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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, 09 Dec 2008 11:18:10 -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/2008/Dec/09/t1228847673dzwm122lcoo4zh7.htm/, Retrieved Tue, 28 May 2024 01:03:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31674, Retrieved Tue, 28 May 2024 01:03:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsjenske_cole@hotmail.com
Estimated Impact140
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]
- RMPD    [(Partial) Autocorrelation Function] [eigen tijdreeks p...] [2008-12-09 18:18:10] [120dfa2440e51a0cfc0f5296bc5d7460] [Current]
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Dataseries X:
98.6
98
106.8
96.6
100.1
107.7
91.5
97.8
107.4
117.5
105.6
97.4
99.5
98
104.3
100.6
101.1
103.9
96.9
95.5
108.4
117
103.8
100.8
110.6
104
112.6
107.3
98.9
109.8
104.9
102.2
123.9
124.9
112.7
121.9
100.6
104.3
120.4
107.5
102.9
125.6
107.5
108.8
128.4
121.1
119.5
128.7
108.7
105.5
119.8
111.3
110.6
120.1
97.5
107.7
127.3
117.2
119.8
116.2
111
112.4
130.6
109.1
118.8
123.9
101.6
112.8
128
129.6
125.8
119.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31674&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31674&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31674&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1431891.10910.135898
20.0855760.66290.254975
30.2633372.03980.02289
4-0.023449-0.18160.42824
50.0870770.67450.251293
60.1913571.48220.071754
7-0.135291-1.0480.149429
80.1152820.8930.18772
90.2021631.56590.06131
10-0.207435-1.60680.056676
11-0.057854-0.44810.327834
12-0.204951-1.58750.058823
13-0.253044-1.96010.027318
140.0924820.71640.238274
15-0.135341-1.04830.149343
16-0.184691-1.43060.078864
170.1533941.18820.119722
18-0.1473-1.1410.129206
19-0.180209-1.39590.083945
20-0.041983-0.32520.373081
21-0.135291-1.0480.149431
22-0.138711-1.07450.143461
230.0793040.61430.270673
24-0.257669-1.99590.025245
25-0.172125-1.33330.093741
26-0.043582-0.33760.368428
27-0.113466-0.87890.19148
28-0.057185-0.4430.329696
29-0.027684-0.21440.415465
30-0.080209-0.62130.268378
310.0250730.19420.423331
320.0507280.39290.34788
33-0.099155-0.76810.222734
340.0553680.42890.334773
350.0657130.5090.306305
360.0666640.51640.303744
370.1865271.44480.076854
380.1178560.91290.182471
390.0458870.35540.361752
400.1281620.99270.162413
410.0236280.1830.427699
420.0701810.54360.29436
430.0568990.44070.330493
440.0289790.22450.411577
450.0368460.28540.388156
460.0553220.42850.334903
47-0.018067-0.13990.444584
48-0.054813-0.42460.336332

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143189 & 1.1091 & 0.135898 \tabularnewline
2 & 0.085576 & 0.6629 & 0.254975 \tabularnewline
3 & 0.263337 & 2.0398 & 0.02289 \tabularnewline
4 & -0.023449 & -0.1816 & 0.42824 \tabularnewline
5 & 0.087077 & 0.6745 & 0.251293 \tabularnewline
6 & 0.191357 & 1.4822 & 0.071754 \tabularnewline
7 & -0.135291 & -1.048 & 0.149429 \tabularnewline
8 & 0.115282 & 0.893 & 0.18772 \tabularnewline
9 & 0.202163 & 1.5659 & 0.06131 \tabularnewline
10 & -0.207435 & -1.6068 & 0.056676 \tabularnewline
11 & -0.057854 & -0.4481 & 0.327834 \tabularnewline
12 & -0.204951 & -1.5875 & 0.058823 \tabularnewline
13 & -0.253044 & -1.9601 & 0.027318 \tabularnewline
14 & 0.092482 & 0.7164 & 0.238274 \tabularnewline
15 & -0.135341 & -1.0483 & 0.149343 \tabularnewline
16 & -0.184691 & -1.4306 & 0.078864 \tabularnewline
17 & 0.153394 & 1.1882 & 0.119722 \tabularnewline
18 & -0.1473 & -1.141 & 0.129206 \tabularnewline
19 & -0.180209 & -1.3959 & 0.083945 \tabularnewline
20 & -0.041983 & -0.3252 & 0.373081 \tabularnewline
21 & -0.135291 & -1.048 & 0.149431 \tabularnewline
22 & -0.138711 & -1.0745 & 0.143461 \tabularnewline
23 & 0.079304 & 0.6143 & 0.270673 \tabularnewline
24 & -0.257669 & -1.9959 & 0.025245 \tabularnewline
25 & -0.172125 & -1.3333 & 0.093741 \tabularnewline
26 & -0.043582 & -0.3376 & 0.368428 \tabularnewline
27 & -0.113466 & -0.8789 & 0.19148 \tabularnewline
28 & -0.057185 & -0.443 & 0.329696 \tabularnewline
29 & -0.027684 & -0.2144 & 0.415465 \tabularnewline
30 & -0.080209 & -0.6213 & 0.268378 \tabularnewline
31 & 0.025073 & 0.1942 & 0.423331 \tabularnewline
32 & 0.050728 & 0.3929 & 0.34788 \tabularnewline
33 & -0.099155 & -0.7681 & 0.222734 \tabularnewline
34 & 0.055368 & 0.4289 & 0.334773 \tabularnewline
35 & 0.065713 & 0.509 & 0.306305 \tabularnewline
36 & 0.066664 & 0.5164 & 0.303744 \tabularnewline
37 & 0.186527 & 1.4448 & 0.076854 \tabularnewline
38 & 0.117856 & 0.9129 & 0.182471 \tabularnewline
39 & 0.045887 & 0.3554 & 0.361752 \tabularnewline
40 & 0.128162 & 0.9927 & 0.162413 \tabularnewline
41 & 0.023628 & 0.183 & 0.427699 \tabularnewline
42 & 0.070181 & 0.5436 & 0.29436 \tabularnewline
43 & 0.056899 & 0.4407 & 0.330493 \tabularnewline
44 & 0.028979 & 0.2245 & 0.411577 \tabularnewline
45 & 0.036846 & 0.2854 & 0.388156 \tabularnewline
46 & 0.055322 & 0.4285 & 0.334903 \tabularnewline
47 & -0.018067 & -0.1399 & 0.444584 \tabularnewline
48 & -0.054813 & -0.4246 & 0.336332 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31674&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]0.143189[/C][C]1.1091[/C][C]0.135898[/C][/ROW]
[ROW][C]2[/C][C]0.085576[/C][C]0.6629[/C][C]0.254975[/C][/ROW]
[ROW][C]3[/C][C]0.263337[/C][C]2.0398[/C][C]0.02289[/C][/ROW]
[ROW][C]4[/C][C]-0.023449[/C][C]-0.1816[/C][C]0.42824[/C][/ROW]
[ROW][C]5[/C][C]0.087077[/C][C]0.6745[/C][C]0.251293[/C][/ROW]
[ROW][C]6[/C][C]0.191357[/C][C]1.4822[/C][C]0.071754[/C][/ROW]
[ROW][C]7[/C][C]-0.135291[/C][C]-1.048[/C][C]0.149429[/C][/ROW]
[ROW][C]8[/C][C]0.115282[/C][C]0.893[/C][C]0.18772[/C][/ROW]
[ROW][C]9[/C][C]0.202163[/C][C]1.5659[/C][C]0.06131[/C][/ROW]
[ROW][C]10[/C][C]-0.207435[/C][C]-1.6068[/C][C]0.056676[/C][/ROW]
[ROW][C]11[/C][C]-0.057854[/C][C]-0.4481[/C][C]0.327834[/C][/ROW]
[ROW][C]12[/C][C]-0.204951[/C][C]-1.5875[/C][C]0.058823[/C][/ROW]
[ROW][C]13[/C][C]-0.253044[/C][C]-1.9601[/C][C]0.027318[/C][/ROW]
[ROW][C]14[/C][C]0.092482[/C][C]0.7164[/C][C]0.238274[/C][/ROW]
[ROW][C]15[/C][C]-0.135341[/C][C]-1.0483[/C][C]0.149343[/C][/ROW]
[ROW][C]16[/C][C]-0.184691[/C][C]-1.4306[/C][C]0.078864[/C][/ROW]
[ROW][C]17[/C][C]0.153394[/C][C]1.1882[/C][C]0.119722[/C][/ROW]
[ROW][C]18[/C][C]-0.1473[/C][C]-1.141[/C][C]0.129206[/C][/ROW]
[ROW][C]19[/C][C]-0.180209[/C][C]-1.3959[/C][C]0.083945[/C][/ROW]
[ROW][C]20[/C][C]-0.041983[/C][C]-0.3252[/C][C]0.373081[/C][/ROW]
[ROW][C]21[/C][C]-0.135291[/C][C]-1.048[/C][C]0.149431[/C][/ROW]
[ROW][C]22[/C][C]-0.138711[/C][C]-1.0745[/C][C]0.143461[/C][/ROW]
[ROW][C]23[/C][C]0.079304[/C][C]0.6143[/C][C]0.270673[/C][/ROW]
[ROW][C]24[/C][C]-0.257669[/C][C]-1.9959[/C][C]0.025245[/C][/ROW]
[ROW][C]25[/C][C]-0.172125[/C][C]-1.3333[/C][C]0.093741[/C][/ROW]
[ROW][C]26[/C][C]-0.043582[/C][C]-0.3376[/C][C]0.368428[/C][/ROW]
[ROW][C]27[/C][C]-0.113466[/C][C]-0.8789[/C][C]0.19148[/C][/ROW]
[ROW][C]28[/C][C]-0.057185[/C][C]-0.443[/C][C]0.329696[/C][/ROW]
[ROW][C]29[/C][C]-0.027684[/C][C]-0.2144[/C][C]0.415465[/C][/ROW]
[ROW][C]30[/C][C]-0.080209[/C][C]-0.6213[/C][C]0.268378[/C][/ROW]
[ROW][C]31[/C][C]0.025073[/C][C]0.1942[/C][C]0.423331[/C][/ROW]
[ROW][C]32[/C][C]0.050728[/C][C]0.3929[/C][C]0.34788[/C][/ROW]
[ROW][C]33[/C][C]-0.099155[/C][C]-0.7681[/C][C]0.222734[/C][/ROW]
[ROW][C]34[/C][C]0.055368[/C][C]0.4289[/C][C]0.334773[/C][/ROW]
[ROW][C]35[/C][C]0.065713[/C][C]0.509[/C][C]0.306305[/C][/ROW]
[ROW][C]36[/C][C]0.066664[/C][C]0.5164[/C][C]0.303744[/C][/ROW]
[ROW][C]37[/C][C]0.186527[/C][C]1.4448[/C][C]0.076854[/C][/ROW]
[ROW][C]38[/C][C]0.117856[/C][C]0.9129[/C][C]0.182471[/C][/ROW]
[ROW][C]39[/C][C]0.045887[/C][C]0.3554[/C][C]0.361752[/C][/ROW]
[ROW][C]40[/C][C]0.128162[/C][C]0.9927[/C][C]0.162413[/C][/ROW]
[ROW][C]41[/C][C]0.023628[/C][C]0.183[/C][C]0.427699[/C][/ROW]
[ROW][C]42[/C][C]0.070181[/C][C]0.5436[/C][C]0.29436[/C][/ROW]
[ROW][C]43[/C][C]0.056899[/C][C]0.4407[/C][C]0.330493[/C][/ROW]
[ROW][C]44[/C][C]0.028979[/C][C]0.2245[/C][C]0.411577[/C][/ROW]
[ROW][C]45[/C][C]0.036846[/C][C]0.2854[/C][C]0.388156[/C][/ROW]
[ROW][C]46[/C][C]0.055322[/C][C]0.4285[/C][C]0.334903[/C][/ROW]
[ROW][C]47[/C][C]-0.018067[/C][C]-0.1399[/C][C]0.444584[/C][/ROW]
[ROW][C]48[/C][C]-0.054813[/C][C]-0.4246[/C][C]0.336332[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31674&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31674&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
10.1431891.10910.135898
20.0855760.66290.254975
30.2633372.03980.02289
4-0.023449-0.18160.42824
50.0870770.67450.251293
60.1913571.48220.071754
7-0.135291-1.0480.149429
80.1152820.8930.18772
90.2021631.56590.06131
10-0.207435-1.60680.056676
11-0.057854-0.44810.327834
12-0.204951-1.58750.058823
13-0.253044-1.96010.027318
140.0924820.71640.238274
15-0.135341-1.04830.149343
16-0.184691-1.43060.078864
170.1533941.18820.119722
18-0.1473-1.1410.129206
19-0.180209-1.39590.083945
20-0.041983-0.32520.373081
21-0.135291-1.0480.149431
22-0.138711-1.07450.143461
230.0793040.61430.270673
24-0.257669-1.99590.025245
25-0.172125-1.33330.093741
26-0.043582-0.33760.368428
27-0.113466-0.87890.19148
28-0.057185-0.4430.329696
29-0.027684-0.21440.415465
30-0.080209-0.62130.268378
310.0250730.19420.423331
320.0507280.39290.34788
33-0.099155-0.76810.222734
340.0553680.42890.334773
350.0657130.5090.306305
360.0666640.51640.303744
370.1865271.44480.076854
380.1178560.91290.182471
390.0458870.35540.361752
400.1281620.99270.162413
410.0236280.1830.427699
420.0701810.54360.29436
430.0568990.44070.330493
440.0289790.22450.411577
450.0368460.28540.388156
460.0553220.42850.334903
47-0.018067-0.13990.444584
48-0.054813-0.42460.336332







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1431891.10910.135898
20.0664350.51460.304359
30.2485561.92530.029467
4-0.101358-0.78510.217737
50.0806270.62450.267321
60.1210720.93780.176049
7-0.171394-1.32760.094667
80.1209670.9370.176256
90.1357091.05120.148691
10-0.224446-1.73860.043622
11-0.111703-0.86520.195175
12-0.264648-2.050.022373
13-0.065311-0.50590.307392
140.1416951.09760.13839
15-0.083251-0.64490.260738
16-0.010799-0.08360.466808
170.138271.0710.144221
18-0.105701-0.81880.208083
19-0.090348-0.69980.243368
20-0.090579-0.70160.242814
210.1301131.00790.158787
22-0.190988-1.47940.072134
23-0.044852-0.34740.364744
24-0.222295-1.72190.045121
25-0.205028-1.58810.058756
26-0.096324-0.74610.229254
270.1121320.86860.194272
28-0.001264-0.00980.49611
290.0596670.46220.322812
30-0.02665-0.20640.418576
31-0.086981-0.67380.251529
32-0.010783-0.08350.466855
330.0055510.0430.482924
34-0.013722-0.10630.457855
35-0.02502-0.19380.423493
36-0.037177-0.2880.387181
37-0.047558-0.36840.356941
38-0.038757-0.30020.382526
390.0711880.55140.291696
40-0.035686-0.27640.391586
41-0.012905-0.10.460353
420.1140210.88320.190326
43-0.13032-1.00950.158404
44-0.13969-1.0820.141784
45-0.014353-0.11120.455924
46-0.077105-0.59730.276292
470.0075410.05840.476807
48-0.135134-1.04670.149709

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143189 & 1.1091 & 0.135898 \tabularnewline
2 & 0.066435 & 0.5146 & 0.304359 \tabularnewline
3 & 0.248556 & 1.9253 & 0.029467 \tabularnewline
4 & -0.101358 & -0.7851 & 0.217737 \tabularnewline
5 & 0.080627 & 0.6245 & 0.267321 \tabularnewline
6 & 0.121072 & 0.9378 & 0.176049 \tabularnewline
7 & -0.171394 & -1.3276 & 0.094667 \tabularnewline
8 & 0.120967 & 0.937 & 0.176256 \tabularnewline
9 & 0.135709 & 1.0512 & 0.148691 \tabularnewline
10 & -0.224446 & -1.7386 & 0.043622 \tabularnewline
11 & -0.111703 & -0.8652 & 0.195175 \tabularnewline
12 & -0.264648 & -2.05 & 0.022373 \tabularnewline
13 & -0.065311 & -0.5059 & 0.307392 \tabularnewline
14 & 0.141695 & 1.0976 & 0.13839 \tabularnewline
15 & -0.083251 & -0.6449 & 0.260738 \tabularnewline
16 & -0.010799 & -0.0836 & 0.466808 \tabularnewline
17 & 0.13827 & 1.071 & 0.144221 \tabularnewline
18 & -0.105701 & -0.8188 & 0.208083 \tabularnewline
19 & -0.090348 & -0.6998 & 0.243368 \tabularnewline
20 & -0.090579 & -0.7016 & 0.242814 \tabularnewline
21 & 0.130113 & 1.0079 & 0.158787 \tabularnewline
22 & -0.190988 & -1.4794 & 0.072134 \tabularnewline
23 & -0.044852 & -0.3474 & 0.364744 \tabularnewline
24 & -0.222295 & -1.7219 & 0.045121 \tabularnewline
25 & -0.205028 & -1.5881 & 0.058756 \tabularnewline
26 & -0.096324 & -0.7461 & 0.229254 \tabularnewline
27 & 0.112132 & 0.8686 & 0.194272 \tabularnewline
28 & -0.001264 & -0.0098 & 0.49611 \tabularnewline
29 & 0.059667 & 0.4622 & 0.322812 \tabularnewline
30 & -0.02665 & -0.2064 & 0.418576 \tabularnewline
31 & -0.086981 & -0.6738 & 0.251529 \tabularnewline
32 & -0.010783 & -0.0835 & 0.466855 \tabularnewline
33 & 0.005551 & 0.043 & 0.482924 \tabularnewline
34 & -0.013722 & -0.1063 & 0.457855 \tabularnewline
35 & -0.02502 & -0.1938 & 0.423493 \tabularnewline
36 & -0.037177 & -0.288 & 0.387181 \tabularnewline
37 & -0.047558 & -0.3684 & 0.356941 \tabularnewline
38 & -0.038757 & -0.3002 & 0.382526 \tabularnewline
39 & 0.071188 & 0.5514 & 0.291696 \tabularnewline
40 & -0.035686 & -0.2764 & 0.391586 \tabularnewline
41 & -0.012905 & -0.1 & 0.460353 \tabularnewline
42 & 0.114021 & 0.8832 & 0.190326 \tabularnewline
43 & -0.13032 & -1.0095 & 0.158404 \tabularnewline
44 & -0.13969 & -1.082 & 0.141784 \tabularnewline
45 & -0.014353 & -0.1112 & 0.455924 \tabularnewline
46 & -0.077105 & -0.5973 & 0.276292 \tabularnewline
47 & 0.007541 & 0.0584 & 0.476807 \tabularnewline
48 & -0.135134 & -1.0467 & 0.149709 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31674&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]0.143189[/C][C]1.1091[/C][C]0.135898[/C][/ROW]
[ROW][C]2[/C][C]0.066435[/C][C]0.5146[/C][C]0.304359[/C][/ROW]
[ROW][C]3[/C][C]0.248556[/C][C]1.9253[/C][C]0.029467[/C][/ROW]
[ROW][C]4[/C][C]-0.101358[/C][C]-0.7851[/C][C]0.217737[/C][/ROW]
[ROW][C]5[/C][C]0.080627[/C][C]0.6245[/C][C]0.267321[/C][/ROW]
[ROW][C]6[/C][C]0.121072[/C][C]0.9378[/C][C]0.176049[/C][/ROW]
[ROW][C]7[/C][C]-0.171394[/C][C]-1.3276[/C][C]0.094667[/C][/ROW]
[ROW][C]8[/C][C]0.120967[/C][C]0.937[/C][C]0.176256[/C][/ROW]
[ROW][C]9[/C][C]0.135709[/C][C]1.0512[/C][C]0.148691[/C][/ROW]
[ROW][C]10[/C][C]-0.224446[/C][C]-1.7386[/C][C]0.043622[/C][/ROW]
[ROW][C]11[/C][C]-0.111703[/C][C]-0.8652[/C][C]0.195175[/C][/ROW]
[ROW][C]12[/C][C]-0.264648[/C][C]-2.05[/C][C]0.022373[/C][/ROW]
[ROW][C]13[/C][C]-0.065311[/C][C]-0.5059[/C][C]0.307392[/C][/ROW]
[ROW][C]14[/C][C]0.141695[/C][C]1.0976[/C][C]0.13839[/C][/ROW]
[ROW][C]15[/C][C]-0.083251[/C][C]-0.6449[/C][C]0.260738[/C][/ROW]
[ROW][C]16[/C][C]-0.010799[/C][C]-0.0836[/C][C]0.466808[/C][/ROW]
[ROW][C]17[/C][C]0.13827[/C][C]1.071[/C][C]0.144221[/C][/ROW]
[ROW][C]18[/C][C]-0.105701[/C][C]-0.8188[/C][C]0.208083[/C][/ROW]
[ROW][C]19[/C][C]-0.090348[/C][C]-0.6998[/C][C]0.243368[/C][/ROW]
[ROW][C]20[/C][C]-0.090579[/C][C]-0.7016[/C][C]0.242814[/C][/ROW]
[ROW][C]21[/C][C]0.130113[/C][C]1.0079[/C][C]0.158787[/C][/ROW]
[ROW][C]22[/C][C]-0.190988[/C][C]-1.4794[/C][C]0.072134[/C][/ROW]
[ROW][C]23[/C][C]-0.044852[/C][C]-0.3474[/C][C]0.364744[/C][/ROW]
[ROW][C]24[/C][C]-0.222295[/C][C]-1.7219[/C][C]0.045121[/C][/ROW]
[ROW][C]25[/C][C]-0.205028[/C][C]-1.5881[/C][C]0.058756[/C][/ROW]
[ROW][C]26[/C][C]-0.096324[/C][C]-0.7461[/C][C]0.229254[/C][/ROW]
[ROW][C]27[/C][C]0.112132[/C][C]0.8686[/C][C]0.194272[/C][/ROW]
[ROW][C]28[/C][C]-0.001264[/C][C]-0.0098[/C][C]0.49611[/C][/ROW]
[ROW][C]29[/C][C]0.059667[/C][C]0.4622[/C][C]0.322812[/C][/ROW]
[ROW][C]30[/C][C]-0.02665[/C][C]-0.2064[/C][C]0.418576[/C][/ROW]
[ROW][C]31[/C][C]-0.086981[/C][C]-0.6738[/C][C]0.251529[/C][/ROW]
[ROW][C]32[/C][C]-0.010783[/C][C]-0.0835[/C][C]0.466855[/C][/ROW]
[ROW][C]33[/C][C]0.005551[/C][C]0.043[/C][C]0.482924[/C][/ROW]
[ROW][C]34[/C][C]-0.013722[/C][C]-0.1063[/C][C]0.457855[/C][/ROW]
[ROW][C]35[/C][C]-0.02502[/C][C]-0.1938[/C][C]0.423493[/C][/ROW]
[ROW][C]36[/C][C]-0.037177[/C][C]-0.288[/C][C]0.387181[/C][/ROW]
[ROW][C]37[/C][C]-0.047558[/C][C]-0.3684[/C][C]0.356941[/C][/ROW]
[ROW][C]38[/C][C]-0.038757[/C][C]-0.3002[/C][C]0.382526[/C][/ROW]
[ROW][C]39[/C][C]0.071188[/C][C]0.5514[/C][C]0.291696[/C][/ROW]
[ROW][C]40[/C][C]-0.035686[/C][C]-0.2764[/C][C]0.391586[/C][/ROW]
[ROW][C]41[/C][C]-0.012905[/C][C]-0.1[/C][C]0.460353[/C][/ROW]
[ROW][C]42[/C][C]0.114021[/C][C]0.8832[/C][C]0.190326[/C][/ROW]
[ROW][C]43[/C][C]-0.13032[/C][C]-1.0095[/C][C]0.158404[/C][/ROW]
[ROW][C]44[/C][C]-0.13969[/C][C]-1.082[/C][C]0.141784[/C][/ROW]
[ROW][C]45[/C][C]-0.014353[/C][C]-0.1112[/C][C]0.455924[/C][/ROW]
[ROW][C]46[/C][C]-0.077105[/C][C]-0.5973[/C][C]0.276292[/C][/ROW]
[ROW][C]47[/C][C]0.007541[/C][C]0.0584[/C][C]0.476807[/C][/ROW]
[ROW][C]48[/C][C]-0.135134[/C][C]-1.0467[/C][C]0.149709[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31674&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31674&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
10.1431891.10910.135898
20.0664350.51460.304359
30.2485561.92530.029467
4-0.101358-0.78510.217737
50.0806270.62450.267321
60.1210720.93780.176049
7-0.171394-1.32760.094667
80.1209670.9370.176256
90.1357091.05120.148691
10-0.224446-1.73860.043622
11-0.111703-0.86520.195175
12-0.264648-2.050.022373
13-0.065311-0.50590.307392
140.1416951.09760.13839
15-0.083251-0.64490.260738
16-0.010799-0.08360.466808
170.138271.0710.144221
18-0.105701-0.81880.208083
19-0.090348-0.69980.243368
20-0.090579-0.70160.242814
210.1301131.00790.158787
22-0.190988-1.47940.072134
23-0.044852-0.34740.364744
24-0.222295-1.72190.045121
25-0.205028-1.58810.058756
26-0.096324-0.74610.229254
270.1121320.86860.194272
28-0.001264-0.00980.49611
290.0596670.46220.322812
30-0.02665-0.20640.418576
31-0.086981-0.67380.251529
32-0.010783-0.08350.466855
330.0055510.0430.482924
34-0.013722-0.10630.457855
35-0.02502-0.19380.423493
36-0.037177-0.2880.387181
37-0.047558-0.36840.356941
38-0.038757-0.30020.382526
390.0711880.55140.291696
40-0.035686-0.27640.391586
41-0.012905-0.10.460353
420.1140210.88320.190326
43-0.13032-1.00950.158404
44-0.13969-1.0820.141784
45-0.014353-0.11120.455924
46-0.077105-0.59730.276292
470.0075410.05840.476807
48-0.135134-1.04670.149709



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; 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 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')