 & 0.283573 \tabularnewline
14 & 0.047671 & 0.5222 & 0.301242 \tabularnewline
15 & 0.053611 & 0.5873 & 0.279059 \tabularnewline
16 & 0.071661 & 0.785 & 0.217 \tabularnewline
17 & 0.102877 & 1.127 & 0.131003 \tabularnewline
18 & 0.052126 & 0.571 & 0.28453 \tabularnewline
19 & 0.082016 & 0.8984 & 0.185376 \tabularnewline
20 & 0.068249 & 0.7476 & 0.228074 \tabularnewline
21 & 0.037718 & 0.4132 & 0.340104 \tabularnewline
22 & -0.000279 & -0.0031 & 0.498781 \tabularnewline
23 & 0.003553 & 0.0389 & 0.484507 \tabularnewline
24 & 0.034741 & 0.3806 & 0.352099 \tabularnewline
25 & -0.039375 & -0.4313 & 0.3335 \tabularnewline
26 & -0.048544 & -0.5318 & 0.297933 \tabularnewline
27 & -0.093565 & -1.025 & 0.153724 \tabularnewline
28 & -0.096658 & -1.0588 & 0.145902 \tabularnewline
29 & -0.115373 & -1.2638 & 0.104367 \tabularnewline
30 & -0.129552 & -1.4192 & 0.079221 \tabularnewline
31 & -0.101799 & -1.1152 & 0.133506 \tabularnewline
32 & -0.120191 & -1.3166 & 0.095237 \tabularnewline
33 & -0.105438 & -1.155 & 0.125189 \tabularnewline
34 & -0.122671 & -1.3438 & 0.090775 \tabularnewline
35 & -0.085509 & -0.9367 & 0.175397 \tabularnewline
36 & 6.1e-05 & 7e-04 & 0.499734 \tabularnewline
37 & -0.012293 & -0.1347 & 0.446551 \tabularnewline
38 & -0.016414 & -0.1798 & 0.428804 \tabularnewline
39 & -0.011506 & -0.126 & 0.449953 \tabularnewline
40 & 0.01589 & 0.1741 & 0.431055 \tabularnewline
41 & 0.05866 & 0.6426 & 0.260858 \tabularnewline
42 & 0.12205 & 1.337 & 0.091878 \tabularnewline
43 & 0.159218 & 1.7441 & 0.041847 \tabularnewline
44 & 0.162459 & 1.7797 & 0.038832 \tabularnewline
45 & 0.162102 & 1.7757 & 0.039156 \tabularnewline
46 & 0.156914 & 1.7189 & 0.044105 \tabularnewline
47 & 0.188318 & 2.0629 & 0.020639 \tabularnewline
48 & 0.178303 & 1.9532 & 0.026561 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96772&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]0.753414[/C][C]8.2532[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.663684[/C][C]7.2703[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.583982[/C][C]6.3972[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.474389[/C][C]5.1967[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.417055[/C][C]4.5686[/C][C]6e-06[/C][/ROW]
[ROW][C]6[/C][C]0.271679[/C][C]2.9761[/C][C]0.001766[/C][/ROW]
[ROW][C]7[/C][C]0.216375[/C][C]2.3703[/C][C]0.009684[/C][/ROW]
[ROW][C]8[/C][C]0.127676[/C][C]1.3986[/C][C]0.082252[/C][/ROW]
[ROW][C]9[/C][C]0.072092[/C][C]0.7897[/C][C]0.215621[/C][/ROW]
[ROW][C]10[/C][C]0.034853[/C][C]0.3818[/C][C]0.351646[/C][/ROW]
[ROW][C]11[/C][C]0.027292[/C][C]0.299[/C][C]0.382738[/C][/ROW]
[ROW][C]12[/C][C]0.116039[/C][C]1.2711[/C][C]0.103069[/C][/ROW]
[ROW][C]13[/C][C]0.052385[/C][C]0.5738[/C][C]0.283573[/C][/ROW]
[ROW][C]14[/C][C]0.047671[/C][C]0.5222[/C][C]0.301242[/C][/ROW]
[ROW][C]15[/C][C]0.053611[/C][C]0.5873[/C][C]0.279059[/C][/ROW]
[ROW][C]16[/C][C]0.071661[/C][C]0.785[/C][C]0.217[/C][/ROW]
[ROW][C]17[/C][C]0.102877[/C][C]1.127[/C][C]0.131003[/C][/ROW]
[ROW][C]18[/C][C]0.052126[/C][C]0.571[/C][C]0.28453[/C][/ROW]
[ROW][C]19[/C][C]0.082016[/C][C]0.8984[/C][C]0.185376[/C][/ROW]
[ROW][C]20[/C][C]0.068249[/C][C]0.7476[/C][C]0.228074[/C][/ROW]
[ROW][C]21[/C][C]0.037718[/C][C]0.4132[/C][C]0.340104[/C][/ROW]
[ROW][C]22[/C][C]-0.000279[/C][C]-0.0031[/C][C]0.498781[/C][/ROW]
[ROW][C]23[/C][C]0.003553[/C][C]0.0389[/C][C]0.484507[/C][/ROW]
[ROW][C]24[/C][C]0.034741[/C][C]0.3806[/C][C]0.352099[/C][/ROW]
[ROW][C]25[/C][C]-0.039375[/C][C]-0.4313[/C][C]0.3335[/C][/ROW]
[ROW][C]26[/C][C]-0.048544[/C][C]-0.5318[/C][C]0.297933[/C][/ROW]
[ROW][C]27[/C][C]-0.093565[/C][C]-1.025[/C][C]0.153724[/C][/ROW]
[ROW][C]28[/C][C]-0.096658[/C][C]-1.0588[/C][C]0.145902[/C][/ROW]
[ROW][C]29[/C][C]-0.115373[/C][C]-1.2638[/C][C]0.104367[/C][/ROW]
[ROW][C]30[/C][C]-0.129552[/C][C]-1.4192[/C][C]0.079221[/C][/ROW]
[ROW][C]31[/C][C]-0.101799[/C][C]-1.1152[/C][C]0.133506[/C][/ROW]
[ROW][C]32[/C][C]-0.120191[/C][C]-1.3166[/C][C]0.095237[/C][/ROW]
[ROW][C]33[/C][C]-0.105438[/C][C]-1.155[/C][C]0.125189[/C][/ROW]
[ROW][C]34[/C][C]-0.122671[/C][C]-1.3438[/C][C]0.090775[/C][/ROW]
[ROW][C]35[/C][C]-0.085509[/C][C]-0.9367[/C][C]0.175397[/C][/ROW]
[ROW][C]36[/C][C]6.1e-05[/C][C]7e-04[/C][C]0.499734[/C][/ROW]
[ROW][C]37[/C][C]-0.012293[/C][C]-0.1347[/C][C]0.446551[/C][/ROW]
[ROW][C]38[/C][C]-0.016414[/C][C]-0.1798[/C][C]0.428804[/C][/ROW]
[ROW][C]39[/C][C]-0.011506[/C][C]-0.126[/C][C]0.449953[/C][/ROW]
[ROW][C]40[/C][C]0.01589[/C][C]0.1741[/C][C]0.431055[/C][/ROW]
[ROW][C]41[/C][C]0.05866[/C][C]0.6426[/C][C]0.260858[/C][/ROW]
[ROW][C]42[/C][C]0.12205[/C][C]1.337[/C][C]0.091878[/C][/ROW]
[ROW][C]43[/C][C]0.159218[/C][C]1.7441[/C][C]0.041847[/C][/ROW]
[ROW][C]44[/C][C]0.162459[/C][C]1.7797[/C][C]0.038832[/C][/ROW]
[ROW][C]45[/C][C]0.162102[/C][C]1.7757[/C][C]0.039156[/C][/ROW]
[ROW][C]46[/C][C]0.156914[/C][C]1.7189[/C][C]0.044105[/C][/ROW]
[ROW][C]47[/C][C]0.188318[/C][C]2.0629[/C][C]0.020639[/C][/ROW]
[ROW][C]48[/C][C]0.178303[/C][C]1.9532[/C][C]0.026561[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96772&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96772&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
10.7534148.25320
20.6636847.27030
30.5839826.39720
40.4743895.19670
50.4170554.56866e-06
60.2716792.97610.001766
70.2163752.37030.009684
80.1276761.39860.082252
90.0720920.78970.215621
100.0348530.38180.351646
110.0272920.2990.382738
120.1160391.27110.103069
130.0523850.57380.283573
140.0476710.52220.301242
150.0536110.58730.279059
160.0716610.7850.217
170.1028771.1270.131003
180.0521260.5710.28453
190.0820160.89840.185376
200.0682490.74760.228074
210.0377180.41320.340104
22-0.000279-0.00310.498781
230.0035530.03890.484507
240.0347410.38060.352099
25-0.039375-0.43130.3335
26-0.048544-0.53180.297933
27-0.093565-1.0250.153724
28-0.096658-1.05880.145902
29-0.115373-1.26380.104367
30-0.129552-1.41920.079221
31-0.101799-1.11520.133506
32-0.120191-1.31660.095237
33-0.105438-1.1550.125189
34-0.122671-1.34380.090775
35-0.085509-0.93670.175397
366.1e-057e-040.499734
37-0.012293-0.13470.446551
38-0.016414-0.17980.428804
39-0.011506-0.1260.449953
400.015890.17410.431055
410.058660.64260.260858
420.122051.3370.091878
430.1592181.74410.041847
440.1624591.77970.038832
450.1621021.77570.039156
460.1569141.71890.044105
470.1883182.06290.020639
480.1783031.95320.026561







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7534148.25320
20.2221512.43350.008213
30.0673020.73730.231204
4-0.075972-0.83220.203466
50.0311710.34150.366678
6-0.205324-2.24920.013162
70.0308720.33820.367906
8-0.080626-0.88320.189444
90.0246640.27020.393744
10-0.00901-0.09870.46077
110.1139351.24810.107212
120.2408842.63870.004713
13-0.166513-1.82410.035316
14-0.054999-0.60250.273996
15-0.016859-0.18470.426897
160.0678350.74310.229437
170.0049040.05370.478625
18-0.063917-0.70020.242585
190.0624470.68410.247623
200.0073120.08010.468144
21-0.055019-0.60270.273922
22-0.078587-0.86090.19551
230.0915661.00310.158927
240.0048890.05360.478691
25-0.123978-1.35810.088489
260.0220750.24180.404667
27-0.06503-0.71240.238809
28-0.004954-0.05430.478405
29-0.090605-0.99250.161468
300.1212011.32770.0934
310.0060430.06620.473667
32-0.054416-0.59610.276116
330.0125820.13780.445303
340.0047650.05220.479228
350.0264450.28970.386277
360.0875320.95890.169778
37-0.005278-0.05780.476997
38-0.108866-1.19260.117695
390.0206630.22640.410655
400.0226850.24850.402086
410.1481111.62250.053664
420.1946432.13220.017514
43-0.027174-0.29770.383231
44-0.023372-0.2560.399184
45-0.062728-0.68720.246657
460.043940.48130.315577
470.0174640.19130.424302
48-0.098449-1.07850.141496

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.753414 & 8.2532 & 0 \tabularnewline
2 & 0.222151 & 2.4335 & 0.008213 \tabularnewline
3 & 0.067302 & 0.7373 & 0.231204 \tabularnewline
4 & -0.075972 & -0.8322 & 0.203466 \tabularnewline
5 & 0.031171 & 0.3415 & 0.366678 \tabularnewline
6 & -0.205324 & -2.2492 & 0.013162 \tabularnewline
7 & 0.030872 & 0.3382 & 0.367906 \tabularnewline
8 & -0.080626 & -0.8832 & 0.189444 \tabularnewline
9 & 0.024664 & 0.2702 & 0.393744 \tabularnewline
10 & -0.00901 & -0.0987 & 0.46077 \tabularnewline
11 & 0.113935 & 1.2481 & 0.107212 \tabularnewline
12 & 0.240884 & 2.6387 & 0.004713 \tabularnewline
13 & -0.166513 & -1.8241 & 0.035316 \tabularnewline
14 & -0.054999 & -0.6025 & 0.273996 \tabularnewline
15 & -0.016859 & -0.1847 & 0.426897 \tabularnewline
16 & 0.067835 & 0.7431 & 0.229437 \tabularnewline
17 & 0.004904 & 0.0537 & 0.478625 \tabularnewline
18 & -0.063917 & -0.7002 & 0.242585 \tabularnewline
19 & 0.062447 & 0.6841 & 0.247623 \tabularnewline
20 & 0.007312 & 0.0801 & 0.468144 \tabularnewline
21 & -0.055019 & -0.6027 & 0.273922 \tabularnewline
22 & -0.078587 & -0.8609 & 0.19551 \tabularnewline
23 & 0.091566 & 1.0031 & 0.158927 \tabularnewline
24 & 0.004889 & 0.0536 & 0.478691 \tabularnewline
25 & -0.123978 & -1.3581 & 0.088489 \tabularnewline
26 & 0.022075 & 0.2418 & 0.404667 \tabularnewline
27 & -0.06503 & -0.7124 & 0.238809 \tabularnewline
28 & -0.004954 & -0.0543 & 0.478405 \tabularnewline
29 & -0.090605 & -0.9925 & 0.161468 \tabularnewline
30 & 0.121201 & 1.3277 & 0.0934 \tabularnewline
31 & 0.006043 & 0.0662 & 0.473667 \tabularnewline
32 & -0.054416 & -0.5961 & 0.276116 \tabularnewline
33 & 0.012582 & 0.1378 & 0.445303 \tabularnewline
34 & 0.004765 & 0.0522 & 0.479228 \tabularnewline
35 & 0.026445 & 0.2897 & 0.386277 \tabularnewline
36 & 0.087532 & 0.9589 & 0.169778 \tabularnewline
37 & -0.005278 & -0.0578 & 0.476997 \tabularnewline
38 & -0.108866 & -1.1926 & 0.117695 \tabularnewline
39 & 0.020663 & 0.2264 & 0.410655 \tabularnewline
40 & 0.022685 & 0.2485 & 0.402086 \tabularnewline
41 & 0.148111 & 1.6225 & 0.053664 \tabularnewline
42 & 0.194643 & 2.1322 & 0.017514 \tabularnewline
43 & -0.027174 & -0.2977 & 0.383231 \tabularnewline
44 & -0.023372 & -0.256 & 0.399184 \tabularnewline
45 & -0.062728 & -0.6872 & 0.246657 \tabularnewline
46 & 0.04394 & 0.4813 & 0.315577 \tabularnewline
47 & 0.017464 & 0.1913 & 0.424302 \tabularnewline
48 & -0.098449 & -1.0785 & 0.141496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96772&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]0.753414[/C][C]8.2532[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.222151[/C][C]2.4335[/C][C]0.008213[/C][/ROW]
[ROW][C]3[/C][C]0.067302[/C][C]0.7373[/C][C]0.231204[/C][/ROW]
[ROW][C]4[/C][C]-0.075972[/C][C]-0.8322[/C][C]0.203466[/C][/ROW]
[ROW][C]5[/C][C]0.031171[/C][C]0.3415[/C][C]0.366678[/C][/ROW]
[ROW][C]6[/C][C]-0.205324[/C][C]-2.2492[/C][C]0.013162[/C][/ROW]
[ROW][C]7[/C][C]0.030872[/C][C]0.3382[/C][C]0.367906[/C][/ROW]
[ROW][C]8[/C][C]-0.080626[/C][C]-0.8832[/C][C]0.189444[/C][/ROW]
[ROW][C]9[/C][C]0.024664[/C][C]0.2702[/C][C]0.393744[/C][/ROW]
[ROW][C]10[/C][C]-0.00901[/C][C]-0.0987[/C][C]0.46077[/C][/ROW]
[ROW][C]11[/C][C]0.113935[/C][C]1.2481[/C][C]0.107212[/C][/ROW]
[ROW][C]12[/C][C]0.240884[/C][C]2.6387[/C][C]0.004713[/C][/ROW]
[ROW][C]13[/C][C]-0.166513[/C][C]-1.8241[/C][C]0.035316[/C][/ROW]
[ROW][C]14[/C][C]-0.054999[/C][C]-0.6025[/C][C]0.273996[/C][/ROW]
[ROW][C]15[/C][C]-0.016859[/C][C]-0.1847[/C][C]0.426897[/C][/ROW]
[ROW][C]16[/C][C]0.067835[/C][C]0.7431[/C][C]0.229437[/C][/ROW]
[ROW][C]17[/C][C]0.004904[/C][C]0.0537[/C][C]0.478625[/C][/ROW]
[ROW][C]18[/C][C]-0.063917[/C][C]-0.7002[/C][C]0.242585[/C][/ROW]
[ROW][C]19[/C][C]0.062447[/C][C]0.6841[/C][C]0.247623[/C][/ROW]
[ROW][C]20[/C][C]0.007312[/C][C]0.0801[/C][C]0.468144[/C][/ROW]
[ROW][C]21[/C][C]-0.055019[/C][C]-0.6027[/C][C]0.273922[/C][/ROW]
[ROW][C]22[/C][C]-0.078587[/C][C]-0.8609[/C][C]0.19551[/C][/ROW]
[ROW][C]23[/C][C]0.091566[/C][C]1.0031[/C][C]0.158927[/C][/ROW]
[ROW][C]24[/C][C]0.004889[/C][C]0.0536[/C][C]0.478691[/C][/ROW]
[ROW][C]25[/C][C]-0.123978[/C][C]-1.3581[/C][C]0.088489[/C][/ROW]
[ROW][C]26[/C][C]0.022075[/C][C]0.2418[/C][C]0.404667[/C][/ROW]
[ROW][C]27[/C][C]-0.06503[/C][C]-0.7124[/C][C]0.238809[/C][/ROW]
[ROW][C]28[/C][C]-0.004954[/C][C]-0.0543[/C][C]0.478405[/C][/ROW]
[ROW][C]29[/C][C]-0.090605[/C][C]-0.9925[/C][C]0.161468[/C][/ROW]
[ROW][C]30[/C][C]0.121201[/C][C]1.3277[/C][C]0.0934[/C][/ROW]
[ROW][C]31[/C][C]0.006043[/C][C]0.0662[/C][C]0.473667[/C][/ROW]
[ROW][C]32[/C][C]-0.054416[/C][C]-0.5961[/C][C]0.276116[/C][/ROW]
[ROW][C]33[/C][C]0.012582[/C][C]0.1378[/C][C]0.445303[/C][/ROW]
[ROW][C]34[/C][C]0.004765[/C][C]0.0522[/C][C]0.479228[/C][/ROW]
[ROW][C]35[/C][C]0.026445[/C][C]0.2897[/C][C]0.386277[/C][/ROW]
[ROW][C]36[/C][C]0.087532[/C][C]0.9589[/C][C]0.169778[/C][/ROW]
[ROW][C]37[/C][C]-0.005278[/C][C]-0.0578[/C][C]0.476997[/C][/ROW]
[ROW][C]38[/C][C]-0.108866[/C][C]-1.1926[/C][C]0.117695[/C][/ROW]
[ROW][C]39[/C][C]0.020663[/C][C]0.2264[/C][C]0.410655[/C][/ROW]
[ROW][C]40[/C][C]0.022685[/C][C]0.2485[/C][C]0.402086[/C][/ROW]
[ROW][C]41[/C][C]0.148111[/C][C]1.6225[/C][C]0.053664[/C][/ROW]
[ROW][C]42[/C][C]0.194643[/C][C]2.1322[/C][C]0.017514[/C][/ROW]
[ROW][C]43[/C][C]-0.027174[/C][C]-0.2977[/C][C]0.383231[/C][/ROW]
[ROW][C]44[/C][C]-0.023372[/C][C]-0.256[/C][C]0.399184[/C][/ROW]
[ROW][C]45[/C][C]-0.062728[/C][C]-0.6872[/C][C]0.246657[/C][/ROW]
[ROW][C]46[/C][C]0.04394[/C][C]0.4813[/C][C]0.315577[/C][/ROW]
[ROW][C]47[/C][C]0.017464[/C][C]0.1913[/C][C]0.424302[/C][/ROW]
[ROW][C]48[/C][C]-0.098449[/C][C]-1.0785[/C][C]0.141496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96772&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96772&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
10.7534148.25320
20.2221512.43350.008213
30.0673020.73730.231204
4-0.075972-0.83220.203466
50.0311710.34150.366678
6-0.205324-2.24920.013162
70.0308720.33820.367906
8-0.080626-0.88320.189444
90.0246640.27020.393744
10-0.00901-0.09870.46077
110.1139351.24810.107212
120.2408842.63870.004713
13-0.166513-1.82410.035316
14-0.054999-0.60250.273996
15-0.016859-0.18470.426897
160.0678350.74310.229437
170.0049040.05370.478625
18-0.063917-0.70020.242585
190.0624470.68410.247623
200.0073120.08010.468144
21-0.055019-0.60270.273922
22-0.078587-0.86090.19551
230.0915661.00310.158927
240.0048890.05360.478691
25-0.123978-1.35810.088489
260.0220750.24180.404667
27-0.06503-0.71240.238809
28-0.004954-0.05430.478405
29-0.090605-0.99250.161468
300.1212011.32770.0934
310.0060430.06620.473667
32-0.054416-0.59610.276116
330.0125820.13780.445303
340.0047650.05220.479228
350.0264450.28970.386277
360.0875320.95890.169778
37-0.005278-0.05780.476997
38-0.108866-1.19260.117695
390.0206630.22640.410655
400.0226850.24850.402086
410.1481111.62250.053664
420.1946432.13220.017514
43-0.027174-0.29770.383231
44-0.023372-0.2560.399184
45-0.062728-0.68720.246657
460.043940.48130.315577
470.0174640.19130.424302
48-0.098449-1.07850.141496



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