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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 16 Dec 2010 14:55:48 +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/16/t1292511209rn7sq08f8kq94p1.htm/, Retrieved Fri, 03 May 2024 04:42:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110985, Retrieved Fri, 03 May 2024 04:42:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [acf methode] [2009-11-25 20:17:41] [21324e9cdf3569788a3d630236984d87]
-   P   [(Partial) Autocorrelation Function] [acf methode] [2009-11-30 18:54:14] [21324e9cdf3569788a3d630236984d87]
-    D      [(Partial) Autocorrelation Function] [] [2010-12-16 14:55:48] [1d208f56d63f78e3037c4c685f0bba30] [Current]
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Dataseries X:
112,3
117,3
111,1
102,2
104,3
122,9
107,6
121,3
131,5
89
104,4
128,9
135,9
133,3
121,3
120,5
120,4
137,9
126,1
133,2
151,1
105
119
140,4
156,6
137,1
122,7
125,8
139,3
134,9
149,2
132,3
149
117,2
119,6
152
149,4
127,3
114,1
102,1
107,7
104,4
102,1
96
109,3
90
83,9
112
114,3
103,6
91,7
80,8
87,2
109,2
102,7
95,1
117,5
85,1
92,1
113,5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110985&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110985&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110985&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8322195.76580
20.8212415.68970
30.7643575.29561e-06
40.6671864.62241.4e-05
50.6050914.19225.9e-05
60.4892993.390.000703
70.3781552.61990.00587
80.3119452.16120.017849
90.1903181.31860.096787
100.1303360.9030.185519
110.0362050.25080.401506
12-0.041596-0.28820.387224
13-0.090314-0.62570.267234
14-0.161797-1.1210.13394
15-0.135224-0.93690.176761
16-0.198754-1.3770.087449
17-0.223266-1.54680.064236
18-0.219452-1.52040.067485
19-0.275388-1.90790.031195
20-0.270189-1.87190.033659
21-0.269441-1.86670.034026
22-0.323745-2.2430.014776
23-0.294608-2.04110.02338
24-0.365013-2.52890.007392
25-0.337585-2.33890.011777
26-0.342974-2.37620.010765
27-0.379845-2.63160.005696
28-0.338505-2.34520.011598
29-0.320671-2.22170.015527
30-0.297508-2.06120.022362
31-0.253231-1.75440.042869
32-0.215418-1.49250.071062
33-0.172861-1.19760.118473
34-0.144792-1.00310.16041
35-0.113883-0.7890.216994
36-0.07554-0.52340.301567
37-0.041771-0.28940.38676
38-0.010996-0.07620.469796
39-0.005728-0.03970.484254
400.0168140.11650.453874
410.0451750.3130.377826
420.0307370.2130.416132
430.0319310.22120.412929
440.0282840.1960.422736
450.0128710.08920.464657
460.0211260.14640.442124
470.0068060.04720.481294
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.832219 & 5.7658 & 0 \tabularnewline
2 & 0.821241 & 5.6897 & 0 \tabularnewline
3 & 0.764357 & 5.2956 & 1e-06 \tabularnewline
4 & 0.667186 & 4.6224 & 1.4e-05 \tabularnewline
5 & 0.605091 & 4.1922 & 5.9e-05 \tabularnewline
6 & 0.489299 & 3.39 & 0.000703 \tabularnewline
7 & 0.378155 & 2.6199 & 0.00587 \tabularnewline
8 & 0.311945 & 2.1612 & 0.017849 \tabularnewline
9 & 0.190318 & 1.3186 & 0.096787 \tabularnewline
10 & 0.130336 & 0.903 & 0.185519 \tabularnewline
11 & 0.036205 & 0.2508 & 0.401506 \tabularnewline
12 & -0.041596 & -0.2882 & 0.387224 \tabularnewline
13 & -0.090314 & -0.6257 & 0.267234 \tabularnewline
14 & -0.161797 & -1.121 & 0.13394 \tabularnewline
15 & -0.135224 & -0.9369 & 0.176761 \tabularnewline
16 & -0.198754 & -1.377 & 0.087449 \tabularnewline
17 & -0.223266 & -1.5468 & 0.064236 \tabularnewline
18 & -0.219452 & -1.5204 & 0.067485 \tabularnewline
19 & -0.275388 & -1.9079 & 0.031195 \tabularnewline
20 & -0.270189 & -1.8719 & 0.033659 \tabularnewline
21 & -0.269441 & -1.8667 & 0.034026 \tabularnewline
22 & -0.323745 & -2.243 & 0.014776 \tabularnewline
23 & -0.294608 & -2.0411 & 0.02338 \tabularnewline
24 & -0.365013 & -2.5289 & 0.007392 \tabularnewline
25 & -0.337585 & -2.3389 & 0.011777 \tabularnewline
26 & -0.342974 & -2.3762 & 0.010765 \tabularnewline
27 & -0.379845 & -2.6316 & 0.005696 \tabularnewline
28 & -0.338505 & -2.3452 & 0.011598 \tabularnewline
29 & -0.320671 & -2.2217 & 0.015527 \tabularnewline
30 & -0.297508 & -2.0612 & 0.022362 \tabularnewline
31 & -0.253231 & -1.7544 & 0.042869 \tabularnewline
32 & -0.215418 & -1.4925 & 0.071062 \tabularnewline
33 & -0.172861 & -1.1976 & 0.118473 \tabularnewline
34 & -0.144792 & -1.0031 & 0.16041 \tabularnewline
35 & -0.113883 & -0.789 & 0.216994 \tabularnewline
36 & -0.07554 & -0.5234 & 0.301567 \tabularnewline
37 & -0.041771 & -0.2894 & 0.38676 \tabularnewline
38 & -0.010996 & -0.0762 & 0.469796 \tabularnewline
39 & -0.005728 & -0.0397 & 0.484254 \tabularnewline
40 & 0.016814 & 0.1165 & 0.453874 \tabularnewline
41 & 0.045175 & 0.313 & 0.377826 \tabularnewline
42 & 0.030737 & 0.213 & 0.416132 \tabularnewline
43 & 0.031931 & 0.2212 & 0.412929 \tabularnewline
44 & 0.028284 & 0.196 & 0.422736 \tabularnewline
45 & 0.012871 & 0.0892 & 0.464657 \tabularnewline
46 & 0.021126 & 0.1464 & 0.442124 \tabularnewline
47 & 0.006806 & 0.0472 & 0.481294 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110985&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]0.832219[/C][C]5.7658[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.821241[/C][C]5.6897[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.764357[/C][C]5.2956[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.667186[/C][C]4.6224[/C][C]1.4e-05[/C][/ROW]
[ROW][C]5[/C][C]0.605091[/C][C]4.1922[/C][C]5.9e-05[/C][/ROW]
[ROW][C]6[/C][C]0.489299[/C][C]3.39[/C][C]0.000703[/C][/ROW]
[ROW][C]7[/C][C]0.378155[/C][C]2.6199[/C][C]0.00587[/C][/ROW]
[ROW][C]8[/C][C]0.311945[/C][C]2.1612[/C][C]0.017849[/C][/ROW]
[ROW][C]9[/C][C]0.190318[/C][C]1.3186[/C][C]0.096787[/C][/ROW]
[ROW][C]10[/C][C]0.130336[/C][C]0.903[/C][C]0.185519[/C][/ROW]
[ROW][C]11[/C][C]0.036205[/C][C]0.2508[/C][C]0.401506[/C][/ROW]
[ROW][C]12[/C][C]-0.041596[/C][C]-0.2882[/C][C]0.387224[/C][/ROW]
[ROW][C]13[/C][C]-0.090314[/C][C]-0.6257[/C][C]0.267234[/C][/ROW]
[ROW][C]14[/C][C]-0.161797[/C][C]-1.121[/C][C]0.13394[/C][/ROW]
[ROW][C]15[/C][C]-0.135224[/C][C]-0.9369[/C][C]0.176761[/C][/ROW]
[ROW][C]16[/C][C]-0.198754[/C][C]-1.377[/C][C]0.087449[/C][/ROW]
[ROW][C]17[/C][C]-0.223266[/C][C]-1.5468[/C][C]0.064236[/C][/ROW]
[ROW][C]18[/C][C]-0.219452[/C][C]-1.5204[/C][C]0.067485[/C][/ROW]
[ROW][C]19[/C][C]-0.275388[/C][C]-1.9079[/C][C]0.031195[/C][/ROW]
[ROW][C]20[/C][C]-0.270189[/C][C]-1.8719[/C][C]0.033659[/C][/ROW]
[ROW][C]21[/C][C]-0.269441[/C][C]-1.8667[/C][C]0.034026[/C][/ROW]
[ROW][C]22[/C][C]-0.323745[/C][C]-2.243[/C][C]0.014776[/C][/ROW]
[ROW][C]23[/C][C]-0.294608[/C][C]-2.0411[/C][C]0.02338[/C][/ROW]
[ROW][C]24[/C][C]-0.365013[/C][C]-2.5289[/C][C]0.007392[/C][/ROW]
[ROW][C]25[/C][C]-0.337585[/C][C]-2.3389[/C][C]0.011777[/C][/ROW]
[ROW][C]26[/C][C]-0.342974[/C][C]-2.3762[/C][C]0.010765[/C][/ROW]
[ROW][C]27[/C][C]-0.379845[/C][C]-2.6316[/C][C]0.005696[/C][/ROW]
[ROW][C]28[/C][C]-0.338505[/C][C]-2.3452[/C][C]0.011598[/C][/ROW]
[ROW][C]29[/C][C]-0.320671[/C][C]-2.2217[/C][C]0.015527[/C][/ROW]
[ROW][C]30[/C][C]-0.297508[/C][C]-2.0612[/C][C]0.022362[/C][/ROW]
[ROW][C]31[/C][C]-0.253231[/C][C]-1.7544[/C][C]0.042869[/C][/ROW]
[ROW][C]32[/C][C]-0.215418[/C][C]-1.4925[/C][C]0.071062[/C][/ROW]
[ROW][C]33[/C][C]-0.172861[/C][C]-1.1976[/C][C]0.118473[/C][/ROW]
[ROW][C]34[/C][C]-0.144792[/C][C]-1.0031[/C][C]0.16041[/C][/ROW]
[ROW][C]35[/C][C]-0.113883[/C][C]-0.789[/C][C]0.216994[/C][/ROW]
[ROW][C]36[/C][C]-0.07554[/C][C]-0.5234[/C][C]0.301567[/C][/ROW]
[ROW][C]37[/C][C]-0.041771[/C][C]-0.2894[/C][C]0.38676[/C][/ROW]
[ROW][C]38[/C][C]-0.010996[/C][C]-0.0762[/C][C]0.469796[/C][/ROW]
[ROW][C]39[/C][C]-0.005728[/C][C]-0.0397[/C][C]0.484254[/C][/ROW]
[ROW][C]40[/C][C]0.016814[/C][C]0.1165[/C][C]0.453874[/C][/ROW]
[ROW][C]41[/C][C]0.045175[/C][C]0.313[/C][C]0.377826[/C][/ROW]
[ROW][C]42[/C][C]0.030737[/C][C]0.213[/C][C]0.416132[/C][/ROW]
[ROW][C]43[/C][C]0.031931[/C][C]0.2212[/C][C]0.412929[/C][/ROW]
[ROW][C]44[/C][C]0.028284[/C][C]0.196[/C][C]0.422736[/C][/ROW]
[ROW][C]45[/C][C]0.012871[/C][C]0.0892[/C][C]0.464657[/C][/ROW]
[ROW][C]46[/C][C]0.021126[/C][C]0.1464[/C][C]0.442124[/C][/ROW]
[ROW][C]47[/C][C]0.006806[/C][C]0.0472[/C][C]0.481294[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110985&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110985&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
10.8322195.76580
20.8212415.68970
30.7643575.29561e-06
40.6671864.62241.4e-05
50.6050914.19225.9e-05
60.4892993.390.000703
70.3781552.61990.00587
80.3119452.16120.017849
90.1903181.31860.096787
100.1303360.9030.185519
110.0362050.25080.401506
12-0.041596-0.28820.387224
13-0.090314-0.62570.267234
14-0.161797-1.1210.13394
15-0.135224-0.93690.176761
16-0.198754-1.3770.087449
17-0.223266-1.54680.064236
18-0.219452-1.52040.067485
19-0.275388-1.90790.031195
20-0.270189-1.87190.033659
21-0.269441-1.86670.034026
22-0.323745-2.2430.014776
23-0.294608-2.04110.02338
24-0.365013-2.52890.007392
25-0.337585-2.33890.011777
26-0.342974-2.37620.010765
27-0.379845-2.63160.005696
28-0.338505-2.34520.011598
29-0.320671-2.22170.015527
30-0.297508-2.06120.022362
31-0.253231-1.75440.042869
32-0.215418-1.49250.071062
33-0.172861-1.19760.118473
34-0.144792-1.00310.16041
35-0.113883-0.7890.216994
36-0.07554-0.52340.301567
37-0.041771-0.28940.38676
38-0.010996-0.07620.469796
39-0.005728-0.03970.484254
400.0168140.11650.453874
410.0451750.3130.377826
420.0307370.2130.416132
430.0319310.22120.412929
440.0282840.1960.422736
450.0128710.08920.464657
460.0211260.14640.442124
470.0068060.04720.481294
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8322195.76580
20.4185032.89950.002811
30.0735330.50950.306386
4-0.217495-1.50690.069201
5-0.102344-0.70910.24086
6-0.200034-1.38590.086095
7-0.201713-1.39750.084343
80.0520540.36060.359975
9-0.059438-0.41180.34116
100.0652810.45230.326551
11-0.044458-0.3080.379702
12-0.044591-0.30890.379353
13-0.007927-0.05490.478214
14-0.051383-0.3560.361704
150.2951492.04490.023187
16-0.091059-0.63090.265557
17-0.131881-0.91370.18272
18-0.07344-0.50880.306609
19-0.208539-1.44480.077505
20-0.07589-0.52580.300731
210.1027990.71220.23989
22-0.053046-0.36750.357425
230.0121830.08440.466541
24-0.229079-1.58710.059527
250.0545390.37790.353601
260.0252940.17520.430812
27-0.026448-0.18320.427693
280.1910521.32360.095945
290.2094021.45080.076673
30-0.054725-0.37910.353125
31-0.156047-1.08110.142522
320.0521970.36160.359607
33-0.160238-1.11020.136231
34-0.081881-0.56730.286581
350.0248630.17230.43198
36-0.125439-0.86910.194567
370.0725820.50290.30868
38-0.090636-0.62790.266508
390.0254430.17630.43041
400.0180540.12510.450489
410.0948830.65740.257043
420.1524571.05630.14807
43-0.134482-0.93170.178072
44-0.144479-1.0010.160928
450.0147460.10220.459527
46-0.072212-0.50030.309575
47-0.073612-0.510.306194
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.832219 & 5.7658 & 0 \tabularnewline
2 & 0.418503 & 2.8995 & 0.002811 \tabularnewline
3 & 0.073533 & 0.5095 & 0.306386 \tabularnewline
4 & -0.217495 & -1.5069 & 0.069201 \tabularnewline
5 & -0.102344 & -0.7091 & 0.24086 \tabularnewline
6 & -0.200034 & -1.3859 & 0.086095 \tabularnewline
7 & -0.201713 & -1.3975 & 0.084343 \tabularnewline
8 & 0.052054 & 0.3606 & 0.359975 \tabularnewline
9 & -0.059438 & -0.4118 & 0.34116 \tabularnewline
10 & 0.065281 & 0.4523 & 0.326551 \tabularnewline
11 & -0.044458 & -0.308 & 0.379702 \tabularnewline
12 & -0.044591 & -0.3089 & 0.379353 \tabularnewline
13 & -0.007927 & -0.0549 & 0.478214 \tabularnewline
14 & -0.051383 & -0.356 & 0.361704 \tabularnewline
15 & 0.295149 & 2.0449 & 0.023187 \tabularnewline
16 & -0.091059 & -0.6309 & 0.265557 \tabularnewline
17 & -0.131881 & -0.9137 & 0.18272 \tabularnewline
18 & -0.07344 & -0.5088 & 0.306609 \tabularnewline
19 & -0.208539 & -1.4448 & 0.077505 \tabularnewline
20 & -0.07589 & -0.5258 & 0.300731 \tabularnewline
21 & 0.102799 & 0.7122 & 0.23989 \tabularnewline
22 & -0.053046 & -0.3675 & 0.357425 \tabularnewline
23 & 0.012183 & 0.0844 & 0.466541 \tabularnewline
24 & -0.229079 & -1.5871 & 0.059527 \tabularnewline
25 & 0.054539 & 0.3779 & 0.353601 \tabularnewline
26 & 0.025294 & 0.1752 & 0.430812 \tabularnewline
27 & -0.026448 & -0.1832 & 0.427693 \tabularnewline
28 & 0.191052 & 1.3236 & 0.095945 \tabularnewline
29 & 0.209402 & 1.4508 & 0.076673 \tabularnewline
30 & -0.054725 & -0.3791 & 0.353125 \tabularnewline
31 & -0.156047 & -1.0811 & 0.142522 \tabularnewline
32 & 0.052197 & 0.3616 & 0.359607 \tabularnewline
33 & -0.160238 & -1.1102 & 0.136231 \tabularnewline
34 & -0.081881 & -0.5673 & 0.286581 \tabularnewline
35 & 0.024863 & 0.1723 & 0.43198 \tabularnewline
36 & -0.125439 & -0.8691 & 0.194567 \tabularnewline
37 & 0.072582 & 0.5029 & 0.30868 \tabularnewline
38 & -0.090636 & -0.6279 & 0.266508 \tabularnewline
39 & 0.025443 & 0.1763 & 0.43041 \tabularnewline
40 & 0.018054 & 0.1251 & 0.450489 \tabularnewline
41 & 0.094883 & 0.6574 & 0.257043 \tabularnewline
42 & 0.152457 & 1.0563 & 0.14807 \tabularnewline
43 & -0.134482 & -0.9317 & 0.178072 \tabularnewline
44 & -0.144479 & -1.001 & 0.160928 \tabularnewline
45 & 0.014746 & 0.1022 & 0.459527 \tabularnewline
46 & -0.072212 & -0.5003 & 0.309575 \tabularnewline
47 & -0.073612 & -0.51 & 0.306194 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110985&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]0.832219[/C][C]5.7658[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.418503[/C][C]2.8995[/C][C]0.002811[/C][/ROW]
[ROW][C]3[/C][C]0.073533[/C][C]0.5095[/C][C]0.306386[/C][/ROW]
[ROW][C]4[/C][C]-0.217495[/C][C]-1.5069[/C][C]0.069201[/C][/ROW]
[ROW][C]5[/C][C]-0.102344[/C][C]-0.7091[/C][C]0.24086[/C][/ROW]
[ROW][C]6[/C][C]-0.200034[/C][C]-1.3859[/C][C]0.086095[/C][/ROW]
[ROW][C]7[/C][C]-0.201713[/C][C]-1.3975[/C][C]0.084343[/C][/ROW]
[ROW][C]8[/C][C]0.052054[/C][C]0.3606[/C][C]0.359975[/C][/ROW]
[ROW][C]9[/C][C]-0.059438[/C][C]-0.4118[/C][C]0.34116[/C][/ROW]
[ROW][C]10[/C][C]0.065281[/C][C]0.4523[/C][C]0.326551[/C][/ROW]
[ROW][C]11[/C][C]-0.044458[/C][C]-0.308[/C][C]0.379702[/C][/ROW]
[ROW][C]12[/C][C]-0.044591[/C][C]-0.3089[/C][C]0.379353[/C][/ROW]
[ROW][C]13[/C][C]-0.007927[/C][C]-0.0549[/C][C]0.478214[/C][/ROW]
[ROW][C]14[/C][C]-0.051383[/C][C]-0.356[/C][C]0.361704[/C][/ROW]
[ROW][C]15[/C][C]0.295149[/C][C]2.0449[/C][C]0.023187[/C][/ROW]
[ROW][C]16[/C][C]-0.091059[/C][C]-0.6309[/C][C]0.265557[/C][/ROW]
[ROW][C]17[/C][C]-0.131881[/C][C]-0.9137[/C][C]0.18272[/C][/ROW]
[ROW][C]18[/C][C]-0.07344[/C][C]-0.5088[/C][C]0.306609[/C][/ROW]
[ROW][C]19[/C][C]-0.208539[/C][C]-1.4448[/C][C]0.077505[/C][/ROW]
[ROW][C]20[/C][C]-0.07589[/C][C]-0.5258[/C][C]0.300731[/C][/ROW]
[ROW][C]21[/C][C]0.102799[/C][C]0.7122[/C][C]0.23989[/C][/ROW]
[ROW][C]22[/C][C]-0.053046[/C][C]-0.3675[/C][C]0.357425[/C][/ROW]
[ROW][C]23[/C][C]0.012183[/C][C]0.0844[/C][C]0.466541[/C][/ROW]
[ROW][C]24[/C][C]-0.229079[/C][C]-1.5871[/C][C]0.059527[/C][/ROW]
[ROW][C]25[/C][C]0.054539[/C][C]0.3779[/C][C]0.353601[/C][/ROW]
[ROW][C]26[/C][C]0.025294[/C][C]0.1752[/C][C]0.430812[/C][/ROW]
[ROW][C]27[/C][C]-0.026448[/C][C]-0.1832[/C][C]0.427693[/C][/ROW]
[ROW][C]28[/C][C]0.191052[/C][C]1.3236[/C][C]0.095945[/C][/ROW]
[ROW][C]29[/C][C]0.209402[/C][C]1.4508[/C][C]0.076673[/C][/ROW]
[ROW][C]30[/C][C]-0.054725[/C][C]-0.3791[/C][C]0.353125[/C][/ROW]
[ROW][C]31[/C][C]-0.156047[/C][C]-1.0811[/C][C]0.142522[/C][/ROW]
[ROW][C]32[/C][C]0.052197[/C][C]0.3616[/C][C]0.359607[/C][/ROW]
[ROW][C]33[/C][C]-0.160238[/C][C]-1.1102[/C][C]0.136231[/C][/ROW]
[ROW][C]34[/C][C]-0.081881[/C][C]-0.5673[/C][C]0.286581[/C][/ROW]
[ROW][C]35[/C][C]0.024863[/C][C]0.1723[/C][C]0.43198[/C][/ROW]
[ROW][C]36[/C][C]-0.125439[/C][C]-0.8691[/C][C]0.194567[/C][/ROW]
[ROW][C]37[/C][C]0.072582[/C][C]0.5029[/C][C]0.30868[/C][/ROW]
[ROW][C]38[/C][C]-0.090636[/C][C]-0.6279[/C][C]0.266508[/C][/ROW]
[ROW][C]39[/C][C]0.025443[/C][C]0.1763[/C][C]0.43041[/C][/ROW]
[ROW][C]40[/C][C]0.018054[/C][C]0.1251[/C][C]0.450489[/C][/ROW]
[ROW][C]41[/C][C]0.094883[/C][C]0.6574[/C][C]0.257043[/C][/ROW]
[ROW][C]42[/C][C]0.152457[/C][C]1.0563[/C][C]0.14807[/C][/ROW]
[ROW][C]43[/C][C]-0.134482[/C][C]-0.9317[/C][C]0.178072[/C][/ROW]
[ROW][C]44[/C][C]-0.144479[/C][C]-1.001[/C][C]0.160928[/C][/ROW]
[ROW][C]45[/C][C]0.014746[/C][C]0.1022[/C][C]0.459527[/C][/ROW]
[ROW][C]46[/C][C]-0.072212[/C][C]-0.5003[/C][C]0.309575[/C][/ROW]
[ROW][C]47[/C][C]-0.073612[/C][C]-0.51[/C][C]0.306194[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110985&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110985&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
10.8322195.76580
20.4185032.89950.002811
30.0735330.50950.306386
4-0.217495-1.50690.069201
5-0.102344-0.70910.24086
6-0.200034-1.38590.086095
7-0.201713-1.39750.084343
80.0520540.36060.359975
9-0.059438-0.41180.34116
100.0652810.45230.326551
11-0.044458-0.3080.379702
12-0.044591-0.30890.379353
13-0.007927-0.05490.478214
14-0.051383-0.3560.361704
150.2951492.04490.023187
16-0.091059-0.63090.265557
17-0.131881-0.91370.18272
18-0.07344-0.50880.306609
19-0.208539-1.44480.077505
20-0.07589-0.52580.300731
210.1027990.71220.23989
22-0.053046-0.36750.357425
230.0121830.08440.466541
24-0.229079-1.58710.059527
250.0545390.37790.353601
260.0252940.17520.430812
27-0.026448-0.18320.427693
280.1910521.32360.095945
290.2094021.45080.076673
30-0.054725-0.37910.353125
31-0.156047-1.08110.142522
320.0521970.36160.359607
33-0.160238-1.11020.136231
34-0.081881-0.56730.286581
350.0248630.17230.43198
36-0.125439-0.86910.194567
370.0725820.50290.30868
38-0.090636-0.62790.266508
390.0254430.17630.43041
400.0180540.12510.450489
410.0948830.65740.257043
420.1524571.05630.14807
43-0.134482-0.93170.178072
44-0.144479-1.0010.160928
450.0147460.10220.459527
46-0.072212-0.50030.309575
47-0.073612-0.510.306194
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



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