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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 computationTue, 14 Dec 2010 15:34:10 +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/14/t1292340981lohl1wb461jzwur.htm/, Retrieved Thu, 02 May 2024 15:29:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109745, Retrieved Thu, 02 May 2024 15:29:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [ACF geen differen...] [2010-12-03 12:24:26] [9f32078fdcdc094ca748857d5ebdb3de]
-    D      [(Partial) Autocorrelation Function] [] [2010-12-07 15:41:58] [ed939ef6f97e5f2afb6796311d9e7a5f]
- R  D          [(Partial) Autocorrelation Function] [Paper - ACF (48 l...] [2010-12-14 15:34:10] [ee4a783fb13f41eb2e9bc8a0c4f26279] [Current]
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Dataseries X:
10.81
9.12
11.03
12.74
9.98
11.62
9.40
9.27
7.76
8.78
10.65
10.95
12.36
10.85
11.84
12.14
11.65
8.86
7.63
7.38
7.25
8.03
7.75
7.16
7.18
7.51
7.07
7.11
8.98
9.53
10.54
11.31
10.36
11.44
10.45
10.69
11.28
11.96
13.52
12.89
14.03
16.27
16.17
17.25
19.38
26.20
33.53
32.20
38.45
44.86
41.67
36.06
39.76
36.81
42.65
46.89
53.61
57.59
67.82
71.89
75.51
68.49
62.72
70.39
59.77
57.27
67.96
67.85
76.98
81.08
91.66
84.84
85.73
84.61
92.91
99.80
121.19
122.04
131.76
138.48
153.47
189.95
182.22
198.08
135.36
125.02
143.50
173.95
188.75
167.44
158.95
169.53
113.66
107.59
92.67
85.35
90.13
89.31
105.12
125.83
135.81
142.43
163.39
168.21
185.35
188.50
199.91
210.73
192.06
204.62
235.00
261.09
256.88
251.53
257.25
243.10
283.75




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109745&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]1 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=109745&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109745&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.95086410.28520
20.9111789.85590
30.864839.35460
40.8224778.89640
50.7801548.43870
60.7325457.92370
70.6923037.48840
80.6591887.13020
90.6273916.78630
100.5916966.40020
110.5577846.03340
120.5260445.690
130.4944065.34780
140.4671055.05251e-06
150.444664.80972e-06
160.4308724.66064e-06
170.4212044.5566e-06
180.4155894.49538e-06
190.4177324.51857e-06
200.4249284.59635e-06
210.4302244.65364e-06
220.4358474.71443e-06
230.4402994.76263e-06
240.4343874.69864e-06
250.4255394.60295e-06
260.3991744.31771.7e-05
270.3791954.10163.8e-05
280.3600853.89498.2e-05
290.3308753.5790.000252
300.3023423.27030.000706
310.2789473.01730.001565
320.2575292.78560.003117
330.2360412.55320.00598
340.1921172.07810.019946
350.1531951.65710.050094
360.1091651.18080.120039
370.0758120.820.206934
380.0470670.50910.305817
390.0208340.22540.411049
40-0.002264-0.02450.490251
41-0.025842-0.27950.390169
42-0.044686-0.48340.314875
43-0.063346-0.68520.247289
44-0.079786-0.8630.194946
45-0.097378-1.05330.147186
46-0.113694-1.22980.110621
47-0.13154-1.42280.078724
48-0.146246-1.58190.058186

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.950864 & 10.2852 & 0 \tabularnewline
2 & 0.911178 & 9.8559 & 0 \tabularnewline
3 & 0.86483 & 9.3546 & 0 \tabularnewline
4 & 0.822477 & 8.8964 & 0 \tabularnewline
5 & 0.780154 & 8.4387 & 0 \tabularnewline
6 & 0.732545 & 7.9237 & 0 \tabularnewline
7 & 0.692303 & 7.4884 & 0 \tabularnewline
8 & 0.659188 & 7.1302 & 0 \tabularnewline
9 & 0.627391 & 6.7863 & 0 \tabularnewline
10 & 0.591696 & 6.4002 & 0 \tabularnewline
11 & 0.557784 & 6.0334 & 0 \tabularnewline
12 & 0.526044 & 5.69 & 0 \tabularnewline
13 & 0.494406 & 5.3478 & 0 \tabularnewline
14 & 0.467105 & 5.0525 & 1e-06 \tabularnewline
15 & 0.44466 & 4.8097 & 2e-06 \tabularnewline
16 & 0.430872 & 4.6606 & 4e-06 \tabularnewline
17 & 0.421204 & 4.556 & 6e-06 \tabularnewline
18 & 0.415589 & 4.4953 & 8e-06 \tabularnewline
19 & 0.417732 & 4.5185 & 7e-06 \tabularnewline
20 & 0.424928 & 4.5963 & 5e-06 \tabularnewline
21 & 0.430224 & 4.6536 & 4e-06 \tabularnewline
22 & 0.435847 & 4.7144 & 3e-06 \tabularnewline
23 & 0.440299 & 4.7626 & 3e-06 \tabularnewline
24 & 0.434387 & 4.6986 & 4e-06 \tabularnewline
25 & 0.425539 & 4.6029 & 5e-06 \tabularnewline
26 & 0.399174 & 4.3177 & 1.7e-05 \tabularnewline
27 & 0.379195 & 4.1016 & 3.8e-05 \tabularnewline
28 & 0.360085 & 3.8949 & 8.2e-05 \tabularnewline
29 & 0.330875 & 3.579 & 0.000252 \tabularnewline
30 & 0.302342 & 3.2703 & 0.000706 \tabularnewline
31 & 0.278947 & 3.0173 & 0.001565 \tabularnewline
32 & 0.257529 & 2.7856 & 0.003117 \tabularnewline
33 & 0.236041 & 2.5532 & 0.00598 \tabularnewline
34 & 0.192117 & 2.0781 & 0.019946 \tabularnewline
35 & 0.153195 & 1.6571 & 0.050094 \tabularnewline
36 & 0.109165 & 1.1808 & 0.120039 \tabularnewline
37 & 0.075812 & 0.82 & 0.206934 \tabularnewline
38 & 0.047067 & 0.5091 & 0.305817 \tabularnewline
39 & 0.020834 & 0.2254 & 0.411049 \tabularnewline
40 & -0.002264 & -0.0245 & 0.490251 \tabularnewline
41 & -0.025842 & -0.2795 & 0.390169 \tabularnewline
42 & -0.044686 & -0.4834 & 0.314875 \tabularnewline
43 & -0.063346 & -0.6852 & 0.247289 \tabularnewline
44 & -0.079786 & -0.863 & 0.194946 \tabularnewline
45 & -0.097378 & -1.0533 & 0.147186 \tabularnewline
46 & -0.113694 & -1.2298 & 0.110621 \tabularnewline
47 & -0.13154 & -1.4228 & 0.078724 \tabularnewline
48 & -0.146246 & -1.5819 & 0.058186 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109745&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]0.950864[/C][C]10.2852[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.911178[/C][C]9.8559[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.86483[/C][C]9.3546[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.822477[/C][C]8.8964[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.780154[/C][C]8.4387[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.732545[/C][C]7.9237[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.692303[/C][C]7.4884[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.659188[/C][C]7.1302[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.627391[/C][C]6.7863[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.591696[/C][C]6.4002[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.557784[/C][C]6.0334[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.526044[/C][C]5.69[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.494406[/C][C]5.3478[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.467105[/C][C]5.0525[/C][C]1e-06[/C][/ROW]
[ROW][C]15[/C][C]0.44466[/C][C]4.8097[/C][C]2e-06[/C][/ROW]
[ROW][C]16[/C][C]0.430872[/C][C]4.6606[/C][C]4e-06[/C][/ROW]
[ROW][C]17[/C][C]0.421204[/C][C]4.556[/C][C]6e-06[/C][/ROW]
[ROW][C]18[/C][C]0.415589[/C][C]4.4953[/C][C]8e-06[/C][/ROW]
[ROW][C]19[/C][C]0.417732[/C][C]4.5185[/C][C]7e-06[/C][/ROW]
[ROW][C]20[/C][C]0.424928[/C][C]4.5963[/C][C]5e-06[/C][/ROW]
[ROW][C]21[/C][C]0.430224[/C][C]4.6536[/C][C]4e-06[/C][/ROW]
[ROW][C]22[/C][C]0.435847[/C][C]4.7144[/C][C]3e-06[/C][/ROW]
[ROW][C]23[/C][C]0.440299[/C][C]4.7626[/C][C]3e-06[/C][/ROW]
[ROW][C]24[/C][C]0.434387[/C][C]4.6986[/C][C]4e-06[/C][/ROW]
[ROW][C]25[/C][C]0.425539[/C][C]4.6029[/C][C]5e-06[/C][/ROW]
[ROW][C]26[/C][C]0.399174[/C][C]4.3177[/C][C]1.7e-05[/C][/ROW]
[ROW][C]27[/C][C]0.379195[/C][C]4.1016[/C][C]3.8e-05[/C][/ROW]
[ROW][C]28[/C][C]0.360085[/C][C]3.8949[/C][C]8.2e-05[/C][/ROW]
[ROW][C]29[/C][C]0.330875[/C][C]3.579[/C][C]0.000252[/C][/ROW]
[ROW][C]30[/C][C]0.302342[/C][C]3.2703[/C][C]0.000706[/C][/ROW]
[ROW][C]31[/C][C]0.278947[/C][C]3.0173[/C][C]0.001565[/C][/ROW]
[ROW][C]32[/C][C]0.257529[/C][C]2.7856[/C][C]0.003117[/C][/ROW]
[ROW][C]33[/C][C]0.236041[/C][C]2.5532[/C][C]0.00598[/C][/ROW]
[ROW][C]34[/C][C]0.192117[/C][C]2.0781[/C][C]0.019946[/C][/ROW]
[ROW][C]35[/C][C]0.153195[/C][C]1.6571[/C][C]0.050094[/C][/ROW]
[ROW][C]36[/C][C]0.109165[/C][C]1.1808[/C][C]0.120039[/C][/ROW]
[ROW][C]37[/C][C]0.075812[/C][C]0.82[/C][C]0.206934[/C][/ROW]
[ROW][C]38[/C][C]0.047067[/C][C]0.5091[/C][C]0.305817[/C][/ROW]
[ROW][C]39[/C][C]0.020834[/C][C]0.2254[/C][C]0.411049[/C][/ROW]
[ROW][C]40[/C][C]-0.002264[/C][C]-0.0245[/C][C]0.490251[/C][/ROW]
[ROW][C]41[/C][C]-0.025842[/C][C]-0.2795[/C][C]0.390169[/C][/ROW]
[ROW][C]42[/C][C]-0.044686[/C][C]-0.4834[/C][C]0.314875[/C][/ROW]
[ROW][C]43[/C][C]-0.063346[/C][C]-0.6852[/C][C]0.247289[/C][/ROW]
[ROW][C]44[/C][C]-0.079786[/C][C]-0.863[/C][C]0.194946[/C][/ROW]
[ROW][C]45[/C][C]-0.097378[/C][C]-1.0533[/C][C]0.147186[/C][/ROW]
[ROW][C]46[/C][C]-0.113694[/C][C]-1.2298[/C][C]0.110621[/C][/ROW]
[ROW][C]47[/C][C]-0.13154[/C][C]-1.4228[/C][C]0.078724[/C][/ROW]
[ROW][C]48[/C][C]-0.146246[/C][C]-1.5819[/C][C]0.058186[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109745&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109745&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
10.95086410.28520
20.9111789.85590
30.864839.35460
40.8224778.89640
50.7801548.43870
60.7325457.92370
70.6923037.48840
80.6591887.13020
90.6273916.78630
100.5916966.40020
110.5577846.03340
120.5260445.690
130.4944065.34780
140.4671055.05251e-06
150.444664.80972e-06
160.4308724.66064e-06
170.4212044.5566e-06
180.4155894.49538e-06
190.4177324.51857e-06
200.4249284.59635e-06
210.4302244.65364e-06
220.4358474.71443e-06
230.4402994.76263e-06
240.4343874.69864e-06
250.4255394.60295e-06
260.3991744.31771.7e-05
270.3791954.10163.8e-05
280.3600853.89498.2e-05
290.3308753.5790.000252
300.3023423.27030.000706
310.2789473.01730.001565
320.2575292.78560.003117
330.2360412.55320.00598
340.1921172.07810.019946
350.1531951.65710.050094
360.1091651.18080.120039
370.0758120.820.206934
380.0470670.50910.305817
390.0208340.22540.411049
40-0.002264-0.02450.490251
41-0.025842-0.27950.390169
42-0.044686-0.48340.314875
43-0.063346-0.68520.247289
44-0.079786-0.8630.194946
45-0.097378-1.05330.147186
46-0.113694-1.22980.110621
47-0.13154-1.42280.078724
48-0.146246-1.58190.058186







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95086410.28520
20.073390.79380.214451
3-0.081546-0.88210.189777
40.0054610.05910.4765
5-0.012663-0.1370.445645
6-0.082922-0.89690.185798
70.0412780.44650.328034
80.0718690.77740.219251
9-0.004925-0.05330.478805
10-0.065276-0.70610.240775
11-0.003214-0.03480.486164
120.0032580.03520.485972
13-0.026361-0.28510.388023
140.0333970.36120.359284
150.0577610.62480.266664
160.0740690.80120.212328
170.0357780.3870.349729
180.0399530.43220.333212
190.0855530.92540.178332
200.0645920.69870.243072
21-0.011027-0.11930.452633
220.0205820.22260.412107
230.0132980.14380.442937
24-0.11354-1.22810.110932
25-0.049864-0.53940.295333
26-0.167145-1.80790.036592
270.0220380.23840.406002
280.0236040.25530.399465
29-0.119891-1.29680.098622
30-0.023228-0.25130.40103
310.0729030.78860.215979
32-0.004769-0.05160.479476
33-0.0095-0.10280.459167
34-0.217563-2.35330.010138
350.0079390.08590.465858
36-0.073804-0.79830.213155
370.054010.58420.280101
380.0803610.86920.193249
39-0.001343-0.01450.494216
40-0.059677-0.64550.259931
41-0.088503-0.95730.170192
42-0.028666-0.31010.37853
43-0.026254-0.2840.388462
44-0.03696-0.39980.345023
45-0.030754-0.33270.369996
460.0088870.09610.461791
47-0.073959-0.80.21267
48-0.016677-0.18040.42858

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.950864 & 10.2852 & 0 \tabularnewline
2 & 0.07339 & 0.7938 & 0.214451 \tabularnewline
3 & -0.081546 & -0.8821 & 0.189777 \tabularnewline
4 & 0.005461 & 0.0591 & 0.4765 \tabularnewline
5 & -0.012663 & -0.137 & 0.445645 \tabularnewline
6 & -0.082922 & -0.8969 & 0.185798 \tabularnewline
7 & 0.041278 & 0.4465 & 0.328034 \tabularnewline
8 & 0.071869 & 0.7774 & 0.219251 \tabularnewline
9 & -0.004925 & -0.0533 & 0.478805 \tabularnewline
10 & -0.065276 & -0.7061 & 0.240775 \tabularnewline
11 & -0.003214 & -0.0348 & 0.486164 \tabularnewline
12 & 0.003258 & 0.0352 & 0.485972 \tabularnewline
13 & -0.026361 & -0.2851 & 0.388023 \tabularnewline
14 & 0.033397 & 0.3612 & 0.359284 \tabularnewline
15 & 0.057761 & 0.6248 & 0.266664 \tabularnewline
16 & 0.074069 & 0.8012 & 0.212328 \tabularnewline
17 & 0.035778 & 0.387 & 0.349729 \tabularnewline
18 & 0.039953 & 0.4322 & 0.333212 \tabularnewline
19 & 0.085553 & 0.9254 & 0.178332 \tabularnewline
20 & 0.064592 & 0.6987 & 0.243072 \tabularnewline
21 & -0.011027 & -0.1193 & 0.452633 \tabularnewline
22 & 0.020582 & 0.2226 & 0.412107 \tabularnewline
23 & 0.013298 & 0.1438 & 0.442937 \tabularnewline
24 & -0.11354 & -1.2281 & 0.110932 \tabularnewline
25 & -0.049864 & -0.5394 & 0.295333 \tabularnewline
26 & -0.167145 & -1.8079 & 0.036592 \tabularnewline
27 & 0.022038 & 0.2384 & 0.406002 \tabularnewline
28 & 0.023604 & 0.2553 & 0.399465 \tabularnewline
29 & -0.119891 & -1.2968 & 0.098622 \tabularnewline
30 & -0.023228 & -0.2513 & 0.40103 \tabularnewline
31 & 0.072903 & 0.7886 & 0.215979 \tabularnewline
32 & -0.004769 & -0.0516 & 0.479476 \tabularnewline
33 & -0.0095 & -0.1028 & 0.459167 \tabularnewline
34 & -0.217563 & -2.3533 & 0.010138 \tabularnewline
35 & 0.007939 & 0.0859 & 0.465858 \tabularnewline
36 & -0.073804 & -0.7983 & 0.213155 \tabularnewline
37 & 0.05401 & 0.5842 & 0.280101 \tabularnewline
38 & 0.080361 & 0.8692 & 0.193249 \tabularnewline
39 & -0.001343 & -0.0145 & 0.494216 \tabularnewline
40 & -0.059677 & -0.6455 & 0.259931 \tabularnewline
41 & -0.088503 & -0.9573 & 0.170192 \tabularnewline
42 & -0.028666 & -0.3101 & 0.37853 \tabularnewline
43 & -0.026254 & -0.284 & 0.388462 \tabularnewline
44 & -0.03696 & -0.3998 & 0.345023 \tabularnewline
45 & -0.030754 & -0.3327 & 0.369996 \tabularnewline
46 & 0.008887 & 0.0961 & 0.461791 \tabularnewline
47 & -0.073959 & -0.8 & 0.21267 \tabularnewline
48 & -0.016677 & -0.1804 & 0.42858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109745&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]0.950864[/C][C]10.2852[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.07339[/C][C]0.7938[/C][C]0.214451[/C][/ROW]
[ROW][C]3[/C][C]-0.081546[/C][C]-0.8821[/C][C]0.189777[/C][/ROW]
[ROW][C]4[/C][C]0.005461[/C][C]0.0591[/C][C]0.4765[/C][/ROW]
[ROW][C]5[/C][C]-0.012663[/C][C]-0.137[/C][C]0.445645[/C][/ROW]
[ROW][C]6[/C][C]-0.082922[/C][C]-0.8969[/C][C]0.185798[/C][/ROW]
[ROW][C]7[/C][C]0.041278[/C][C]0.4465[/C][C]0.328034[/C][/ROW]
[ROW][C]8[/C][C]0.071869[/C][C]0.7774[/C][C]0.219251[/C][/ROW]
[ROW][C]9[/C][C]-0.004925[/C][C]-0.0533[/C][C]0.478805[/C][/ROW]
[ROW][C]10[/C][C]-0.065276[/C][C]-0.7061[/C][C]0.240775[/C][/ROW]
[ROW][C]11[/C][C]-0.003214[/C][C]-0.0348[/C][C]0.486164[/C][/ROW]
[ROW][C]12[/C][C]0.003258[/C][C]0.0352[/C][C]0.485972[/C][/ROW]
[ROW][C]13[/C][C]-0.026361[/C][C]-0.2851[/C][C]0.388023[/C][/ROW]
[ROW][C]14[/C][C]0.033397[/C][C]0.3612[/C][C]0.359284[/C][/ROW]
[ROW][C]15[/C][C]0.057761[/C][C]0.6248[/C][C]0.266664[/C][/ROW]
[ROW][C]16[/C][C]0.074069[/C][C]0.8012[/C][C]0.212328[/C][/ROW]
[ROW][C]17[/C][C]0.035778[/C][C]0.387[/C][C]0.349729[/C][/ROW]
[ROW][C]18[/C][C]0.039953[/C][C]0.4322[/C][C]0.333212[/C][/ROW]
[ROW][C]19[/C][C]0.085553[/C][C]0.9254[/C][C]0.178332[/C][/ROW]
[ROW][C]20[/C][C]0.064592[/C][C]0.6987[/C][C]0.243072[/C][/ROW]
[ROW][C]21[/C][C]-0.011027[/C][C]-0.1193[/C][C]0.452633[/C][/ROW]
[ROW][C]22[/C][C]0.020582[/C][C]0.2226[/C][C]0.412107[/C][/ROW]
[ROW][C]23[/C][C]0.013298[/C][C]0.1438[/C][C]0.442937[/C][/ROW]
[ROW][C]24[/C][C]-0.11354[/C][C]-1.2281[/C][C]0.110932[/C][/ROW]
[ROW][C]25[/C][C]-0.049864[/C][C]-0.5394[/C][C]0.295333[/C][/ROW]
[ROW][C]26[/C][C]-0.167145[/C][C]-1.8079[/C][C]0.036592[/C][/ROW]
[ROW][C]27[/C][C]0.022038[/C][C]0.2384[/C][C]0.406002[/C][/ROW]
[ROW][C]28[/C][C]0.023604[/C][C]0.2553[/C][C]0.399465[/C][/ROW]
[ROW][C]29[/C][C]-0.119891[/C][C]-1.2968[/C][C]0.098622[/C][/ROW]
[ROW][C]30[/C][C]-0.023228[/C][C]-0.2513[/C][C]0.40103[/C][/ROW]
[ROW][C]31[/C][C]0.072903[/C][C]0.7886[/C][C]0.215979[/C][/ROW]
[ROW][C]32[/C][C]-0.004769[/C][C]-0.0516[/C][C]0.479476[/C][/ROW]
[ROW][C]33[/C][C]-0.0095[/C][C]-0.1028[/C][C]0.459167[/C][/ROW]
[ROW][C]34[/C][C]-0.217563[/C][C]-2.3533[/C][C]0.010138[/C][/ROW]
[ROW][C]35[/C][C]0.007939[/C][C]0.0859[/C][C]0.465858[/C][/ROW]
[ROW][C]36[/C][C]-0.073804[/C][C]-0.7983[/C][C]0.213155[/C][/ROW]
[ROW][C]37[/C][C]0.05401[/C][C]0.5842[/C][C]0.280101[/C][/ROW]
[ROW][C]38[/C][C]0.080361[/C][C]0.8692[/C][C]0.193249[/C][/ROW]
[ROW][C]39[/C][C]-0.001343[/C][C]-0.0145[/C][C]0.494216[/C][/ROW]
[ROW][C]40[/C][C]-0.059677[/C][C]-0.6455[/C][C]0.259931[/C][/ROW]
[ROW][C]41[/C][C]-0.088503[/C][C]-0.9573[/C][C]0.170192[/C][/ROW]
[ROW][C]42[/C][C]-0.028666[/C][C]-0.3101[/C][C]0.37853[/C][/ROW]
[ROW][C]43[/C][C]-0.026254[/C][C]-0.284[/C][C]0.388462[/C][/ROW]
[ROW][C]44[/C][C]-0.03696[/C][C]-0.3998[/C][C]0.345023[/C][/ROW]
[ROW][C]45[/C][C]-0.030754[/C][C]-0.3327[/C][C]0.369996[/C][/ROW]
[ROW][C]46[/C][C]0.008887[/C][C]0.0961[/C][C]0.461791[/C][/ROW]
[ROW][C]47[/C][C]-0.073959[/C][C]-0.8[/C][C]0.21267[/C][/ROW]
[ROW][C]48[/C][C]-0.016677[/C][C]-0.1804[/C][C]0.42858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109745&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109745&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
10.95086410.28520
20.073390.79380.214451
3-0.081546-0.88210.189777
40.0054610.05910.4765
5-0.012663-0.1370.445645
6-0.082922-0.89690.185798
70.0412780.44650.328034
80.0718690.77740.219251
9-0.004925-0.05330.478805
10-0.065276-0.70610.240775
11-0.003214-0.03480.486164
120.0032580.03520.485972
13-0.026361-0.28510.388023
140.0333970.36120.359284
150.0577610.62480.266664
160.0740690.80120.212328
170.0357780.3870.349729
180.0399530.43220.333212
190.0855530.92540.178332
200.0645920.69870.243072
21-0.011027-0.11930.452633
220.0205820.22260.412107
230.0132980.14380.442937
24-0.11354-1.22810.110932
25-0.049864-0.53940.295333
26-0.167145-1.80790.036592
270.0220380.23840.406002
280.0236040.25530.399465
29-0.119891-1.29680.098622
30-0.023228-0.25130.40103
310.0729030.78860.215979
32-0.004769-0.05160.479476
33-0.0095-0.10280.459167
34-0.217563-2.35330.010138
350.0079390.08590.465858
36-0.073804-0.79830.213155
370.054010.58420.280101
380.0803610.86920.193249
39-0.001343-0.01450.494216
40-0.059677-0.64550.259931
41-0.088503-0.95730.170192
42-0.028666-0.31010.37853
43-0.026254-0.2840.388462
44-0.03696-0.39980.345023
45-0.030754-0.33270.369996
460.0088870.09610.461791
47-0.073959-0.80.21267
48-0.016677-0.18040.42858



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')