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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 16 Aug 2009 09:12:19 -0600
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/Aug/16/t1250435562q3r0j42eoura6r3.htm/, Retrieved Sun, 05 May 2024 15:34:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42643, Retrieved Sun, 05 May 2024 15:34:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Maarten Verhaegen...] [2008-08-17 13:34:14] [b57209f6d0b19d479b8c06a8ae81c48a]
- RMPD    [(Partial) Autocorrelation Function] [] [2009-08-16 15:12:19] [0d1085ed835696cdd537ad5fa07600ec] [Current]
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Dataseries X:
72.84
73.96
73.26
73.86
73.04
212.8
157.92
111.55
99.01
89.5
100.95
116.06
131.5
137.43
138.53
137.26
136.81
182.98
149.45
109.34
93.37
84.09
83.83
82.94
82.88
81.41
79.87
79.66
76.07
182.69
165.78
142.5
120.6
105.73
98.72
98.41
96.08
97.3
97.5
97.02
98.75
232.81
240.83
193.4
148.28
138.34
135.34
134.02
133.86
131.67
132.43
130.21
129.98
206.16
195.17
159.16
136.33
125.18
121.21
119.38
119.26
119.75
118.78
116.97
121.69
223.51
228.58
205.22
189.4
180.14
177.59
176.39
171.16
173.11
171.74
175.97
179.64
254.62
240.5
212.01
176.36
153.24
146.69
141.52
142.6
143.19
142.32
142.03
144.92
177.31
194.4
189.19
180.44
175.84
178.54
176.55




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=42643&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=42643&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42643&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
10.7348797.20030
20.4516684.42541.3e-05
30.2681142.6270.005014
40.1682551.64860.051254
50.112951.10670.135598
60.1184381.16050.124371
70.1104431.08210.140956
80.0988980.9690.167491
90.119551.17140.122178
100.2056032.01450.023378
110.3818353.74120.000156
120.5584525.47170
130.3877433.79910.000127
140.19081.86950.032304
150.0788470.77250.220847
160.0379240.37160.355513
170.0257310.25210.400746
180.0270160.26470.395902
190.0152920.14980.440606
200.007150.07010.472147
210.028020.27450.392129
220.1126971.10420.136132
230.2946892.88740.0024
240.5024794.92332e-06
250.3799573.72280.000166
260.2091782.04950.02157
270.0830890.81410.2088
280.0103590.10150.459685
29-0.040652-0.39830.345643
30-0.059308-0.58110.281268
31-0.086999-0.85240.198053
32-0.097193-0.95230.17167
33-0.083888-0.82190.206577
34-0.019185-0.1880.425647
350.1215181.19060.118368
360.2911172.85240.002657
370.174571.71040.045208
38-0.001253-0.01230.495115
39-0.130809-1.28170.101524
40-0.196224-1.92260.028747
41-0.238863-2.34040.010667
42-0.237096-2.32310.011144
43-0.232017-2.27330.012619
44-0.224672-2.20130.015054
45-0.211758-2.07480.020341
46-0.167603-1.64220.051913
47-0.068916-0.67520.250574
480.0559620.54830.292373

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.734879 & 7.2003 & 0 \tabularnewline
2 & 0.451668 & 4.4254 & 1.3e-05 \tabularnewline
3 & 0.268114 & 2.627 & 0.005014 \tabularnewline
4 & 0.168255 & 1.6486 & 0.051254 \tabularnewline
5 & 0.11295 & 1.1067 & 0.135598 \tabularnewline
6 & 0.118438 & 1.1605 & 0.124371 \tabularnewline
7 & 0.110443 & 1.0821 & 0.140956 \tabularnewline
8 & 0.098898 & 0.969 & 0.167491 \tabularnewline
9 & 0.11955 & 1.1714 & 0.122178 \tabularnewline
10 & 0.205603 & 2.0145 & 0.023378 \tabularnewline
11 & 0.381835 & 3.7412 & 0.000156 \tabularnewline
12 & 0.558452 & 5.4717 & 0 \tabularnewline
13 & 0.387743 & 3.7991 & 0.000127 \tabularnewline
14 & 0.1908 & 1.8695 & 0.032304 \tabularnewline
15 & 0.078847 & 0.7725 & 0.220847 \tabularnewline
16 & 0.037924 & 0.3716 & 0.355513 \tabularnewline
17 & 0.025731 & 0.2521 & 0.400746 \tabularnewline
18 & 0.027016 & 0.2647 & 0.395902 \tabularnewline
19 & 0.015292 & 0.1498 & 0.440606 \tabularnewline
20 & 0.00715 & 0.0701 & 0.472147 \tabularnewline
21 & 0.02802 & 0.2745 & 0.392129 \tabularnewline
22 & 0.112697 & 1.1042 & 0.136132 \tabularnewline
23 & 0.294689 & 2.8874 & 0.0024 \tabularnewline
24 & 0.502479 & 4.9233 & 2e-06 \tabularnewline
25 & 0.379957 & 3.7228 & 0.000166 \tabularnewline
26 & 0.209178 & 2.0495 & 0.02157 \tabularnewline
27 & 0.083089 & 0.8141 & 0.2088 \tabularnewline
28 & 0.010359 & 0.1015 & 0.459685 \tabularnewline
29 & -0.040652 & -0.3983 & 0.345643 \tabularnewline
30 & -0.059308 & -0.5811 & 0.281268 \tabularnewline
31 & -0.086999 & -0.8524 & 0.198053 \tabularnewline
32 & -0.097193 & -0.9523 & 0.17167 \tabularnewline
33 & -0.083888 & -0.8219 & 0.206577 \tabularnewline
34 & -0.019185 & -0.188 & 0.425647 \tabularnewline
35 & 0.121518 & 1.1906 & 0.118368 \tabularnewline
36 & 0.291117 & 2.8524 & 0.002657 \tabularnewline
37 & 0.17457 & 1.7104 & 0.045208 \tabularnewline
38 & -0.001253 & -0.0123 & 0.495115 \tabularnewline
39 & -0.130809 & -1.2817 & 0.101524 \tabularnewline
40 & -0.196224 & -1.9226 & 0.028747 \tabularnewline
41 & -0.238863 & -2.3404 & 0.010667 \tabularnewline
42 & -0.237096 & -2.3231 & 0.011144 \tabularnewline
43 & -0.232017 & -2.2733 & 0.012619 \tabularnewline
44 & -0.224672 & -2.2013 & 0.015054 \tabularnewline
45 & -0.211758 & -2.0748 & 0.020341 \tabularnewline
46 & -0.167603 & -1.6422 & 0.051913 \tabularnewline
47 & -0.068916 & -0.6752 & 0.250574 \tabularnewline
48 & 0.055962 & 0.5483 & 0.292373 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42643&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]0.734879[/C][C]7.2003[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.451668[/C][C]4.4254[/C][C]1.3e-05[/C][/ROW]
[ROW][C]3[/C][C]0.268114[/C][C]2.627[/C][C]0.005014[/C][/ROW]
[ROW][C]4[/C][C]0.168255[/C][C]1.6486[/C][C]0.051254[/C][/ROW]
[ROW][C]5[/C][C]0.11295[/C][C]1.1067[/C][C]0.135598[/C][/ROW]
[ROW][C]6[/C][C]0.118438[/C][C]1.1605[/C][C]0.124371[/C][/ROW]
[ROW][C]7[/C][C]0.110443[/C][C]1.0821[/C][C]0.140956[/C][/ROW]
[ROW][C]8[/C][C]0.098898[/C][C]0.969[/C][C]0.167491[/C][/ROW]
[ROW][C]9[/C][C]0.11955[/C][C]1.1714[/C][C]0.122178[/C][/ROW]
[ROW][C]10[/C][C]0.205603[/C][C]2.0145[/C][C]0.023378[/C][/ROW]
[ROW][C]11[/C][C]0.381835[/C][C]3.7412[/C][C]0.000156[/C][/ROW]
[ROW][C]12[/C][C]0.558452[/C][C]5.4717[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.387743[/C][C]3.7991[/C][C]0.000127[/C][/ROW]
[ROW][C]14[/C][C]0.1908[/C][C]1.8695[/C][C]0.032304[/C][/ROW]
[ROW][C]15[/C][C]0.078847[/C][C]0.7725[/C][C]0.220847[/C][/ROW]
[ROW][C]16[/C][C]0.037924[/C][C]0.3716[/C][C]0.355513[/C][/ROW]
[ROW][C]17[/C][C]0.025731[/C][C]0.2521[/C][C]0.400746[/C][/ROW]
[ROW][C]18[/C][C]0.027016[/C][C]0.2647[/C][C]0.395902[/C][/ROW]
[ROW][C]19[/C][C]0.015292[/C][C]0.1498[/C][C]0.440606[/C][/ROW]
[ROW][C]20[/C][C]0.00715[/C][C]0.0701[/C][C]0.472147[/C][/ROW]
[ROW][C]21[/C][C]0.02802[/C][C]0.2745[/C][C]0.392129[/C][/ROW]
[ROW][C]22[/C][C]0.112697[/C][C]1.1042[/C][C]0.136132[/C][/ROW]
[ROW][C]23[/C][C]0.294689[/C][C]2.8874[/C][C]0.0024[/C][/ROW]
[ROW][C]24[/C][C]0.502479[/C][C]4.9233[/C][C]2e-06[/C][/ROW]
[ROW][C]25[/C][C]0.379957[/C][C]3.7228[/C][C]0.000166[/C][/ROW]
[ROW][C]26[/C][C]0.209178[/C][C]2.0495[/C][C]0.02157[/C][/ROW]
[ROW][C]27[/C][C]0.083089[/C][C]0.8141[/C][C]0.2088[/C][/ROW]
[ROW][C]28[/C][C]0.010359[/C][C]0.1015[/C][C]0.459685[/C][/ROW]
[ROW][C]29[/C][C]-0.040652[/C][C]-0.3983[/C][C]0.345643[/C][/ROW]
[ROW][C]30[/C][C]-0.059308[/C][C]-0.5811[/C][C]0.281268[/C][/ROW]
[ROW][C]31[/C][C]-0.086999[/C][C]-0.8524[/C][C]0.198053[/C][/ROW]
[ROW][C]32[/C][C]-0.097193[/C][C]-0.9523[/C][C]0.17167[/C][/ROW]
[ROW][C]33[/C][C]-0.083888[/C][C]-0.8219[/C][C]0.206577[/C][/ROW]
[ROW][C]34[/C][C]-0.019185[/C][C]-0.188[/C][C]0.425647[/C][/ROW]
[ROW][C]35[/C][C]0.121518[/C][C]1.1906[/C][C]0.118368[/C][/ROW]
[ROW][C]36[/C][C]0.291117[/C][C]2.8524[/C][C]0.002657[/C][/ROW]
[ROW][C]37[/C][C]0.17457[/C][C]1.7104[/C][C]0.045208[/C][/ROW]
[ROW][C]38[/C][C]-0.001253[/C][C]-0.0123[/C][C]0.495115[/C][/ROW]
[ROW][C]39[/C][C]-0.130809[/C][C]-1.2817[/C][C]0.101524[/C][/ROW]
[ROW][C]40[/C][C]-0.196224[/C][C]-1.9226[/C][C]0.028747[/C][/ROW]
[ROW][C]41[/C][C]-0.238863[/C][C]-2.3404[/C][C]0.010667[/C][/ROW]
[ROW][C]42[/C][C]-0.237096[/C][C]-2.3231[/C][C]0.011144[/C][/ROW]
[ROW][C]43[/C][C]-0.232017[/C][C]-2.2733[/C][C]0.012619[/C][/ROW]
[ROW][C]44[/C][C]-0.224672[/C][C]-2.2013[/C][C]0.015054[/C][/ROW]
[ROW][C]45[/C][C]-0.211758[/C][C]-2.0748[/C][C]0.020341[/C][/ROW]
[ROW][C]46[/C][C]-0.167603[/C][C]-1.6422[/C][C]0.051913[/C][/ROW]
[ROW][C]47[/C][C]-0.068916[/C][C]-0.6752[/C][C]0.250574[/C][/ROW]
[ROW][C]48[/C][C]0.055962[/C][C]0.5483[/C][C]0.292373[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42643&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42643&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
10.7348797.20030
20.4516684.42541.3e-05
30.2681142.6270.005014
40.1682551.64860.051254
50.112951.10670.135598
60.1184381.16050.124371
70.1104431.08210.140956
80.0988980.9690.167491
90.119551.17140.122178
100.2056032.01450.023378
110.3818353.74120.000156
120.5584525.47170
130.3877433.79910.000127
140.19081.86950.032304
150.0788470.77250.220847
160.0379240.37160.355513
170.0257310.25210.400746
180.0270160.26470.395902
190.0152920.14980.440606
200.007150.07010.472147
210.028020.27450.392129
220.1126971.10420.136132
230.2946892.88740.0024
240.5024794.92332e-06
250.3799573.72280.000166
260.2091782.04950.02157
270.0830890.81410.2088
280.0103590.10150.459685
29-0.040652-0.39830.345643
30-0.059308-0.58110.281268
31-0.086999-0.85240.198053
32-0.097193-0.95230.17167
33-0.083888-0.82190.206577
34-0.019185-0.1880.425647
350.1215181.19060.118368
360.2911172.85240.002657
370.174571.71040.045208
38-0.001253-0.01230.495115
39-0.130809-1.28170.101524
40-0.196224-1.92260.028747
41-0.238863-2.34040.010667
42-0.237096-2.32310.011144
43-0.232017-2.27330.012619
44-0.224672-2.20130.015054
45-0.211758-2.07480.020341
46-0.167603-1.64220.051913
47-0.068916-0.67520.250574
480.0559620.54830.292373







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7348797.20030
2-0.192147-1.88260.031388
30.0307440.30120.381944
40.0183930.18020.428681
50.0050370.04940.480369
60.092450.90580.18365
7-0.032627-0.31970.374955
80.0258760.25350.400199
90.0842610.82560.205543
100.1717691.6830.047814
110.3168773.10470.001252
120.2590372.5380.006379
13-0.528398-5.17721e-06
140.0629470.61680.269429
150.0587510.57560.283101
160.0442050.43310.33295
170.0215680.21130.416542
18-0.194316-1.90390.029959
190.0136440.13370.446968
200.1338331.31130.096443
210.0403310.39520.346801
220.0868410.85090.198482
230.0917690.89920.185411
240.1832731.79570.037844
25-0.203526-1.99410.024487
260.0157950.15480.438668
27-0.086746-0.84990.198737
28-0.048818-0.47830.316758
29-0.02141-0.20980.417145
30-0.065279-0.63960.261976
31-0.066287-0.64950.258792
320.0607880.59560.276422
33-0.032936-0.32270.373809
340.0100080.09810.461047
35-0.049392-0.48390.314763
36-0.031195-0.30560.380267
37-0.09904-0.97040.167144
38-0.082271-0.80610.211093
39-0.058965-0.57770.282398
40-0.041389-0.40550.342996
41-0.079327-0.77720.219463
420.0246510.24150.404829
43-0.008222-0.08060.46798
44-0.016394-0.16060.436363
45-0.041767-0.40920.341642
46-0.073284-0.7180.237241
47-0.106684-1.04530.149257
48-0.131166-1.28520.100914

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.734879 & 7.2003 & 0 \tabularnewline
2 & -0.192147 & -1.8826 & 0.031388 \tabularnewline
3 & 0.030744 & 0.3012 & 0.381944 \tabularnewline
4 & 0.018393 & 0.1802 & 0.428681 \tabularnewline
5 & 0.005037 & 0.0494 & 0.480369 \tabularnewline
6 & 0.09245 & 0.9058 & 0.18365 \tabularnewline
7 & -0.032627 & -0.3197 & 0.374955 \tabularnewline
8 & 0.025876 & 0.2535 & 0.400199 \tabularnewline
9 & 0.084261 & 0.8256 & 0.205543 \tabularnewline
10 & 0.171769 & 1.683 & 0.047814 \tabularnewline
11 & 0.316877 & 3.1047 & 0.001252 \tabularnewline
12 & 0.259037 & 2.538 & 0.006379 \tabularnewline
13 & -0.528398 & -5.1772 & 1e-06 \tabularnewline
14 & 0.062947 & 0.6168 & 0.269429 \tabularnewline
15 & 0.058751 & 0.5756 & 0.283101 \tabularnewline
16 & 0.044205 & 0.4331 & 0.33295 \tabularnewline
17 & 0.021568 & 0.2113 & 0.416542 \tabularnewline
18 & -0.194316 & -1.9039 & 0.029959 \tabularnewline
19 & 0.013644 & 0.1337 & 0.446968 \tabularnewline
20 & 0.133833 & 1.3113 & 0.096443 \tabularnewline
21 & 0.040331 & 0.3952 & 0.346801 \tabularnewline
22 & 0.086841 & 0.8509 & 0.198482 \tabularnewline
23 & 0.091769 & 0.8992 & 0.185411 \tabularnewline
24 & 0.183273 & 1.7957 & 0.037844 \tabularnewline
25 & -0.203526 & -1.9941 & 0.024487 \tabularnewline
26 & 0.015795 & 0.1548 & 0.438668 \tabularnewline
27 & -0.086746 & -0.8499 & 0.198737 \tabularnewline
28 & -0.048818 & -0.4783 & 0.316758 \tabularnewline
29 & -0.02141 & -0.2098 & 0.417145 \tabularnewline
30 & -0.065279 & -0.6396 & 0.261976 \tabularnewline
31 & -0.066287 & -0.6495 & 0.258792 \tabularnewline
32 & 0.060788 & 0.5956 & 0.276422 \tabularnewline
33 & -0.032936 & -0.3227 & 0.373809 \tabularnewline
34 & 0.010008 & 0.0981 & 0.461047 \tabularnewline
35 & -0.049392 & -0.4839 & 0.314763 \tabularnewline
36 & -0.031195 & -0.3056 & 0.380267 \tabularnewline
37 & -0.09904 & -0.9704 & 0.167144 \tabularnewline
38 & -0.082271 & -0.8061 & 0.211093 \tabularnewline
39 & -0.058965 & -0.5777 & 0.282398 \tabularnewline
40 & -0.041389 & -0.4055 & 0.342996 \tabularnewline
41 & -0.079327 & -0.7772 & 0.219463 \tabularnewline
42 & 0.024651 & 0.2415 & 0.404829 \tabularnewline
43 & -0.008222 & -0.0806 & 0.46798 \tabularnewline
44 & -0.016394 & -0.1606 & 0.436363 \tabularnewline
45 & -0.041767 & -0.4092 & 0.341642 \tabularnewline
46 & -0.073284 & -0.718 & 0.237241 \tabularnewline
47 & -0.106684 & -1.0453 & 0.149257 \tabularnewline
48 & -0.131166 & -1.2852 & 0.100914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42643&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]0.734879[/C][C]7.2003[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.192147[/C][C]-1.8826[/C][C]0.031388[/C][/ROW]
[ROW][C]3[/C][C]0.030744[/C][C]0.3012[/C][C]0.381944[/C][/ROW]
[ROW][C]4[/C][C]0.018393[/C][C]0.1802[/C][C]0.428681[/C][/ROW]
[ROW][C]5[/C][C]0.005037[/C][C]0.0494[/C][C]0.480369[/C][/ROW]
[ROW][C]6[/C][C]0.09245[/C][C]0.9058[/C][C]0.18365[/C][/ROW]
[ROW][C]7[/C][C]-0.032627[/C][C]-0.3197[/C][C]0.374955[/C][/ROW]
[ROW][C]8[/C][C]0.025876[/C][C]0.2535[/C][C]0.400199[/C][/ROW]
[ROW][C]9[/C][C]0.084261[/C][C]0.8256[/C][C]0.205543[/C][/ROW]
[ROW][C]10[/C][C]0.171769[/C][C]1.683[/C][C]0.047814[/C][/ROW]
[ROW][C]11[/C][C]0.316877[/C][C]3.1047[/C][C]0.001252[/C][/ROW]
[ROW][C]12[/C][C]0.259037[/C][C]2.538[/C][C]0.006379[/C][/ROW]
[ROW][C]13[/C][C]-0.528398[/C][C]-5.1772[/C][C]1e-06[/C][/ROW]
[ROW][C]14[/C][C]0.062947[/C][C]0.6168[/C][C]0.269429[/C][/ROW]
[ROW][C]15[/C][C]0.058751[/C][C]0.5756[/C][C]0.283101[/C][/ROW]
[ROW][C]16[/C][C]0.044205[/C][C]0.4331[/C][C]0.33295[/C][/ROW]
[ROW][C]17[/C][C]0.021568[/C][C]0.2113[/C][C]0.416542[/C][/ROW]
[ROW][C]18[/C][C]-0.194316[/C][C]-1.9039[/C][C]0.029959[/C][/ROW]
[ROW][C]19[/C][C]0.013644[/C][C]0.1337[/C][C]0.446968[/C][/ROW]
[ROW][C]20[/C][C]0.133833[/C][C]1.3113[/C][C]0.096443[/C][/ROW]
[ROW][C]21[/C][C]0.040331[/C][C]0.3952[/C][C]0.346801[/C][/ROW]
[ROW][C]22[/C][C]0.086841[/C][C]0.8509[/C][C]0.198482[/C][/ROW]
[ROW][C]23[/C][C]0.091769[/C][C]0.8992[/C][C]0.185411[/C][/ROW]
[ROW][C]24[/C][C]0.183273[/C][C]1.7957[/C][C]0.037844[/C][/ROW]
[ROW][C]25[/C][C]-0.203526[/C][C]-1.9941[/C][C]0.024487[/C][/ROW]
[ROW][C]26[/C][C]0.015795[/C][C]0.1548[/C][C]0.438668[/C][/ROW]
[ROW][C]27[/C][C]-0.086746[/C][C]-0.8499[/C][C]0.198737[/C][/ROW]
[ROW][C]28[/C][C]-0.048818[/C][C]-0.4783[/C][C]0.316758[/C][/ROW]
[ROW][C]29[/C][C]-0.02141[/C][C]-0.2098[/C][C]0.417145[/C][/ROW]
[ROW][C]30[/C][C]-0.065279[/C][C]-0.6396[/C][C]0.261976[/C][/ROW]
[ROW][C]31[/C][C]-0.066287[/C][C]-0.6495[/C][C]0.258792[/C][/ROW]
[ROW][C]32[/C][C]0.060788[/C][C]0.5956[/C][C]0.276422[/C][/ROW]
[ROW][C]33[/C][C]-0.032936[/C][C]-0.3227[/C][C]0.373809[/C][/ROW]
[ROW][C]34[/C][C]0.010008[/C][C]0.0981[/C][C]0.461047[/C][/ROW]
[ROW][C]35[/C][C]-0.049392[/C][C]-0.4839[/C][C]0.314763[/C][/ROW]
[ROW][C]36[/C][C]-0.031195[/C][C]-0.3056[/C][C]0.380267[/C][/ROW]
[ROW][C]37[/C][C]-0.09904[/C][C]-0.9704[/C][C]0.167144[/C][/ROW]
[ROW][C]38[/C][C]-0.082271[/C][C]-0.8061[/C][C]0.211093[/C][/ROW]
[ROW][C]39[/C][C]-0.058965[/C][C]-0.5777[/C][C]0.282398[/C][/ROW]
[ROW][C]40[/C][C]-0.041389[/C][C]-0.4055[/C][C]0.342996[/C][/ROW]
[ROW][C]41[/C][C]-0.079327[/C][C]-0.7772[/C][C]0.219463[/C][/ROW]
[ROW][C]42[/C][C]0.024651[/C][C]0.2415[/C][C]0.404829[/C][/ROW]
[ROW][C]43[/C][C]-0.008222[/C][C]-0.0806[/C][C]0.46798[/C][/ROW]
[ROW][C]44[/C][C]-0.016394[/C][C]-0.1606[/C][C]0.436363[/C][/ROW]
[ROW][C]45[/C][C]-0.041767[/C][C]-0.4092[/C][C]0.341642[/C][/ROW]
[ROW][C]46[/C][C]-0.073284[/C][C]-0.718[/C][C]0.237241[/C][/ROW]
[ROW][C]47[/C][C]-0.106684[/C][C]-1.0453[/C][C]0.149257[/C][/ROW]
[ROW][C]48[/C][C]-0.131166[/C][C]-1.2852[/C][C]0.100914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42643&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42643&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
10.7348797.20030
2-0.192147-1.88260.031388
30.0307440.30120.381944
40.0183930.18020.428681
50.0050370.04940.480369
60.092450.90580.18365
7-0.032627-0.31970.374955
80.0258760.25350.400199
90.0842610.82560.205543
100.1717691.6830.047814
110.3168773.10470.001252
120.2590372.5380.006379
13-0.528398-5.17721e-06
140.0629470.61680.269429
150.0587510.57560.283101
160.0442050.43310.33295
170.0215680.21130.416542
18-0.194316-1.90390.029959
190.0136440.13370.446968
200.1338331.31130.096443
210.0403310.39520.346801
220.0868410.85090.198482
230.0917690.89920.185411
240.1832731.79570.037844
25-0.203526-1.99410.024487
260.0157950.15480.438668
27-0.086746-0.84990.198737
28-0.048818-0.47830.316758
29-0.02141-0.20980.417145
30-0.065279-0.63960.261976
31-0.066287-0.64950.258792
320.0607880.59560.276422
33-0.032936-0.32270.373809
340.0100080.09810.461047
35-0.049392-0.48390.314763
36-0.031195-0.30560.380267
37-0.09904-0.97040.167144
38-0.082271-0.80610.211093
39-0.058965-0.57770.282398
40-0.041389-0.40550.342996
41-0.079327-0.77720.219463
420.0246510.24150.404829
43-0.008222-0.08060.46798
44-0.016394-0.16060.436363
45-0.041767-0.40920.341642
46-0.073284-0.7180.237241
47-0.106684-1.04530.149257
48-0.131166-1.28520.100914



Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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 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')