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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 13 Dec 2007 07:26:16 -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/2007/Dec/13/t1197555091ioev2g2ewqosqcl.htm/, Retrieved Sun, 05 May 2024 10:00:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3564, Retrieved Sun, 05 May 2024 10:00:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [autocorrelatie (D...] [2007-11-27 10:57:05] [aa0d06577c57214974bc715dada29347]
-   PD    [(Partial) Autocorrelation Function] [Tijdreeks 2: omze...] [2007-12-13 14:26:16] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
106,0
100,9
114,3
101,2
109,2
111,6
91,7
93,7
105,7
109,5
105,3
102,8
100,6
97,6
110,3
107,2
107,2
108,1
97,1
92,2
112,2
111,6
115,7
111,3
104,2
103,2
112,7
106,4
102,6
110,6
95,2
89,0
112,5
116,8
107,2
113,6
101,8
102,6
122,7
110,3
110,5
121,6
100,3
100,7
123,4
127,1
124,1
131,2
111,6
114,2
130,1
125,9
119,0
133,8
107,5
113,5
134,4
126,8
135,6
139,9
129,8
131,0
153,1
134,1
144,1
155,9
123,3
128,1
144,3
153,0
149,9
150,9
141,0
138,9
157,4
142,9
151,7
161,0
138,6
136,0
151,9




Summary of compuational 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 compuational 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=3564&T=0

[TABLE]
[ROW][C]Summary of compuational 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=3564&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3564&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 compuational 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
018.24620
1-0.577365-4.76110.999995
20.1339571.10460.136605
30.041410.34150.366901
4-0.078871-0.65040.741184
50.0921360.75980.225007
6-0.076401-0.630.734603
70.0468770.38660.350146
8-0.113828-0.93870.824384
90.2357281.94390.028025
10-0.259838-2.14270.982139
110.2272841.87420.032597
12-0.295131-2.43370.991211
130.0828350.68310.24844
140.0646810.53340.297758
15-0.019947-0.16450.565082
16-0.030673-0.25290.59946
17-0.083638-0.68970.753634
180.2918662.40680.009407
19-0.309962-2.5560.993586
200.212641.75350.042014
21-0.120448-0.99320.837942
22-0.016974-0.140.555451
230.1739171.43420.078055
24-0.079215-0.65320.742093
25-0.025247-0.20820.582148
260.0712720.58770.279332
27-0.007317-0.06030.523969
28-0.147821-1.2190.886465
290.2576612.12470.018623
30-0.290346-2.39430.990291
310.1818751.49980.06915
32-0.026901-0.22180.587443
33-0.007582-0.06250.524834
34-0.038643-0.31870.62452
35-0.054023-0.44550.671307
360.0359920.29680.383762
37-0.021161-0.17450.569004
380.0642770.530.298905
39-0.151723-1.25110.892414
400.2375261.95870.027126
41-0.161137-1.32880.905817
420.0362620.2990.382916
430.0237450.19580.422672
44-0.00698-0.05760.522866
45-0.035028-0.28880.613212
460.0394250.32510.373049
470.1097860.90530.184247

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 8.2462 & 0 \tabularnewline
1 & -0.577365 & -4.7611 & 0.999995 \tabularnewline
2 & 0.133957 & 1.1046 & 0.136605 \tabularnewline
3 & 0.04141 & 0.3415 & 0.366901 \tabularnewline
4 & -0.078871 & -0.6504 & 0.741184 \tabularnewline
5 & 0.092136 & 0.7598 & 0.225007 \tabularnewline
6 & -0.076401 & -0.63 & 0.734603 \tabularnewline
7 & 0.046877 & 0.3866 & 0.350146 \tabularnewline
8 & -0.113828 & -0.9387 & 0.824384 \tabularnewline
9 & 0.235728 & 1.9439 & 0.028025 \tabularnewline
10 & -0.259838 & -2.1427 & 0.982139 \tabularnewline
11 & 0.227284 & 1.8742 & 0.032597 \tabularnewline
12 & -0.295131 & -2.4337 & 0.991211 \tabularnewline
13 & 0.082835 & 0.6831 & 0.24844 \tabularnewline
14 & 0.064681 & 0.5334 & 0.297758 \tabularnewline
15 & -0.019947 & -0.1645 & 0.565082 \tabularnewline
16 & -0.030673 & -0.2529 & 0.59946 \tabularnewline
17 & -0.083638 & -0.6897 & 0.753634 \tabularnewline
18 & 0.291866 & 2.4068 & 0.009407 \tabularnewline
19 & -0.309962 & -2.556 & 0.993586 \tabularnewline
20 & 0.21264 & 1.7535 & 0.042014 \tabularnewline
21 & -0.120448 & -0.9932 & 0.837942 \tabularnewline
22 & -0.016974 & -0.14 & 0.555451 \tabularnewline
23 & 0.173917 & 1.4342 & 0.078055 \tabularnewline
24 & -0.079215 & -0.6532 & 0.742093 \tabularnewline
25 & -0.025247 & -0.2082 & 0.582148 \tabularnewline
26 & 0.071272 & 0.5877 & 0.279332 \tabularnewline
27 & -0.007317 & -0.0603 & 0.523969 \tabularnewline
28 & -0.147821 & -1.219 & 0.886465 \tabularnewline
29 & 0.257661 & 2.1247 & 0.018623 \tabularnewline
30 & -0.290346 & -2.3943 & 0.990291 \tabularnewline
31 & 0.181875 & 1.4998 & 0.06915 \tabularnewline
32 & -0.026901 & -0.2218 & 0.587443 \tabularnewline
33 & -0.007582 & -0.0625 & 0.524834 \tabularnewline
34 & -0.038643 & -0.3187 & 0.62452 \tabularnewline
35 & -0.054023 & -0.4455 & 0.671307 \tabularnewline
36 & 0.035992 & 0.2968 & 0.383762 \tabularnewline
37 & -0.021161 & -0.1745 & 0.569004 \tabularnewline
38 & 0.064277 & 0.53 & 0.298905 \tabularnewline
39 & -0.151723 & -1.2511 & 0.892414 \tabularnewline
40 & 0.237526 & 1.9587 & 0.027126 \tabularnewline
41 & -0.161137 & -1.3288 & 0.905817 \tabularnewline
42 & 0.036262 & 0.299 & 0.382916 \tabularnewline
43 & 0.023745 & 0.1958 & 0.422672 \tabularnewline
44 & -0.00698 & -0.0576 & 0.522866 \tabularnewline
45 & -0.035028 & -0.2888 & 0.613212 \tabularnewline
46 & 0.039425 & 0.3251 & 0.373049 \tabularnewline
47 & 0.109786 & 0.9053 & 0.184247 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3564&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]0[/C][C]1[/C][C]8.2462[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]-0.577365[/C][C]-4.7611[/C][C]0.999995[/C][/ROW]
[ROW][C]2[/C][C]0.133957[/C][C]1.1046[/C][C]0.136605[/C][/ROW]
[ROW][C]3[/C][C]0.04141[/C][C]0.3415[/C][C]0.366901[/C][/ROW]
[ROW][C]4[/C][C]-0.078871[/C][C]-0.6504[/C][C]0.741184[/C][/ROW]
[ROW][C]5[/C][C]0.092136[/C][C]0.7598[/C][C]0.225007[/C][/ROW]
[ROW][C]6[/C][C]-0.076401[/C][C]-0.63[/C][C]0.734603[/C][/ROW]
[ROW][C]7[/C][C]0.046877[/C][C]0.3866[/C][C]0.350146[/C][/ROW]
[ROW][C]8[/C][C]-0.113828[/C][C]-0.9387[/C][C]0.824384[/C][/ROW]
[ROW][C]9[/C][C]0.235728[/C][C]1.9439[/C][C]0.028025[/C][/ROW]
[ROW][C]10[/C][C]-0.259838[/C][C]-2.1427[/C][C]0.982139[/C][/ROW]
[ROW][C]11[/C][C]0.227284[/C][C]1.8742[/C][C]0.032597[/C][/ROW]
[ROW][C]12[/C][C]-0.295131[/C][C]-2.4337[/C][C]0.991211[/C][/ROW]
[ROW][C]13[/C][C]0.082835[/C][C]0.6831[/C][C]0.24844[/C][/ROW]
[ROW][C]14[/C][C]0.064681[/C][C]0.5334[/C][C]0.297758[/C][/ROW]
[ROW][C]15[/C][C]-0.019947[/C][C]-0.1645[/C][C]0.565082[/C][/ROW]
[ROW][C]16[/C][C]-0.030673[/C][C]-0.2529[/C][C]0.59946[/C][/ROW]
[ROW][C]17[/C][C]-0.083638[/C][C]-0.6897[/C][C]0.753634[/C][/ROW]
[ROW][C]18[/C][C]0.291866[/C][C]2.4068[/C][C]0.009407[/C][/ROW]
[ROW][C]19[/C][C]-0.309962[/C][C]-2.556[/C][C]0.993586[/C][/ROW]
[ROW][C]20[/C][C]0.21264[/C][C]1.7535[/C][C]0.042014[/C][/ROW]
[ROW][C]21[/C][C]-0.120448[/C][C]-0.9932[/C][C]0.837942[/C][/ROW]
[ROW][C]22[/C][C]-0.016974[/C][C]-0.14[/C][C]0.555451[/C][/ROW]
[ROW][C]23[/C][C]0.173917[/C][C]1.4342[/C][C]0.078055[/C][/ROW]
[ROW][C]24[/C][C]-0.079215[/C][C]-0.6532[/C][C]0.742093[/C][/ROW]
[ROW][C]25[/C][C]-0.025247[/C][C]-0.2082[/C][C]0.582148[/C][/ROW]
[ROW][C]26[/C][C]0.071272[/C][C]0.5877[/C][C]0.279332[/C][/ROW]
[ROW][C]27[/C][C]-0.007317[/C][C]-0.0603[/C][C]0.523969[/C][/ROW]
[ROW][C]28[/C][C]-0.147821[/C][C]-1.219[/C][C]0.886465[/C][/ROW]
[ROW][C]29[/C][C]0.257661[/C][C]2.1247[/C][C]0.018623[/C][/ROW]
[ROW][C]30[/C][C]-0.290346[/C][C]-2.3943[/C][C]0.990291[/C][/ROW]
[ROW][C]31[/C][C]0.181875[/C][C]1.4998[/C][C]0.06915[/C][/ROW]
[ROW][C]32[/C][C]-0.026901[/C][C]-0.2218[/C][C]0.587443[/C][/ROW]
[ROW][C]33[/C][C]-0.007582[/C][C]-0.0625[/C][C]0.524834[/C][/ROW]
[ROW][C]34[/C][C]-0.038643[/C][C]-0.3187[/C][C]0.62452[/C][/ROW]
[ROW][C]35[/C][C]-0.054023[/C][C]-0.4455[/C][C]0.671307[/C][/ROW]
[ROW][C]36[/C][C]0.035992[/C][C]0.2968[/C][C]0.383762[/C][/ROW]
[ROW][C]37[/C][C]-0.021161[/C][C]-0.1745[/C][C]0.569004[/C][/ROW]
[ROW][C]38[/C][C]0.064277[/C][C]0.53[/C][C]0.298905[/C][/ROW]
[ROW][C]39[/C][C]-0.151723[/C][C]-1.2511[/C][C]0.892414[/C][/ROW]
[ROW][C]40[/C][C]0.237526[/C][C]1.9587[/C][C]0.027126[/C][/ROW]
[ROW][C]41[/C][C]-0.161137[/C][C]-1.3288[/C][C]0.905817[/C][/ROW]
[ROW][C]42[/C][C]0.036262[/C][C]0.299[/C][C]0.382916[/C][/ROW]
[ROW][C]43[/C][C]0.023745[/C][C]0.1958[/C][C]0.422672[/C][/ROW]
[ROW][C]44[/C][C]-0.00698[/C][C]-0.0576[/C][C]0.522866[/C][/ROW]
[ROW][C]45[/C][C]-0.035028[/C][C]-0.2888[/C][C]0.613212[/C][/ROW]
[ROW][C]46[/C][C]0.039425[/C][C]0.3251[/C][C]0.373049[/C][/ROW]
[ROW][C]47[/C][C]0.109786[/C][C]0.9053[/C][C]0.184247[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3564&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3564&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
018.24620
1-0.577365-4.76110.999995
20.1339571.10460.136605
30.041410.34150.366901
4-0.078871-0.65040.741184
50.0921360.75980.225007
6-0.076401-0.630.734603
70.0468770.38660.350146
8-0.113828-0.93870.824384
90.2357281.94390.028025
10-0.259838-2.14270.982139
110.2272841.87420.032597
12-0.295131-2.43370.991211
130.0828350.68310.24844
140.0646810.53340.297758
15-0.019947-0.16450.565082
16-0.030673-0.25290.59946
17-0.083638-0.68970.753634
180.2918662.40680.009407
19-0.309962-2.5560.993586
200.212641.75350.042014
21-0.120448-0.99320.837942
22-0.016974-0.140.555451
230.1739171.43420.078055
24-0.079215-0.65320.742093
25-0.025247-0.20820.582148
260.0712720.58770.279332
27-0.007317-0.06030.523969
28-0.147821-1.2190.886465
290.2576612.12470.018623
30-0.290346-2.39430.990291
310.1818751.49980.06915
32-0.026901-0.22180.587443
33-0.007582-0.06250.524834
34-0.038643-0.31870.62452
35-0.054023-0.44550.671307
360.0359920.29680.383762
37-0.021161-0.17450.569004
380.0642770.530.298905
39-0.151723-1.25110.892414
400.2375261.95870.027126
41-0.161137-1.32880.905817
420.0362620.2990.382916
430.0237450.19580.422672
44-0.00698-0.05760.522866
45-0.035028-0.28880.613212
460.0394250.32510.373049
470.1097860.90530.184247







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
0-0.577365-4.76110.999995
1-0.299097-2.46640.991913
2-0.050746-0.41850.661537
3-0.051726-0.42650.664471
40.0471880.38910.349199
5-0.001896-0.01560.506213
60.0138080.11390.454842
7-0.156839-1.29330.899863
80.1540821.27060.104102
9-0.057454-0.47380.681412
100.1182630.97520.166454
11-0.278937-2.30020.987744
12-0.320266-2.6410.994877
13-0.231813-1.91160.969927
140.0825850.6810.249087
150.0236870.19530.422859
16-0.138608-1.1430.871475
170.174331.43760.077573
180.0304440.2510.401267
190.0168680.13910.444894
200.0649710.53580.296934
21-0.105941-0.87360.807298
220.0733380.60480.273675
230.0652320.53790.296195
24-0.089964-0.74190.769638
250.0484420.39950.345401
260.0943060.77770.219731
27-0.152427-1.25690.893464
28-0.004934-0.04070.516168
290.0453820.37420.354698
300.0945260.77950.219201
31-0.024899-0.20530.581034
320.0905280.74650.228965
33-0.086941-0.71690.762064
34-0.119257-0.98340.835556
35-0.160884-1.32670.905475
36-0.02891-0.23840.593855
37-0.0058-0.04780.519003
38-0.008001-0.0660.526206
390.1084170.8940.187229
400.0195260.1610.436278
41-0.02093-0.17260.56826
420.0466880.3850.35072
430.0160110.1320.447674
440.0209380.17270.431717
45-0.067299-0.5550.709629
46-0.043582-0.35940.63979
47-0.076774-0.63310.735602

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & -0.577365 & -4.7611 & 0.999995 \tabularnewline
1 & -0.299097 & -2.4664 & 0.991913 \tabularnewline
2 & -0.050746 & -0.4185 & 0.661537 \tabularnewline
3 & -0.051726 & -0.4265 & 0.664471 \tabularnewline
4 & 0.047188 & 0.3891 & 0.349199 \tabularnewline
5 & -0.001896 & -0.0156 & 0.506213 \tabularnewline
6 & 0.013808 & 0.1139 & 0.454842 \tabularnewline
7 & -0.156839 & -1.2933 & 0.899863 \tabularnewline
8 & 0.154082 & 1.2706 & 0.104102 \tabularnewline
9 & -0.057454 & -0.4738 & 0.681412 \tabularnewline
10 & 0.118263 & 0.9752 & 0.166454 \tabularnewline
11 & -0.278937 & -2.3002 & 0.987744 \tabularnewline
12 & -0.320266 & -2.641 & 0.994877 \tabularnewline
13 & -0.231813 & -1.9116 & 0.969927 \tabularnewline
14 & 0.082585 & 0.681 & 0.249087 \tabularnewline
15 & 0.023687 & 0.1953 & 0.422859 \tabularnewline
16 & -0.138608 & -1.143 & 0.871475 \tabularnewline
17 & 0.17433 & 1.4376 & 0.077573 \tabularnewline
18 & 0.030444 & 0.251 & 0.401267 \tabularnewline
19 & 0.016868 & 0.1391 & 0.444894 \tabularnewline
20 & 0.064971 & 0.5358 & 0.296934 \tabularnewline
21 & -0.105941 & -0.8736 & 0.807298 \tabularnewline
22 & 0.073338 & 0.6048 & 0.273675 \tabularnewline
23 & 0.065232 & 0.5379 & 0.296195 \tabularnewline
24 & -0.089964 & -0.7419 & 0.769638 \tabularnewline
25 & 0.048442 & 0.3995 & 0.345401 \tabularnewline
26 & 0.094306 & 0.7777 & 0.219731 \tabularnewline
27 & -0.152427 & -1.2569 & 0.893464 \tabularnewline
28 & -0.004934 & -0.0407 & 0.516168 \tabularnewline
29 & 0.045382 & 0.3742 & 0.354698 \tabularnewline
30 & 0.094526 & 0.7795 & 0.219201 \tabularnewline
31 & -0.024899 & -0.2053 & 0.581034 \tabularnewline
32 & 0.090528 & 0.7465 & 0.228965 \tabularnewline
33 & -0.086941 & -0.7169 & 0.762064 \tabularnewline
34 & -0.119257 & -0.9834 & 0.835556 \tabularnewline
35 & -0.160884 & -1.3267 & 0.905475 \tabularnewline
36 & -0.02891 & -0.2384 & 0.593855 \tabularnewline
37 & -0.0058 & -0.0478 & 0.519003 \tabularnewline
38 & -0.008001 & -0.066 & 0.526206 \tabularnewline
39 & 0.108417 & 0.894 & 0.187229 \tabularnewline
40 & 0.019526 & 0.161 & 0.436278 \tabularnewline
41 & -0.02093 & -0.1726 & 0.56826 \tabularnewline
42 & 0.046688 & 0.385 & 0.35072 \tabularnewline
43 & 0.016011 & 0.132 & 0.447674 \tabularnewline
44 & 0.020938 & 0.1727 & 0.431717 \tabularnewline
45 & -0.067299 & -0.555 & 0.709629 \tabularnewline
46 & -0.043582 & -0.3594 & 0.63979 \tabularnewline
47 & -0.076774 & -0.6331 & 0.735602 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3564&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]0[/C][C]-0.577365[/C][C]-4.7611[/C][C]0.999995[/C][/ROW]
[ROW][C]1[/C][C]-0.299097[/C][C]-2.4664[/C][C]0.991913[/C][/ROW]
[ROW][C]2[/C][C]-0.050746[/C][C]-0.4185[/C][C]0.661537[/C][/ROW]
[ROW][C]3[/C][C]-0.051726[/C][C]-0.4265[/C][C]0.664471[/C][/ROW]
[ROW][C]4[/C][C]0.047188[/C][C]0.3891[/C][C]0.349199[/C][/ROW]
[ROW][C]5[/C][C]-0.001896[/C][C]-0.0156[/C][C]0.506213[/C][/ROW]
[ROW][C]6[/C][C]0.013808[/C][C]0.1139[/C][C]0.454842[/C][/ROW]
[ROW][C]7[/C][C]-0.156839[/C][C]-1.2933[/C][C]0.899863[/C][/ROW]
[ROW][C]8[/C][C]0.154082[/C][C]1.2706[/C][C]0.104102[/C][/ROW]
[ROW][C]9[/C][C]-0.057454[/C][C]-0.4738[/C][C]0.681412[/C][/ROW]
[ROW][C]10[/C][C]0.118263[/C][C]0.9752[/C][C]0.166454[/C][/ROW]
[ROW][C]11[/C][C]-0.278937[/C][C]-2.3002[/C][C]0.987744[/C][/ROW]
[ROW][C]12[/C][C]-0.320266[/C][C]-2.641[/C][C]0.994877[/C][/ROW]
[ROW][C]13[/C][C]-0.231813[/C][C]-1.9116[/C][C]0.969927[/C][/ROW]
[ROW][C]14[/C][C]0.082585[/C][C]0.681[/C][C]0.249087[/C][/ROW]
[ROW][C]15[/C][C]0.023687[/C][C]0.1953[/C][C]0.422859[/C][/ROW]
[ROW][C]16[/C][C]-0.138608[/C][C]-1.143[/C][C]0.871475[/C][/ROW]
[ROW][C]17[/C][C]0.17433[/C][C]1.4376[/C][C]0.077573[/C][/ROW]
[ROW][C]18[/C][C]0.030444[/C][C]0.251[/C][C]0.401267[/C][/ROW]
[ROW][C]19[/C][C]0.016868[/C][C]0.1391[/C][C]0.444894[/C][/ROW]
[ROW][C]20[/C][C]0.064971[/C][C]0.5358[/C][C]0.296934[/C][/ROW]
[ROW][C]21[/C][C]-0.105941[/C][C]-0.8736[/C][C]0.807298[/C][/ROW]
[ROW][C]22[/C][C]0.073338[/C][C]0.6048[/C][C]0.273675[/C][/ROW]
[ROW][C]23[/C][C]0.065232[/C][C]0.5379[/C][C]0.296195[/C][/ROW]
[ROW][C]24[/C][C]-0.089964[/C][C]-0.7419[/C][C]0.769638[/C][/ROW]
[ROW][C]25[/C][C]0.048442[/C][C]0.3995[/C][C]0.345401[/C][/ROW]
[ROW][C]26[/C][C]0.094306[/C][C]0.7777[/C][C]0.219731[/C][/ROW]
[ROW][C]27[/C][C]-0.152427[/C][C]-1.2569[/C][C]0.893464[/C][/ROW]
[ROW][C]28[/C][C]-0.004934[/C][C]-0.0407[/C][C]0.516168[/C][/ROW]
[ROW][C]29[/C][C]0.045382[/C][C]0.3742[/C][C]0.354698[/C][/ROW]
[ROW][C]30[/C][C]0.094526[/C][C]0.7795[/C][C]0.219201[/C][/ROW]
[ROW][C]31[/C][C]-0.024899[/C][C]-0.2053[/C][C]0.581034[/C][/ROW]
[ROW][C]32[/C][C]0.090528[/C][C]0.7465[/C][C]0.228965[/C][/ROW]
[ROW][C]33[/C][C]-0.086941[/C][C]-0.7169[/C][C]0.762064[/C][/ROW]
[ROW][C]34[/C][C]-0.119257[/C][C]-0.9834[/C][C]0.835556[/C][/ROW]
[ROW][C]35[/C][C]-0.160884[/C][C]-1.3267[/C][C]0.905475[/C][/ROW]
[ROW][C]36[/C][C]-0.02891[/C][C]-0.2384[/C][C]0.593855[/C][/ROW]
[ROW][C]37[/C][C]-0.0058[/C][C]-0.0478[/C][C]0.519003[/C][/ROW]
[ROW][C]38[/C][C]-0.008001[/C][C]-0.066[/C][C]0.526206[/C][/ROW]
[ROW][C]39[/C][C]0.108417[/C][C]0.894[/C][C]0.187229[/C][/ROW]
[ROW][C]40[/C][C]0.019526[/C][C]0.161[/C][C]0.436278[/C][/ROW]
[ROW][C]41[/C][C]-0.02093[/C][C]-0.1726[/C][C]0.56826[/C][/ROW]
[ROW][C]42[/C][C]0.046688[/C][C]0.385[/C][C]0.35072[/C][/ROW]
[ROW][C]43[/C][C]0.016011[/C][C]0.132[/C][C]0.447674[/C][/ROW]
[ROW][C]44[/C][C]0.020938[/C][C]0.1727[/C][C]0.431717[/C][/ROW]
[ROW][C]45[/C][C]-0.067299[/C][C]-0.555[/C][C]0.709629[/C][/ROW]
[ROW][C]46[/C][C]-0.043582[/C][C]-0.3594[/C][C]0.63979[/C][/ROW]
[ROW][C]47[/C][C]-0.076774[/C][C]-0.6331[/C][C]0.735602[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3564&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3564&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
0-0.577365-4.76110.999995
1-0.299097-2.46640.991913
2-0.050746-0.41850.661537
3-0.051726-0.42650.664471
40.0471880.38910.349199
5-0.001896-0.01560.506213
60.0138080.11390.454842
7-0.156839-1.29330.899863
80.1540821.27060.104102
9-0.057454-0.47380.681412
100.1182630.97520.166454
11-0.278937-2.30020.987744
12-0.320266-2.6410.994877
13-0.231813-1.91160.969927
140.0825850.6810.249087
150.0236870.19530.422859
16-0.138608-1.1430.871475
170.174331.43760.077573
180.0304440.2510.401267
190.0168680.13910.444894
200.0649710.53580.296934
21-0.105941-0.87360.807298
220.0733380.60480.273675
230.0652320.53790.296195
24-0.089964-0.74190.769638
250.0484420.39950.345401
260.0943060.77770.219731
27-0.152427-1.25690.893464
28-0.004934-0.04070.516168
290.0453820.37420.354698
300.0945260.77950.219201
31-0.024899-0.20530.581034
320.0905280.74650.228965
33-0.086941-0.71690.762064
34-0.119257-0.98340.835556
35-0.160884-1.32670.905475
36-0.02891-0.23840.593855
37-0.0058-0.04780.519003
38-0.008001-0.0660.526206
390.1084170.8940.187229
400.0195260.1610.436278
41-0.02093-0.17260.56826
420.0466880.3850.35072
430.0160110.1320.447674
440.0209380.17270.431717
45-0.067299-0.5550.709629
46-0.043582-0.35940.63979
47-0.076774-0.63310.735602



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')