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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 computationWed, 16 Dec 2009 05:21:55 -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/2009/Dec/16/t1260966141s5zqvynhgu6zh26.htm/, Retrieved Tue, 30 Apr 2024 13:14:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68266, Retrieved Tue, 30 Apr 2024 13:14:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [autocorrelation p...] [2009-12-16 12:21:55] [c19014a46a59847aff41bf8576e11c24] [Current]
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Dataseries X:
101.5
99.2
107.8
92.3
99.2
101.6
87
71.4
104.7
115.1
102.5
75.3
96.7
94.6
98.6
99.5
92
93.6
89.3
66.9
108.8
113.2
105.5
77.8
102.1
97
95.5
99.3
86.4
92.4
85.7
61.9
104.9
107.9
95.6
79.8
94.8
93.7
108.1
96.9
88.8
106.7
86.8
69.8
110.9
105.4
99.2
84.4
87.2
91.9
97.9
94.5
85
100.3
78.7
65.8
104.8
96
103.3
82.9
91.4
94.5
109.3
92.1
99.3
109.6
87.5
73.1
110.7
111.6
110.7
84
101.6
102.1
113.9
99
100.4
109.5
93
76.8
105.3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68266&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68266&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68266&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0234060.21070.416842
2-0.327401-2.94660.002097
3-0.105708-0.95140.172122
40.1781841.60370.056341
50.0583170.52490.300559
60.0532730.47950.316452
70.0140340.12630.449902
80.1697721.52790.065211
9-0.16321-1.46890.072868
10-0.377226-3.3950.000533
11-0.023143-0.20830.417763
120.7228526.50570
13-0.055348-0.49810.309871
14-0.297943-2.68150.00444
15-0.160678-1.44610.076003
160.064790.58310.280721
170.0232130.20890.41752
18-0.002366-0.02130.491532
19-0.02632-0.23690.406672
200.1477691.32990.093638
21-0.137971-1.24170.108958
22-0.340388-3.06350.001485
230.0045770.04120.48362
240.5654345.08891e-06
25-0.030999-0.2790.390482
26-0.20008-1.80070.037735
27-0.147069-1.32360.094677
280.0447910.40310.343963
290.05990.53910.295649
30-0.030668-0.2760.391621
31-0.025308-0.22780.410199
320.1527231.37450.086538
33-0.118946-1.07050.143783
34-0.29473-2.65260.004805
35-0.015397-0.13860.445067
360.4363683.92739e-05
37-0.016474-0.14830.441252
38-0.136867-1.23180.110794
39-0.130533-1.17480.121758
400.0321210.28910.386628
410.0303140.27280.39284
42-0.02678-0.2410.405075
43-0.04555-0.40990.341463
440.1269171.14220.128358
45-0.110821-0.99740.160773
46-0.235955-2.12360.018378
47-0.017275-0.15550.438417
480.2957082.66140.004691

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.023406 & 0.2107 & 0.416842 \tabularnewline
2 & -0.327401 & -2.9466 & 0.002097 \tabularnewline
3 & -0.105708 & -0.9514 & 0.172122 \tabularnewline
4 & 0.178184 & 1.6037 & 0.056341 \tabularnewline
5 & 0.058317 & 0.5249 & 0.300559 \tabularnewline
6 & 0.053273 & 0.4795 & 0.316452 \tabularnewline
7 & 0.014034 & 0.1263 & 0.449902 \tabularnewline
8 & 0.169772 & 1.5279 & 0.065211 \tabularnewline
9 & -0.16321 & -1.4689 & 0.072868 \tabularnewline
10 & -0.377226 & -3.395 & 0.000533 \tabularnewline
11 & -0.023143 & -0.2083 & 0.417763 \tabularnewline
12 & 0.722852 & 6.5057 & 0 \tabularnewline
13 & -0.055348 & -0.4981 & 0.309871 \tabularnewline
14 & -0.297943 & -2.6815 & 0.00444 \tabularnewline
15 & -0.160678 & -1.4461 & 0.076003 \tabularnewline
16 & 0.06479 & 0.5831 & 0.280721 \tabularnewline
17 & 0.023213 & 0.2089 & 0.41752 \tabularnewline
18 & -0.002366 & -0.0213 & 0.491532 \tabularnewline
19 & -0.02632 & -0.2369 & 0.406672 \tabularnewline
20 & 0.147769 & 1.3299 & 0.093638 \tabularnewline
21 & -0.137971 & -1.2417 & 0.108958 \tabularnewline
22 & -0.340388 & -3.0635 & 0.001485 \tabularnewline
23 & 0.004577 & 0.0412 & 0.48362 \tabularnewline
24 & 0.565434 & 5.0889 & 1e-06 \tabularnewline
25 & -0.030999 & -0.279 & 0.390482 \tabularnewline
26 & -0.20008 & -1.8007 & 0.037735 \tabularnewline
27 & -0.147069 & -1.3236 & 0.094677 \tabularnewline
28 & 0.044791 & 0.4031 & 0.343963 \tabularnewline
29 & 0.0599 & 0.5391 & 0.295649 \tabularnewline
30 & -0.030668 & -0.276 & 0.391621 \tabularnewline
31 & -0.025308 & -0.2278 & 0.410199 \tabularnewline
32 & 0.152723 & 1.3745 & 0.086538 \tabularnewline
33 & -0.118946 & -1.0705 & 0.143783 \tabularnewline
34 & -0.29473 & -2.6526 & 0.004805 \tabularnewline
35 & -0.015397 & -0.1386 & 0.445067 \tabularnewline
36 & 0.436368 & 3.9273 & 9e-05 \tabularnewline
37 & -0.016474 & -0.1483 & 0.441252 \tabularnewline
38 & -0.136867 & -1.2318 & 0.110794 \tabularnewline
39 & -0.130533 & -1.1748 & 0.121758 \tabularnewline
40 & 0.032121 & 0.2891 & 0.386628 \tabularnewline
41 & 0.030314 & 0.2728 & 0.39284 \tabularnewline
42 & -0.02678 & -0.241 & 0.405075 \tabularnewline
43 & -0.04555 & -0.4099 & 0.341463 \tabularnewline
44 & 0.126917 & 1.1422 & 0.128358 \tabularnewline
45 & -0.110821 & -0.9974 & 0.160773 \tabularnewline
46 & -0.235955 & -2.1236 & 0.018378 \tabularnewline
47 & -0.017275 & -0.1555 & 0.438417 \tabularnewline
48 & 0.295708 & 2.6614 & 0.004691 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68266&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]0.023406[/C][C]0.2107[/C][C]0.416842[/C][/ROW]
[ROW][C]2[/C][C]-0.327401[/C][C]-2.9466[/C][C]0.002097[/C][/ROW]
[ROW][C]3[/C][C]-0.105708[/C][C]-0.9514[/C][C]0.172122[/C][/ROW]
[ROW][C]4[/C][C]0.178184[/C][C]1.6037[/C][C]0.056341[/C][/ROW]
[ROW][C]5[/C][C]0.058317[/C][C]0.5249[/C][C]0.300559[/C][/ROW]
[ROW][C]6[/C][C]0.053273[/C][C]0.4795[/C][C]0.316452[/C][/ROW]
[ROW][C]7[/C][C]0.014034[/C][C]0.1263[/C][C]0.449902[/C][/ROW]
[ROW][C]8[/C][C]0.169772[/C][C]1.5279[/C][C]0.065211[/C][/ROW]
[ROW][C]9[/C][C]-0.16321[/C][C]-1.4689[/C][C]0.072868[/C][/ROW]
[ROW][C]10[/C][C]-0.377226[/C][C]-3.395[/C][C]0.000533[/C][/ROW]
[ROW][C]11[/C][C]-0.023143[/C][C]-0.2083[/C][C]0.417763[/C][/ROW]
[ROW][C]12[/C][C]0.722852[/C][C]6.5057[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.055348[/C][C]-0.4981[/C][C]0.309871[/C][/ROW]
[ROW][C]14[/C][C]-0.297943[/C][C]-2.6815[/C][C]0.00444[/C][/ROW]
[ROW][C]15[/C][C]-0.160678[/C][C]-1.4461[/C][C]0.076003[/C][/ROW]
[ROW][C]16[/C][C]0.06479[/C][C]0.5831[/C][C]0.280721[/C][/ROW]
[ROW][C]17[/C][C]0.023213[/C][C]0.2089[/C][C]0.41752[/C][/ROW]
[ROW][C]18[/C][C]-0.002366[/C][C]-0.0213[/C][C]0.491532[/C][/ROW]
[ROW][C]19[/C][C]-0.02632[/C][C]-0.2369[/C][C]0.406672[/C][/ROW]
[ROW][C]20[/C][C]0.147769[/C][C]1.3299[/C][C]0.093638[/C][/ROW]
[ROW][C]21[/C][C]-0.137971[/C][C]-1.2417[/C][C]0.108958[/C][/ROW]
[ROW][C]22[/C][C]-0.340388[/C][C]-3.0635[/C][C]0.001485[/C][/ROW]
[ROW][C]23[/C][C]0.004577[/C][C]0.0412[/C][C]0.48362[/C][/ROW]
[ROW][C]24[/C][C]0.565434[/C][C]5.0889[/C][C]1e-06[/C][/ROW]
[ROW][C]25[/C][C]-0.030999[/C][C]-0.279[/C][C]0.390482[/C][/ROW]
[ROW][C]26[/C][C]-0.20008[/C][C]-1.8007[/C][C]0.037735[/C][/ROW]
[ROW][C]27[/C][C]-0.147069[/C][C]-1.3236[/C][C]0.094677[/C][/ROW]
[ROW][C]28[/C][C]0.044791[/C][C]0.4031[/C][C]0.343963[/C][/ROW]
[ROW][C]29[/C][C]0.0599[/C][C]0.5391[/C][C]0.295649[/C][/ROW]
[ROW][C]30[/C][C]-0.030668[/C][C]-0.276[/C][C]0.391621[/C][/ROW]
[ROW][C]31[/C][C]-0.025308[/C][C]-0.2278[/C][C]0.410199[/C][/ROW]
[ROW][C]32[/C][C]0.152723[/C][C]1.3745[/C][C]0.086538[/C][/ROW]
[ROW][C]33[/C][C]-0.118946[/C][C]-1.0705[/C][C]0.143783[/C][/ROW]
[ROW][C]34[/C][C]-0.29473[/C][C]-2.6526[/C][C]0.004805[/C][/ROW]
[ROW][C]35[/C][C]-0.015397[/C][C]-0.1386[/C][C]0.445067[/C][/ROW]
[ROW][C]36[/C][C]0.436368[/C][C]3.9273[/C][C]9e-05[/C][/ROW]
[ROW][C]37[/C][C]-0.016474[/C][C]-0.1483[/C][C]0.441252[/C][/ROW]
[ROW][C]38[/C][C]-0.136867[/C][C]-1.2318[/C][C]0.110794[/C][/ROW]
[ROW][C]39[/C][C]-0.130533[/C][C]-1.1748[/C][C]0.121758[/C][/ROW]
[ROW][C]40[/C][C]0.032121[/C][C]0.2891[/C][C]0.386628[/C][/ROW]
[ROW][C]41[/C][C]0.030314[/C][C]0.2728[/C][C]0.39284[/C][/ROW]
[ROW][C]42[/C][C]-0.02678[/C][C]-0.241[/C][C]0.405075[/C][/ROW]
[ROW][C]43[/C][C]-0.04555[/C][C]-0.4099[/C][C]0.341463[/C][/ROW]
[ROW][C]44[/C][C]0.126917[/C][C]1.1422[/C][C]0.128358[/C][/ROW]
[ROW][C]45[/C][C]-0.110821[/C][C]-0.9974[/C][C]0.160773[/C][/ROW]
[ROW][C]46[/C][C]-0.235955[/C][C]-2.1236[/C][C]0.018378[/C][/ROW]
[ROW][C]47[/C][C]-0.017275[/C][C]-0.1555[/C][C]0.438417[/C][/ROW]
[ROW][C]48[/C][C]0.295708[/C][C]2.6614[/C][C]0.004691[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68266&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68266&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
10.0234060.21070.416842
2-0.327401-2.94660.002097
3-0.105708-0.95140.172122
40.1781841.60370.056341
50.0583170.52490.300559
60.0532730.47950.316452
70.0140340.12630.449902
80.1697721.52790.065211
9-0.16321-1.46890.072868
10-0.377226-3.3950.000533
11-0.023143-0.20830.417763
120.7228526.50570
13-0.055348-0.49810.309871
14-0.297943-2.68150.00444
15-0.160678-1.44610.076003
160.064790.58310.280721
170.0232130.20890.41752
18-0.002366-0.02130.491532
19-0.02632-0.23690.406672
200.1477691.32990.093638
21-0.137971-1.24170.108958
22-0.340388-3.06350.001485
230.0045770.04120.48362
240.5654345.08891e-06
25-0.030999-0.2790.390482
26-0.20008-1.80070.037735
27-0.147069-1.32360.094677
280.0447910.40310.343963
290.05990.53910.295649
30-0.030668-0.2760.391621
31-0.025308-0.22780.410199
320.1527231.37450.086538
33-0.118946-1.07050.143783
34-0.29473-2.65260.004805
35-0.015397-0.13860.445067
360.4363683.92739e-05
37-0.016474-0.14830.441252
38-0.136867-1.23180.110794
39-0.130533-1.17480.121758
400.0321210.28910.386628
410.0303140.27280.39284
42-0.02678-0.2410.405075
43-0.04555-0.40990.341463
440.1269171.14220.128358
45-0.110821-0.99740.160773
46-0.235955-2.12360.018378
47-0.017275-0.15550.438417
480.2957082.66140.004691







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0234060.21070.416842
2-0.328129-2.95320.002058
3-0.098504-0.88650.188976
40.083710.75340.2267
5-0.009799-0.08820.464972
60.1402751.26250.1052
70.0623650.56130.288078
80.2494642.24520.013741
9-0.155195-1.39680.083152
10-0.350125-3.15110.00114
11-0.157931-1.42140.079523
120.6167975.55120
13-0.182189-1.63970.052473
140.0534730.48130.315816
15-0.148956-1.34060.091899
16-0.153825-1.38440.085016
17-0.067222-0.6050.273435
18-0.099212-0.89290.187277
19-0.021127-0.19010.424837
20-0.038988-0.35090.36329
210.1273311.1460.12759
220.0255450.22990.409373
230.0894320.80490.211621
240.0092850.08360.466803
250.0069060.06220.475297
26-0.011511-0.10360.458874
27-0.080163-0.72150.236351
28-0.027717-0.24950.401821
29-0.025094-0.22580.410947
30-0.07796-0.70160.242456
31-0.00608-0.05470.478247
320.0029350.02640.489496
33-0.018099-0.16290.435506
340.0208990.18810.425638
35-0.087494-0.78740.21666
360.0338160.30430.380823
37-0.048297-0.43470.332478
380.0401040.36090.359544
390.0310940.27980.390155
40-0.000198-0.00180.49929
41-0.095559-0.860.196155
420.054790.49310.311635
43-0.140206-1.26190.105312
44-0.066945-0.60250.274261
45-0.059951-0.53960.29549
46-0.007993-0.07190.471413
470.0388290.34950.363825
48-0.097708-0.87940.190901

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.023406 & 0.2107 & 0.416842 \tabularnewline
2 & -0.328129 & -2.9532 & 0.002058 \tabularnewline
3 & -0.098504 & -0.8865 & 0.188976 \tabularnewline
4 & 0.08371 & 0.7534 & 0.2267 \tabularnewline
5 & -0.009799 & -0.0882 & 0.464972 \tabularnewline
6 & 0.140275 & 1.2625 & 0.1052 \tabularnewline
7 & 0.062365 & 0.5613 & 0.288078 \tabularnewline
8 & 0.249464 & 2.2452 & 0.013741 \tabularnewline
9 & -0.155195 & -1.3968 & 0.083152 \tabularnewline
10 & -0.350125 & -3.1511 & 0.00114 \tabularnewline
11 & -0.157931 & -1.4214 & 0.079523 \tabularnewline
12 & 0.616797 & 5.5512 & 0 \tabularnewline
13 & -0.182189 & -1.6397 & 0.052473 \tabularnewline
14 & 0.053473 & 0.4813 & 0.315816 \tabularnewline
15 & -0.148956 & -1.3406 & 0.091899 \tabularnewline
16 & -0.153825 & -1.3844 & 0.085016 \tabularnewline
17 & -0.067222 & -0.605 & 0.273435 \tabularnewline
18 & -0.099212 & -0.8929 & 0.187277 \tabularnewline
19 & -0.021127 & -0.1901 & 0.424837 \tabularnewline
20 & -0.038988 & -0.3509 & 0.36329 \tabularnewline
21 & 0.127331 & 1.146 & 0.12759 \tabularnewline
22 & 0.025545 & 0.2299 & 0.409373 \tabularnewline
23 & 0.089432 & 0.8049 & 0.211621 \tabularnewline
24 & 0.009285 & 0.0836 & 0.466803 \tabularnewline
25 & 0.006906 & 0.0622 & 0.475297 \tabularnewline
26 & -0.011511 & -0.1036 & 0.458874 \tabularnewline
27 & -0.080163 & -0.7215 & 0.236351 \tabularnewline
28 & -0.027717 & -0.2495 & 0.401821 \tabularnewline
29 & -0.025094 & -0.2258 & 0.410947 \tabularnewline
30 & -0.07796 & -0.7016 & 0.242456 \tabularnewline
31 & -0.00608 & -0.0547 & 0.478247 \tabularnewline
32 & 0.002935 & 0.0264 & 0.489496 \tabularnewline
33 & -0.018099 & -0.1629 & 0.435506 \tabularnewline
34 & 0.020899 & 0.1881 & 0.425638 \tabularnewline
35 & -0.087494 & -0.7874 & 0.21666 \tabularnewline
36 & 0.033816 & 0.3043 & 0.380823 \tabularnewline
37 & -0.048297 & -0.4347 & 0.332478 \tabularnewline
38 & 0.040104 & 0.3609 & 0.359544 \tabularnewline
39 & 0.031094 & 0.2798 & 0.390155 \tabularnewline
40 & -0.000198 & -0.0018 & 0.49929 \tabularnewline
41 & -0.095559 & -0.86 & 0.196155 \tabularnewline
42 & 0.05479 & 0.4931 & 0.311635 \tabularnewline
43 & -0.140206 & -1.2619 & 0.105312 \tabularnewline
44 & -0.066945 & -0.6025 & 0.274261 \tabularnewline
45 & -0.059951 & -0.5396 & 0.29549 \tabularnewline
46 & -0.007993 & -0.0719 & 0.471413 \tabularnewline
47 & 0.038829 & 0.3495 & 0.363825 \tabularnewline
48 & -0.097708 & -0.8794 & 0.190901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68266&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]0.023406[/C][C]0.2107[/C][C]0.416842[/C][/ROW]
[ROW][C]2[/C][C]-0.328129[/C][C]-2.9532[/C][C]0.002058[/C][/ROW]
[ROW][C]3[/C][C]-0.098504[/C][C]-0.8865[/C][C]0.188976[/C][/ROW]
[ROW][C]4[/C][C]0.08371[/C][C]0.7534[/C][C]0.2267[/C][/ROW]
[ROW][C]5[/C][C]-0.009799[/C][C]-0.0882[/C][C]0.464972[/C][/ROW]
[ROW][C]6[/C][C]0.140275[/C][C]1.2625[/C][C]0.1052[/C][/ROW]
[ROW][C]7[/C][C]0.062365[/C][C]0.5613[/C][C]0.288078[/C][/ROW]
[ROW][C]8[/C][C]0.249464[/C][C]2.2452[/C][C]0.013741[/C][/ROW]
[ROW][C]9[/C][C]-0.155195[/C][C]-1.3968[/C][C]0.083152[/C][/ROW]
[ROW][C]10[/C][C]-0.350125[/C][C]-3.1511[/C][C]0.00114[/C][/ROW]
[ROW][C]11[/C][C]-0.157931[/C][C]-1.4214[/C][C]0.079523[/C][/ROW]
[ROW][C]12[/C][C]0.616797[/C][C]5.5512[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.182189[/C][C]-1.6397[/C][C]0.052473[/C][/ROW]
[ROW][C]14[/C][C]0.053473[/C][C]0.4813[/C][C]0.315816[/C][/ROW]
[ROW][C]15[/C][C]-0.148956[/C][C]-1.3406[/C][C]0.091899[/C][/ROW]
[ROW][C]16[/C][C]-0.153825[/C][C]-1.3844[/C][C]0.085016[/C][/ROW]
[ROW][C]17[/C][C]-0.067222[/C][C]-0.605[/C][C]0.273435[/C][/ROW]
[ROW][C]18[/C][C]-0.099212[/C][C]-0.8929[/C][C]0.187277[/C][/ROW]
[ROW][C]19[/C][C]-0.021127[/C][C]-0.1901[/C][C]0.424837[/C][/ROW]
[ROW][C]20[/C][C]-0.038988[/C][C]-0.3509[/C][C]0.36329[/C][/ROW]
[ROW][C]21[/C][C]0.127331[/C][C]1.146[/C][C]0.12759[/C][/ROW]
[ROW][C]22[/C][C]0.025545[/C][C]0.2299[/C][C]0.409373[/C][/ROW]
[ROW][C]23[/C][C]0.089432[/C][C]0.8049[/C][C]0.211621[/C][/ROW]
[ROW][C]24[/C][C]0.009285[/C][C]0.0836[/C][C]0.466803[/C][/ROW]
[ROW][C]25[/C][C]0.006906[/C][C]0.0622[/C][C]0.475297[/C][/ROW]
[ROW][C]26[/C][C]-0.011511[/C][C]-0.1036[/C][C]0.458874[/C][/ROW]
[ROW][C]27[/C][C]-0.080163[/C][C]-0.7215[/C][C]0.236351[/C][/ROW]
[ROW][C]28[/C][C]-0.027717[/C][C]-0.2495[/C][C]0.401821[/C][/ROW]
[ROW][C]29[/C][C]-0.025094[/C][C]-0.2258[/C][C]0.410947[/C][/ROW]
[ROW][C]30[/C][C]-0.07796[/C][C]-0.7016[/C][C]0.242456[/C][/ROW]
[ROW][C]31[/C][C]-0.00608[/C][C]-0.0547[/C][C]0.478247[/C][/ROW]
[ROW][C]32[/C][C]0.002935[/C][C]0.0264[/C][C]0.489496[/C][/ROW]
[ROW][C]33[/C][C]-0.018099[/C][C]-0.1629[/C][C]0.435506[/C][/ROW]
[ROW][C]34[/C][C]0.020899[/C][C]0.1881[/C][C]0.425638[/C][/ROW]
[ROW][C]35[/C][C]-0.087494[/C][C]-0.7874[/C][C]0.21666[/C][/ROW]
[ROW][C]36[/C][C]0.033816[/C][C]0.3043[/C][C]0.380823[/C][/ROW]
[ROW][C]37[/C][C]-0.048297[/C][C]-0.4347[/C][C]0.332478[/C][/ROW]
[ROW][C]38[/C][C]0.040104[/C][C]0.3609[/C][C]0.359544[/C][/ROW]
[ROW][C]39[/C][C]0.031094[/C][C]0.2798[/C][C]0.390155[/C][/ROW]
[ROW][C]40[/C][C]-0.000198[/C][C]-0.0018[/C][C]0.49929[/C][/ROW]
[ROW][C]41[/C][C]-0.095559[/C][C]-0.86[/C][C]0.196155[/C][/ROW]
[ROW][C]42[/C][C]0.05479[/C][C]0.4931[/C][C]0.311635[/C][/ROW]
[ROW][C]43[/C][C]-0.140206[/C][C]-1.2619[/C][C]0.105312[/C][/ROW]
[ROW][C]44[/C][C]-0.066945[/C][C]-0.6025[/C][C]0.274261[/C][/ROW]
[ROW][C]45[/C][C]-0.059951[/C][C]-0.5396[/C][C]0.29549[/C][/ROW]
[ROW][C]46[/C][C]-0.007993[/C][C]-0.0719[/C][C]0.471413[/C][/ROW]
[ROW][C]47[/C][C]0.038829[/C][C]0.3495[/C][C]0.363825[/C][/ROW]
[ROW][C]48[/C][C]-0.097708[/C][C]-0.8794[/C][C]0.190901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68266&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68266&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
10.0234060.21070.416842
2-0.328129-2.95320.002058
3-0.098504-0.88650.188976
40.083710.75340.2267
5-0.009799-0.08820.464972
60.1402751.26250.1052
70.0623650.56130.288078
80.2494642.24520.013741
9-0.155195-1.39680.083152
10-0.350125-3.15110.00114
11-0.157931-1.42140.079523
120.6167975.55120
13-0.182189-1.63970.052473
140.0534730.48130.315816
15-0.148956-1.34060.091899
16-0.153825-1.38440.085016
17-0.067222-0.6050.273435
18-0.099212-0.89290.187277
19-0.021127-0.19010.424837
20-0.038988-0.35090.36329
210.1273311.1460.12759
220.0255450.22990.409373
230.0894320.80490.211621
240.0092850.08360.466803
250.0069060.06220.475297
26-0.011511-0.10360.458874
27-0.080163-0.72150.236351
28-0.027717-0.24950.401821
29-0.025094-0.22580.410947
30-0.07796-0.70160.242456
31-0.00608-0.05470.478247
320.0029350.02640.489496
33-0.018099-0.16290.435506
340.0208990.18810.425638
35-0.087494-0.78740.21666
360.0338160.30430.380823
37-0.048297-0.43470.332478
380.0401040.36090.359544
390.0310940.27980.390155
40-0.000198-0.00180.49929
41-0.095559-0.860.196155
420.054790.49310.311635
43-0.140206-1.26190.105312
44-0.066945-0.60250.274261
45-0.059951-0.53960.29549
46-0.007993-0.07190.471413
470.0388290.34950.363825
48-0.097708-0.87940.190901



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')