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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 22 Dec 2012 18:42:44 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/22/t1356219784ap651psn4tyhq63.htm/, Retrieved Thu, 28 Mar 2024 21:47:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204644, Retrieved Thu, 28 Mar 2024 21:47:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-12-16 20:15:45] [1eab65e90adf64584b8e6f0da23ff414]
-               [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-12-19 16:25:55] [1eab65e90adf64584b8e6f0da23ff414]
- R P               [(Partial) Autocorrelation Function] [] [2012-12-22 23:42:44] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
103.34
102.60
100.69
105.67
123.61
113.08
106.46
123.38
109.87
95.74
123.06
123.39
120.28
115.33
110.40
114.49
132.03
123.16
118.82
128.32
112.24
104.53
132.57
122.52
131.80
124.55
120.96
122.60
145.52
118.57
134.25
136.70
121.37
111.63
134.42
137.65
137.86
119.77
130.69
128.28
147.45
128.42
136.90
143.95
135.64
122.48
136.83
153.04
142.71
123.46
144.37
146.15
147.61
158.51
147.40
165.05
154.64
126.20
157.36
154.15
123.21
113.07
110.45
113.57
122.44
114.93
111.85
126.04
121.34
124.36




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' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204644&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204644&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204644&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' @ yule.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5826824.87513e-06
20.4129953.45540.000469
30.4967594.15624.5e-05
40.4429353.70590.000209
50.3644813.04950.001618
60.3850753.22180.000967
70.2159651.80690.037538
80.2836142.37290.0102
90.1628161.36220.088748
10-0.000477-0.0040.498413
110.1369671.1460.127859
120.3407472.85090.002862
130.0943810.78960.216201
140.0072140.06040.476022
150.0582570.48740.313743
160.0883210.73890.231206
170.0440440.36850.356806
180.0694070.58070.281653
190.0213070.17830.429515
200.0559090.46780.320701
21-0.055762-0.46650.321141
22-0.146939-1.22940.111524
23-0.041818-0.34990.363741
240.0676710.56620.286542
25-0.064514-0.53980.295537
26-0.176651-1.4780.071951
27-0.106618-0.8920.187717
28-0.041976-0.35120.363247
29-0.110136-0.92150.179987
30-0.110552-0.92490.179087
31-0.081405-0.68110.249034
32-0.138838-1.16160.124671
33-0.178258-1.49140.070173
34-0.225487-1.88660.031684
35-0.213252-1.78420.039363
36-0.100021-0.83680.202766
37-0.176526-1.47690.072091
38-0.299958-2.50960.007201
39-0.196055-1.64030.052713
40-0.165978-1.38870.084668
41-0.21649-1.81130.037193
42-0.187297-1.5670.060807
43-0.160095-1.33950.092378
44-0.219902-1.83980.035017
45-0.21201-1.77380.040222
46-0.237641-1.98830.025348
47-0.218489-1.8280.035905
48-0.123066-1.02960.15336
49-0.189643-1.58670.058548
50-0.258755-2.16490.016903
51-0.157255-1.31570.096286
52-0.145708-1.21910.113453
53-0.160653-1.34410.091625
54-0.092936-0.77760.219725
55-0.084813-0.70960.240155
56-0.056187-0.47010.319875
57-0.007737-0.06470.474285
58-0.025023-0.20940.417387
590.0438560.36690.35739
600.1115110.9330.177021

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.582682 & 4.8751 & 3e-06 \tabularnewline
2 & 0.412995 & 3.4554 & 0.000469 \tabularnewline
3 & 0.496759 & 4.1562 & 4.5e-05 \tabularnewline
4 & 0.442935 & 3.7059 & 0.000209 \tabularnewline
5 & 0.364481 & 3.0495 & 0.001618 \tabularnewline
6 & 0.385075 & 3.2218 & 0.000967 \tabularnewline
7 & 0.215965 & 1.8069 & 0.037538 \tabularnewline
8 & 0.283614 & 2.3729 & 0.0102 \tabularnewline
9 & 0.162816 & 1.3622 & 0.088748 \tabularnewline
10 & -0.000477 & -0.004 & 0.498413 \tabularnewline
11 & 0.136967 & 1.146 & 0.127859 \tabularnewline
12 & 0.340747 & 2.8509 & 0.002862 \tabularnewline
13 & 0.094381 & 0.7896 & 0.216201 \tabularnewline
14 & 0.007214 & 0.0604 & 0.476022 \tabularnewline
15 & 0.058257 & 0.4874 & 0.313743 \tabularnewline
16 & 0.088321 & 0.7389 & 0.231206 \tabularnewline
17 & 0.044044 & 0.3685 & 0.356806 \tabularnewline
18 & 0.069407 & 0.5807 & 0.281653 \tabularnewline
19 & 0.021307 & 0.1783 & 0.429515 \tabularnewline
20 & 0.055909 & 0.4678 & 0.320701 \tabularnewline
21 & -0.055762 & -0.4665 & 0.321141 \tabularnewline
22 & -0.146939 & -1.2294 & 0.111524 \tabularnewline
23 & -0.041818 & -0.3499 & 0.363741 \tabularnewline
24 & 0.067671 & 0.5662 & 0.286542 \tabularnewline
25 & -0.064514 & -0.5398 & 0.295537 \tabularnewline
26 & -0.176651 & -1.478 & 0.071951 \tabularnewline
27 & -0.106618 & -0.892 & 0.187717 \tabularnewline
28 & -0.041976 & -0.3512 & 0.363247 \tabularnewline
29 & -0.110136 & -0.9215 & 0.179987 \tabularnewline
30 & -0.110552 & -0.9249 & 0.179087 \tabularnewline
31 & -0.081405 & -0.6811 & 0.249034 \tabularnewline
32 & -0.138838 & -1.1616 & 0.124671 \tabularnewline
33 & -0.178258 & -1.4914 & 0.070173 \tabularnewline
34 & -0.225487 & -1.8866 & 0.031684 \tabularnewline
35 & -0.213252 & -1.7842 & 0.039363 \tabularnewline
36 & -0.100021 & -0.8368 & 0.202766 \tabularnewline
37 & -0.176526 & -1.4769 & 0.072091 \tabularnewline
38 & -0.299958 & -2.5096 & 0.007201 \tabularnewline
39 & -0.196055 & -1.6403 & 0.052713 \tabularnewline
40 & -0.165978 & -1.3887 & 0.084668 \tabularnewline
41 & -0.21649 & -1.8113 & 0.037193 \tabularnewline
42 & -0.187297 & -1.567 & 0.060807 \tabularnewline
43 & -0.160095 & -1.3395 & 0.092378 \tabularnewline
44 & -0.219902 & -1.8398 & 0.035017 \tabularnewline
45 & -0.21201 & -1.7738 & 0.040222 \tabularnewline
46 & -0.237641 & -1.9883 & 0.025348 \tabularnewline
47 & -0.218489 & -1.828 & 0.035905 \tabularnewline
48 & -0.123066 & -1.0296 & 0.15336 \tabularnewline
49 & -0.189643 & -1.5867 & 0.058548 \tabularnewline
50 & -0.258755 & -2.1649 & 0.016903 \tabularnewline
51 & -0.157255 & -1.3157 & 0.096286 \tabularnewline
52 & -0.145708 & -1.2191 & 0.113453 \tabularnewline
53 & -0.160653 & -1.3441 & 0.091625 \tabularnewline
54 & -0.092936 & -0.7776 & 0.219725 \tabularnewline
55 & -0.084813 & -0.7096 & 0.240155 \tabularnewline
56 & -0.056187 & -0.4701 & 0.319875 \tabularnewline
57 & -0.007737 & -0.0647 & 0.474285 \tabularnewline
58 & -0.025023 & -0.2094 & 0.417387 \tabularnewline
59 & 0.043856 & 0.3669 & 0.35739 \tabularnewline
60 & 0.111511 & 0.933 & 0.177021 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204644&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]0.582682[/C][C]4.8751[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.412995[/C][C]3.4554[/C][C]0.000469[/C][/ROW]
[ROW][C]3[/C][C]0.496759[/C][C]4.1562[/C][C]4.5e-05[/C][/ROW]
[ROW][C]4[/C][C]0.442935[/C][C]3.7059[/C][C]0.000209[/C][/ROW]
[ROW][C]5[/C][C]0.364481[/C][C]3.0495[/C][C]0.001618[/C][/ROW]
[ROW][C]6[/C][C]0.385075[/C][C]3.2218[/C][C]0.000967[/C][/ROW]
[ROW][C]7[/C][C]0.215965[/C][C]1.8069[/C][C]0.037538[/C][/ROW]
[ROW][C]8[/C][C]0.283614[/C][C]2.3729[/C][C]0.0102[/C][/ROW]
[ROW][C]9[/C][C]0.162816[/C][C]1.3622[/C][C]0.088748[/C][/ROW]
[ROW][C]10[/C][C]-0.000477[/C][C]-0.004[/C][C]0.498413[/C][/ROW]
[ROW][C]11[/C][C]0.136967[/C][C]1.146[/C][C]0.127859[/C][/ROW]
[ROW][C]12[/C][C]0.340747[/C][C]2.8509[/C][C]0.002862[/C][/ROW]
[ROW][C]13[/C][C]0.094381[/C][C]0.7896[/C][C]0.216201[/C][/ROW]
[ROW][C]14[/C][C]0.007214[/C][C]0.0604[/C][C]0.476022[/C][/ROW]
[ROW][C]15[/C][C]0.058257[/C][C]0.4874[/C][C]0.313743[/C][/ROW]
[ROW][C]16[/C][C]0.088321[/C][C]0.7389[/C][C]0.231206[/C][/ROW]
[ROW][C]17[/C][C]0.044044[/C][C]0.3685[/C][C]0.356806[/C][/ROW]
[ROW][C]18[/C][C]0.069407[/C][C]0.5807[/C][C]0.281653[/C][/ROW]
[ROW][C]19[/C][C]0.021307[/C][C]0.1783[/C][C]0.429515[/C][/ROW]
[ROW][C]20[/C][C]0.055909[/C][C]0.4678[/C][C]0.320701[/C][/ROW]
[ROW][C]21[/C][C]-0.055762[/C][C]-0.4665[/C][C]0.321141[/C][/ROW]
[ROW][C]22[/C][C]-0.146939[/C][C]-1.2294[/C][C]0.111524[/C][/ROW]
[ROW][C]23[/C][C]-0.041818[/C][C]-0.3499[/C][C]0.363741[/C][/ROW]
[ROW][C]24[/C][C]0.067671[/C][C]0.5662[/C][C]0.286542[/C][/ROW]
[ROW][C]25[/C][C]-0.064514[/C][C]-0.5398[/C][C]0.295537[/C][/ROW]
[ROW][C]26[/C][C]-0.176651[/C][C]-1.478[/C][C]0.071951[/C][/ROW]
[ROW][C]27[/C][C]-0.106618[/C][C]-0.892[/C][C]0.187717[/C][/ROW]
[ROW][C]28[/C][C]-0.041976[/C][C]-0.3512[/C][C]0.363247[/C][/ROW]
[ROW][C]29[/C][C]-0.110136[/C][C]-0.9215[/C][C]0.179987[/C][/ROW]
[ROW][C]30[/C][C]-0.110552[/C][C]-0.9249[/C][C]0.179087[/C][/ROW]
[ROW][C]31[/C][C]-0.081405[/C][C]-0.6811[/C][C]0.249034[/C][/ROW]
[ROW][C]32[/C][C]-0.138838[/C][C]-1.1616[/C][C]0.124671[/C][/ROW]
[ROW][C]33[/C][C]-0.178258[/C][C]-1.4914[/C][C]0.070173[/C][/ROW]
[ROW][C]34[/C][C]-0.225487[/C][C]-1.8866[/C][C]0.031684[/C][/ROW]
[ROW][C]35[/C][C]-0.213252[/C][C]-1.7842[/C][C]0.039363[/C][/ROW]
[ROW][C]36[/C][C]-0.100021[/C][C]-0.8368[/C][C]0.202766[/C][/ROW]
[ROW][C]37[/C][C]-0.176526[/C][C]-1.4769[/C][C]0.072091[/C][/ROW]
[ROW][C]38[/C][C]-0.299958[/C][C]-2.5096[/C][C]0.007201[/C][/ROW]
[ROW][C]39[/C][C]-0.196055[/C][C]-1.6403[/C][C]0.052713[/C][/ROW]
[ROW][C]40[/C][C]-0.165978[/C][C]-1.3887[/C][C]0.084668[/C][/ROW]
[ROW][C]41[/C][C]-0.21649[/C][C]-1.8113[/C][C]0.037193[/C][/ROW]
[ROW][C]42[/C][C]-0.187297[/C][C]-1.567[/C][C]0.060807[/C][/ROW]
[ROW][C]43[/C][C]-0.160095[/C][C]-1.3395[/C][C]0.092378[/C][/ROW]
[ROW][C]44[/C][C]-0.219902[/C][C]-1.8398[/C][C]0.035017[/C][/ROW]
[ROW][C]45[/C][C]-0.21201[/C][C]-1.7738[/C][C]0.040222[/C][/ROW]
[ROW][C]46[/C][C]-0.237641[/C][C]-1.9883[/C][C]0.025348[/C][/ROW]
[ROW][C]47[/C][C]-0.218489[/C][C]-1.828[/C][C]0.035905[/C][/ROW]
[ROW][C]48[/C][C]-0.123066[/C][C]-1.0296[/C][C]0.15336[/C][/ROW]
[ROW][C]49[/C][C]-0.189643[/C][C]-1.5867[/C][C]0.058548[/C][/ROW]
[ROW][C]50[/C][C]-0.258755[/C][C]-2.1649[/C][C]0.016903[/C][/ROW]
[ROW][C]51[/C][C]-0.157255[/C][C]-1.3157[/C][C]0.096286[/C][/ROW]
[ROW][C]52[/C][C]-0.145708[/C][C]-1.2191[/C][C]0.113453[/C][/ROW]
[ROW][C]53[/C][C]-0.160653[/C][C]-1.3441[/C][C]0.091625[/C][/ROW]
[ROW][C]54[/C][C]-0.092936[/C][C]-0.7776[/C][C]0.219725[/C][/ROW]
[ROW][C]55[/C][C]-0.084813[/C][C]-0.7096[/C][C]0.240155[/C][/ROW]
[ROW][C]56[/C][C]-0.056187[/C][C]-0.4701[/C][C]0.319875[/C][/ROW]
[ROW][C]57[/C][C]-0.007737[/C][C]-0.0647[/C][C]0.474285[/C][/ROW]
[ROW][C]58[/C][C]-0.025023[/C][C]-0.2094[/C][C]0.417387[/C][/ROW]
[ROW][C]59[/C][C]0.043856[/C][C]0.3669[/C][C]0.35739[/C][/ROW]
[ROW][C]60[/C][C]0.111511[/C][C]0.933[/C][C]0.177021[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204644&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204644&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
10.5826824.87513e-06
20.4129953.45540.000469
30.4967594.15624.5e-05
40.4429353.70590.000209
50.3644813.04950.001618
60.3850753.22180.000967
70.2159651.80690.037538
80.2836142.37290.0102
90.1628161.36220.088748
10-0.000477-0.0040.498413
110.1369671.1460.127859
120.3407472.85090.002862
130.0943810.78960.216201
140.0072140.06040.476022
150.0582570.48740.313743
160.0883210.73890.231206
170.0440440.36850.356806
180.0694070.58070.281653
190.0213070.17830.429515
200.0559090.46780.320701
21-0.055762-0.46650.321141
22-0.146939-1.22940.111524
23-0.041818-0.34990.363741
240.0676710.56620.286542
25-0.064514-0.53980.295537
26-0.176651-1.4780.071951
27-0.106618-0.8920.187717
28-0.041976-0.35120.363247
29-0.110136-0.92150.179987
30-0.110552-0.92490.179087
31-0.081405-0.68110.249034
32-0.138838-1.16160.124671
33-0.178258-1.49140.070173
34-0.225487-1.88660.031684
35-0.213252-1.78420.039363
36-0.100021-0.83680.202766
37-0.176526-1.47690.072091
38-0.299958-2.50960.007201
39-0.196055-1.64030.052713
40-0.165978-1.38870.084668
41-0.21649-1.81130.037193
42-0.187297-1.5670.060807
43-0.160095-1.33950.092378
44-0.219902-1.83980.035017
45-0.21201-1.77380.040222
46-0.237641-1.98830.025348
47-0.218489-1.8280.035905
48-0.123066-1.02960.15336
49-0.189643-1.58670.058548
50-0.258755-2.16490.016903
51-0.157255-1.31570.096286
52-0.145708-1.21910.113453
53-0.160653-1.34410.091625
54-0.092936-0.77760.219725
55-0.084813-0.70960.240155
56-0.056187-0.47010.319875
57-0.007737-0.06470.474285
58-0.025023-0.20940.417387
590.0438560.36690.35739
600.1115110.9330.177021







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5826824.87513e-06
20.1112470.93080.177588
30.3342962.79690.003328
40.0602720.50430.307828
50.0487880.40820.342191
60.0929340.77750.21973
7-0.233449-1.95320.027398
80.2137741.78860.039007
9-0.320262-2.67950.004592
10-0.08935-0.74760.228616
110.2051571.71650.045249
120.3479512.91120.002413
13-0.202539-1.69460.047302
14-0.171378-1.43390.078034
150.0276310.23120.408926
160.0478330.40020.345115
17-0.088355-0.73920.23112
180.0635770.53190.298232
190.0270680.22650.41075
20-0.115445-0.96590.168713
21-0.065993-0.55210.291307
220.0347890.29110.385932
230.033330.27890.390586
24-0.108773-0.91010.182957
250.0887540.74260.230115
26-0.15732-1.31620.096194
270.1089840.91180.182494
280.0214990.17990.428885
29-0.031803-0.26610.39548
30-0.087598-0.73290.233034
31-0.032743-0.27390.392467
32-0.132647-1.10980.135441
330.0398630.33350.369869
34-0.004979-0.04170.483446
35-0.117934-0.98670.163592
360.0224530.18790.425767
37-0.000157-0.00130.499476
380.0627290.52480.300681
39-0.087458-0.73170.233388
400.0193880.16220.435804
41-0.027109-0.22680.410616
42-0.073585-0.61570.270059
43-0.010461-0.08750.465253
44-0.050089-0.41910.338223
45-0.042941-0.35930.360238
46-0.005464-0.04570.481833
47-0.017519-0.14660.441945
480.0310450.25970.397914
49-0.094328-0.78920.216329
500.1000020.83670.202811
51-0.033217-0.27790.390948
52-0.036188-0.30280.381482
530.0551780.46170.32288
540.0211390.17690.430065
55-0.013422-0.11230.455455
560.0905530.75760.225611
570.0958170.80170.21273
58-0.049772-0.41640.339189
590.0355890.29780.383384
600.0240720.20140.420486

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.582682 & 4.8751 & 3e-06 \tabularnewline
2 & 0.111247 & 0.9308 & 0.177588 \tabularnewline
3 & 0.334296 & 2.7969 & 0.003328 \tabularnewline
4 & 0.060272 & 0.5043 & 0.307828 \tabularnewline
5 & 0.048788 & 0.4082 & 0.342191 \tabularnewline
6 & 0.092934 & 0.7775 & 0.21973 \tabularnewline
7 & -0.233449 & -1.9532 & 0.027398 \tabularnewline
8 & 0.213774 & 1.7886 & 0.039007 \tabularnewline
9 & -0.320262 & -2.6795 & 0.004592 \tabularnewline
10 & -0.08935 & -0.7476 & 0.228616 \tabularnewline
11 & 0.205157 & 1.7165 & 0.045249 \tabularnewline
12 & 0.347951 & 2.9112 & 0.002413 \tabularnewline
13 & -0.202539 & -1.6946 & 0.047302 \tabularnewline
14 & -0.171378 & -1.4339 & 0.078034 \tabularnewline
15 & 0.027631 & 0.2312 & 0.408926 \tabularnewline
16 & 0.047833 & 0.4002 & 0.345115 \tabularnewline
17 & -0.088355 & -0.7392 & 0.23112 \tabularnewline
18 & 0.063577 & 0.5319 & 0.298232 \tabularnewline
19 & 0.027068 & 0.2265 & 0.41075 \tabularnewline
20 & -0.115445 & -0.9659 & 0.168713 \tabularnewline
21 & -0.065993 & -0.5521 & 0.291307 \tabularnewline
22 & 0.034789 & 0.2911 & 0.385932 \tabularnewline
23 & 0.03333 & 0.2789 & 0.390586 \tabularnewline
24 & -0.108773 & -0.9101 & 0.182957 \tabularnewline
25 & 0.088754 & 0.7426 & 0.230115 \tabularnewline
26 & -0.15732 & -1.3162 & 0.096194 \tabularnewline
27 & 0.108984 & 0.9118 & 0.182494 \tabularnewline
28 & 0.021499 & 0.1799 & 0.428885 \tabularnewline
29 & -0.031803 & -0.2661 & 0.39548 \tabularnewline
30 & -0.087598 & -0.7329 & 0.233034 \tabularnewline
31 & -0.032743 & -0.2739 & 0.392467 \tabularnewline
32 & -0.132647 & -1.1098 & 0.135441 \tabularnewline
33 & 0.039863 & 0.3335 & 0.369869 \tabularnewline
34 & -0.004979 & -0.0417 & 0.483446 \tabularnewline
35 & -0.117934 & -0.9867 & 0.163592 \tabularnewline
36 & 0.022453 & 0.1879 & 0.425767 \tabularnewline
37 & -0.000157 & -0.0013 & 0.499476 \tabularnewline
38 & 0.062729 & 0.5248 & 0.300681 \tabularnewline
39 & -0.087458 & -0.7317 & 0.233388 \tabularnewline
40 & 0.019388 & 0.1622 & 0.435804 \tabularnewline
41 & -0.027109 & -0.2268 & 0.410616 \tabularnewline
42 & -0.073585 & -0.6157 & 0.270059 \tabularnewline
43 & -0.010461 & -0.0875 & 0.465253 \tabularnewline
44 & -0.050089 & -0.4191 & 0.338223 \tabularnewline
45 & -0.042941 & -0.3593 & 0.360238 \tabularnewline
46 & -0.005464 & -0.0457 & 0.481833 \tabularnewline
47 & -0.017519 & -0.1466 & 0.441945 \tabularnewline
48 & 0.031045 & 0.2597 & 0.397914 \tabularnewline
49 & -0.094328 & -0.7892 & 0.216329 \tabularnewline
50 & 0.100002 & 0.8367 & 0.202811 \tabularnewline
51 & -0.033217 & -0.2779 & 0.390948 \tabularnewline
52 & -0.036188 & -0.3028 & 0.381482 \tabularnewline
53 & 0.055178 & 0.4617 & 0.32288 \tabularnewline
54 & 0.021139 & 0.1769 & 0.430065 \tabularnewline
55 & -0.013422 & -0.1123 & 0.455455 \tabularnewline
56 & 0.090553 & 0.7576 & 0.225611 \tabularnewline
57 & 0.095817 & 0.8017 & 0.21273 \tabularnewline
58 & -0.049772 & -0.4164 & 0.339189 \tabularnewline
59 & 0.035589 & 0.2978 & 0.383384 \tabularnewline
60 & 0.024072 & 0.2014 & 0.420486 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204644&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]0.582682[/C][C]4.8751[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.111247[/C][C]0.9308[/C][C]0.177588[/C][/ROW]
[ROW][C]3[/C][C]0.334296[/C][C]2.7969[/C][C]0.003328[/C][/ROW]
[ROW][C]4[/C][C]0.060272[/C][C]0.5043[/C][C]0.307828[/C][/ROW]
[ROW][C]5[/C][C]0.048788[/C][C]0.4082[/C][C]0.342191[/C][/ROW]
[ROW][C]6[/C][C]0.092934[/C][C]0.7775[/C][C]0.21973[/C][/ROW]
[ROW][C]7[/C][C]-0.233449[/C][C]-1.9532[/C][C]0.027398[/C][/ROW]
[ROW][C]8[/C][C]0.213774[/C][C]1.7886[/C][C]0.039007[/C][/ROW]
[ROW][C]9[/C][C]-0.320262[/C][C]-2.6795[/C][C]0.004592[/C][/ROW]
[ROW][C]10[/C][C]-0.08935[/C][C]-0.7476[/C][C]0.228616[/C][/ROW]
[ROW][C]11[/C][C]0.205157[/C][C]1.7165[/C][C]0.045249[/C][/ROW]
[ROW][C]12[/C][C]0.347951[/C][C]2.9112[/C][C]0.002413[/C][/ROW]
[ROW][C]13[/C][C]-0.202539[/C][C]-1.6946[/C][C]0.047302[/C][/ROW]
[ROW][C]14[/C][C]-0.171378[/C][C]-1.4339[/C][C]0.078034[/C][/ROW]
[ROW][C]15[/C][C]0.027631[/C][C]0.2312[/C][C]0.408926[/C][/ROW]
[ROW][C]16[/C][C]0.047833[/C][C]0.4002[/C][C]0.345115[/C][/ROW]
[ROW][C]17[/C][C]-0.088355[/C][C]-0.7392[/C][C]0.23112[/C][/ROW]
[ROW][C]18[/C][C]0.063577[/C][C]0.5319[/C][C]0.298232[/C][/ROW]
[ROW][C]19[/C][C]0.027068[/C][C]0.2265[/C][C]0.41075[/C][/ROW]
[ROW][C]20[/C][C]-0.115445[/C][C]-0.9659[/C][C]0.168713[/C][/ROW]
[ROW][C]21[/C][C]-0.065993[/C][C]-0.5521[/C][C]0.291307[/C][/ROW]
[ROW][C]22[/C][C]0.034789[/C][C]0.2911[/C][C]0.385932[/C][/ROW]
[ROW][C]23[/C][C]0.03333[/C][C]0.2789[/C][C]0.390586[/C][/ROW]
[ROW][C]24[/C][C]-0.108773[/C][C]-0.9101[/C][C]0.182957[/C][/ROW]
[ROW][C]25[/C][C]0.088754[/C][C]0.7426[/C][C]0.230115[/C][/ROW]
[ROW][C]26[/C][C]-0.15732[/C][C]-1.3162[/C][C]0.096194[/C][/ROW]
[ROW][C]27[/C][C]0.108984[/C][C]0.9118[/C][C]0.182494[/C][/ROW]
[ROW][C]28[/C][C]0.021499[/C][C]0.1799[/C][C]0.428885[/C][/ROW]
[ROW][C]29[/C][C]-0.031803[/C][C]-0.2661[/C][C]0.39548[/C][/ROW]
[ROW][C]30[/C][C]-0.087598[/C][C]-0.7329[/C][C]0.233034[/C][/ROW]
[ROW][C]31[/C][C]-0.032743[/C][C]-0.2739[/C][C]0.392467[/C][/ROW]
[ROW][C]32[/C][C]-0.132647[/C][C]-1.1098[/C][C]0.135441[/C][/ROW]
[ROW][C]33[/C][C]0.039863[/C][C]0.3335[/C][C]0.369869[/C][/ROW]
[ROW][C]34[/C][C]-0.004979[/C][C]-0.0417[/C][C]0.483446[/C][/ROW]
[ROW][C]35[/C][C]-0.117934[/C][C]-0.9867[/C][C]0.163592[/C][/ROW]
[ROW][C]36[/C][C]0.022453[/C][C]0.1879[/C][C]0.425767[/C][/ROW]
[ROW][C]37[/C][C]-0.000157[/C][C]-0.0013[/C][C]0.499476[/C][/ROW]
[ROW][C]38[/C][C]0.062729[/C][C]0.5248[/C][C]0.300681[/C][/ROW]
[ROW][C]39[/C][C]-0.087458[/C][C]-0.7317[/C][C]0.233388[/C][/ROW]
[ROW][C]40[/C][C]0.019388[/C][C]0.1622[/C][C]0.435804[/C][/ROW]
[ROW][C]41[/C][C]-0.027109[/C][C]-0.2268[/C][C]0.410616[/C][/ROW]
[ROW][C]42[/C][C]-0.073585[/C][C]-0.6157[/C][C]0.270059[/C][/ROW]
[ROW][C]43[/C][C]-0.010461[/C][C]-0.0875[/C][C]0.465253[/C][/ROW]
[ROW][C]44[/C][C]-0.050089[/C][C]-0.4191[/C][C]0.338223[/C][/ROW]
[ROW][C]45[/C][C]-0.042941[/C][C]-0.3593[/C][C]0.360238[/C][/ROW]
[ROW][C]46[/C][C]-0.005464[/C][C]-0.0457[/C][C]0.481833[/C][/ROW]
[ROW][C]47[/C][C]-0.017519[/C][C]-0.1466[/C][C]0.441945[/C][/ROW]
[ROW][C]48[/C][C]0.031045[/C][C]0.2597[/C][C]0.397914[/C][/ROW]
[ROW][C]49[/C][C]-0.094328[/C][C]-0.7892[/C][C]0.216329[/C][/ROW]
[ROW][C]50[/C][C]0.100002[/C][C]0.8367[/C][C]0.202811[/C][/ROW]
[ROW][C]51[/C][C]-0.033217[/C][C]-0.2779[/C][C]0.390948[/C][/ROW]
[ROW][C]52[/C][C]-0.036188[/C][C]-0.3028[/C][C]0.381482[/C][/ROW]
[ROW][C]53[/C][C]0.055178[/C][C]0.4617[/C][C]0.32288[/C][/ROW]
[ROW][C]54[/C][C]0.021139[/C][C]0.1769[/C][C]0.430065[/C][/ROW]
[ROW][C]55[/C][C]-0.013422[/C][C]-0.1123[/C][C]0.455455[/C][/ROW]
[ROW][C]56[/C][C]0.090553[/C][C]0.7576[/C][C]0.225611[/C][/ROW]
[ROW][C]57[/C][C]0.095817[/C][C]0.8017[/C][C]0.21273[/C][/ROW]
[ROW][C]58[/C][C]-0.049772[/C][C]-0.4164[/C][C]0.339189[/C][/ROW]
[ROW][C]59[/C][C]0.035589[/C][C]0.2978[/C][C]0.383384[/C][/ROW]
[ROW][C]60[/C][C]0.024072[/C][C]0.2014[/C][C]0.420486[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204644&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204644&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
10.5826824.87513e-06
20.1112470.93080.177588
30.3342962.79690.003328
40.0602720.50430.307828
50.0487880.40820.342191
60.0929340.77750.21973
7-0.233449-1.95320.027398
80.2137741.78860.039007
9-0.320262-2.67950.004592
10-0.08935-0.74760.228616
110.2051571.71650.045249
120.3479512.91120.002413
13-0.202539-1.69460.047302
14-0.171378-1.43390.078034
150.0276310.23120.408926
160.0478330.40020.345115
17-0.088355-0.73920.23112
180.0635770.53190.298232
190.0270680.22650.41075
20-0.115445-0.96590.168713
21-0.065993-0.55210.291307
220.0347890.29110.385932
230.033330.27890.390586
24-0.108773-0.91010.182957
250.0887540.74260.230115
26-0.15732-1.31620.096194
270.1089840.91180.182494
280.0214990.17990.428885
29-0.031803-0.26610.39548
30-0.087598-0.73290.233034
31-0.032743-0.27390.392467
32-0.132647-1.10980.135441
330.0398630.33350.369869
34-0.004979-0.04170.483446
35-0.117934-0.98670.163592
360.0224530.18790.425767
37-0.000157-0.00130.499476
380.0627290.52480.300681
39-0.087458-0.73170.233388
400.0193880.16220.435804
41-0.027109-0.22680.410616
42-0.073585-0.61570.270059
43-0.010461-0.08750.465253
44-0.050089-0.41910.338223
45-0.042941-0.35930.360238
46-0.005464-0.04570.481833
47-0.017519-0.14660.441945
480.0310450.25970.397914
49-0.094328-0.78920.216329
500.1000020.83670.202811
51-0.033217-0.27790.390948
52-0.036188-0.30280.381482
530.0551780.46170.32288
540.0211390.17690.430065
55-0.013422-0.11230.455455
560.0905530.75760.225611
570.0958170.80170.21273
58-0.049772-0.41640.339189
590.0355890.29780.383384
600.0240720.20140.420486



Parameters (Session):
par1 = 50 ; par2 = 36 ;
Parameters (R input):
par1 = 60 ; par2 = 0.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (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')