Free Statistics

of Irreproducible Research!

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 10:37:03 +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/t1292323454isoiwonr7c74nlp.htm/, Retrieved Thu, 02 May 2024 20:43:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109379, Retrieved Thu, 02 May 2024 20:43:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123
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 09:13:00] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [WS 9 - ACF] [2010-12-04 11:15:33] [8ef49741e164ec6343c90c7935194465]
-   PD        [(Partial) Autocorrelation Function] [AFC - Broodprijs] [2010-12-14 10:37:03] [934c3727858e074bf543f25f5906ed72] [Current]
Feedback Forum

Post a new message
Dataseries X:
104.37
104.89
105.15
105.72
106.38
106.40
106.47
106.59
106.76
107.35
107.81
108.03
109.08
109.86
110.29
110.34
110.59
110.64
110.83
111.51
113.32
115.89
116.51
117.44
118.25
118.65
118.52
119.07
119.12
119.28
119.30
119.44
119.57
119.93
120.03
119.66
119.46
119.48
119.56
119.43
119.57
119.59
119.50
119.54
119.56
119.61
119.64
119.60
119.71
119.72
119.66
119.76
119.80
119.88
119.78
120.08
120.22




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109379&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]2 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=109379&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109379&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.189284-1.40380.083005
2-0.196031-1.45380.075841
30.0040620.03010.488038
40.0854550.63370.264436
5-0.278359-2.06440.021856
6-0.023909-0.17730.429957
7-0.00613-0.04550.481954
80.1014010.7520.227627
90.1234480.91550.181959
10-0.173117-1.28390.102286
110.115170.85410.198372
120.0738230.54750.29313
130.0355990.2640.396381
14-0.165713-1.2290.11216
15-0.055916-0.41470.339992
16-0.124535-0.92360.179871
170.2299061.7050.046916
18-0.083332-0.6180.26956
19-0.057872-0.42920.33473
200.1147160.85080.199296
210.0220720.16370.435288
22-0.070304-0.52140.302096
23-0.048299-0.35820.360783
240.1028510.76280.224432
25-0.015715-0.11650.453824
26-0.042173-0.31280.377821
27-0.033664-0.24970.401891
280.0941420.69820.244006
29-0.064033-0.47490.318377
300.0240150.17810.429648
31-0.009458-0.07010.472166
320.0319190.23670.406878
33-0.083256-0.61740.269744
340.0583340.43260.333492
350.002930.02170.49137
360.0147420.10930.456669
370.0095740.0710.471826
38-0.045684-0.33880.368026
390.0421950.31290.377761
40-0.020119-0.14920.440968
41-0.005936-0.0440.482524
42-0.007837-0.05810.476932
430.0272870.20240.42019
44-0.012061-0.08940.464525
450.0017370.01290.494885
460.0001350.0010.499602
470.0003950.00290.498836
480.003840.02850.488692

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.189284 & -1.4038 & 0.083005 \tabularnewline
2 & -0.196031 & -1.4538 & 0.075841 \tabularnewline
3 & 0.004062 & 0.0301 & 0.488038 \tabularnewline
4 & 0.085455 & 0.6337 & 0.264436 \tabularnewline
5 & -0.278359 & -2.0644 & 0.021856 \tabularnewline
6 & -0.023909 & -0.1773 & 0.429957 \tabularnewline
7 & -0.00613 & -0.0455 & 0.481954 \tabularnewline
8 & 0.101401 & 0.752 & 0.227627 \tabularnewline
9 & 0.123448 & 0.9155 & 0.181959 \tabularnewline
10 & -0.173117 & -1.2839 & 0.102286 \tabularnewline
11 & 0.11517 & 0.8541 & 0.198372 \tabularnewline
12 & 0.073823 & 0.5475 & 0.29313 \tabularnewline
13 & 0.035599 & 0.264 & 0.396381 \tabularnewline
14 & -0.165713 & -1.229 & 0.11216 \tabularnewline
15 & -0.055916 & -0.4147 & 0.339992 \tabularnewline
16 & -0.124535 & -0.9236 & 0.179871 \tabularnewline
17 & 0.229906 & 1.705 & 0.046916 \tabularnewline
18 & -0.083332 & -0.618 & 0.26956 \tabularnewline
19 & -0.057872 & -0.4292 & 0.33473 \tabularnewline
20 & 0.114716 & 0.8508 & 0.199296 \tabularnewline
21 & 0.022072 & 0.1637 & 0.435288 \tabularnewline
22 & -0.070304 & -0.5214 & 0.302096 \tabularnewline
23 & -0.048299 & -0.3582 & 0.360783 \tabularnewline
24 & 0.102851 & 0.7628 & 0.224432 \tabularnewline
25 & -0.015715 & -0.1165 & 0.453824 \tabularnewline
26 & -0.042173 & -0.3128 & 0.377821 \tabularnewline
27 & -0.033664 & -0.2497 & 0.401891 \tabularnewline
28 & 0.094142 & 0.6982 & 0.244006 \tabularnewline
29 & -0.064033 & -0.4749 & 0.318377 \tabularnewline
30 & 0.024015 & 0.1781 & 0.429648 \tabularnewline
31 & -0.009458 & -0.0701 & 0.472166 \tabularnewline
32 & 0.031919 & 0.2367 & 0.406878 \tabularnewline
33 & -0.083256 & -0.6174 & 0.269744 \tabularnewline
34 & 0.058334 & 0.4326 & 0.333492 \tabularnewline
35 & 0.00293 & 0.0217 & 0.49137 \tabularnewline
36 & 0.014742 & 0.1093 & 0.456669 \tabularnewline
37 & 0.009574 & 0.071 & 0.471826 \tabularnewline
38 & -0.045684 & -0.3388 & 0.368026 \tabularnewline
39 & 0.042195 & 0.3129 & 0.377761 \tabularnewline
40 & -0.020119 & -0.1492 & 0.440968 \tabularnewline
41 & -0.005936 & -0.044 & 0.482524 \tabularnewline
42 & -0.007837 & -0.0581 & 0.476932 \tabularnewline
43 & 0.027287 & 0.2024 & 0.42019 \tabularnewline
44 & -0.012061 & -0.0894 & 0.464525 \tabularnewline
45 & 0.001737 & 0.0129 & 0.494885 \tabularnewline
46 & 0.000135 & 0.001 & 0.499602 \tabularnewline
47 & 0.000395 & 0.0029 & 0.498836 \tabularnewline
48 & 0.00384 & 0.0285 & 0.488692 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109379&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]-0.189284[/C][C]-1.4038[/C][C]0.083005[/C][/ROW]
[ROW][C]2[/C][C]-0.196031[/C][C]-1.4538[/C][C]0.075841[/C][/ROW]
[ROW][C]3[/C][C]0.004062[/C][C]0.0301[/C][C]0.488038[/C][/ROW]
[ROW][C]4[/C][C]0.085455[/C][C]0.6337[/C][C]0.264436[/C][/ROW]
[ROW][C]5[/C][C]-0.278359[/C][C]-2.0644[/C][C]0.021856[/C][/ROW]
[ROW][C]6[/C][C]-0.023909[/C][C]-0.1773[/C][C]0.429957[/C][/ROW]
[ROW][C]7[/C][C]-0.00613[/C][C]-0.0455[/C][C]0.481954[/C][/ROW]
[ROW][C]8[/C][C]0.101401[/C][C]0.752[/C][C]0.227627[/C][/ROW]
[ROW][C]9[/C][C]0.123448[/C][C]0.9155[/C][C]0.181959[/C][/ROW]
[ROW][C]10[/C][C]-0.173117[/C][C]-1.2839[/C][C]0.102286[/C][/ROW]
[ROW][C]11[/C][C]0.11517[/C][C]0.8541[/C][C]0.198372[/C][/ROW]
[ROW][C]12[/C][C]0.073823[/C][C]0.5475[/C][C]0.29313[/C][/ROW]
[ROW][C]13[/C][C]0.035599[/C][C]0.264[/C][C]0.396381[/C][/ROW]
[ROW][C]14[/C][C]-0.165713[/C][C]-1.229[/C][C]0.11216[/C][/ROW]
[ROW][C]15[/C][C]-0.055916[/C][C]-0.4147[/C][C]0.339992[/C][/ROW]
[ROW][C]16[/C][C]-0.124535[/C][C]-0.9236[/C][C]0.179871[/C][/ROW]
[ROW][C]17[/C][C]0.229906[/C][C]1.705[/C][C]0.046916[/C][/ROW]
[ROW][C]18[/C][C]-0.083332[/C][C]-0.618[/C][C]0.26956[/C][/ROW]
[ROW][C]19[/C][C]-0.057872[/C][C]-0.4292[/C][C]0.33473[/C][/ROW]
[ROW][C]20[/C][C]0.114716[/C][C]0.8508[/C][C]0.199296[/C][/ROW]
[ROW][C]21[/C][C]0.022072[/C][C]0.1637[/C][C]0.435288[/C][/ROW]
[ROW][C]22[/C][C]-0.070304[/C][C]-0.5214[/C][C]0.302096[/C][/ROW]
[ROW][C]23[/C][C]-0.048299[/C][C]-0.3582[/C][C]0.360783[/C][/ROW]
[ROW][C]24[/C][C]0.102851[/C][C]0.7628[/C][C]0.224432[/C][/ROW]
[ROW][C]25[/C][C]-0.015715[/C][C]-0.1165[/C][C]0.453824[/C][/ROW]
[ROW][C]26[/C][C]-0.042173[/C][C]-0.3128[/C][C]0.377821[/C][/ROW]
[ROW][C]27[/C][C]-0.033664[/C][C]-0.2497[/C][C]0.401891[/C][/ROW]
[ROW][C]28[/C][C]0.094142[/C][C]0.6982[/C][C]0.244006[/C][/ROW]
[ROW][C]29[/C][C]-0.064033[/C][C]-0.4749[/C][C]0.318377[/C][/ROW]
[ROW][C]30[/C][C]0.024015[/C][C]0.1781[/C][C]0.429648[/C][/ROW]
[ROW][C]31[/C][C]-0.009458[/C][C]-0.0701[/C][C]0.472166[/C][/ROW]
[ROW][C]32[/C][C]0.031919[/C][C]0.2367[/C][C]0.406878[/C][/ROW]
[ROW][C]33[/C][C]-0.083256[/C][C]-0.6174[/C][C]0.269744[/C][/ROW]
[ROW][C]34[/C][C]0.058334[/C][C]0.4326[/C][C]0.333492[/C][/ROW]
[ROW][C]35[/C][C]0.00293[/C][C]0.0217[/C][C]0.49137[/C][/ROW]
[ROW][C]36[/C][C]0.014742[/C][C]0.1093[/C][C]0.456669[/C][/ROW]
[ROW][C]37[/C][C]0.009574[/C][C]0.071[/C][C]0.471826[/C][/ROW]
[ROW][C]38[/C][C]-0.045684[/C][C]-0.3388[/C][C]0.368026[/C][/ROW]
[ROW][C]39[/C][C]0.042195[/C][C]0.3129[/C][C]0.377761[/C][/ROW]
[ROW][C]40[/C][C]-0.020119[/C][C]-0.1492[/C][C]0.440968[/C][/ROW]
[ROW][C]41[/C][C]-0.005936[/C][C]-0.044[/C][C]0.482524[/C][/ROW]
[ROW][C]42[/C][C]-0.007837[/C][C]-0.0581[/C][C]0.476932[/C][/ROW]
[ROW][C]43[/C][C]0.027287[/C][C]0.2024[/C][C]0.42019[/C][/ROW]
[ROW][C]44[/C][C]-0.012061[/C][C]-0.0894[/C][C]0.464525[/C][/ROW]
[ROW][C]45[/C][C]0.001737[/C][C]0.0129[/C][C]0.494885[/C][/ROW]
[ROW][C]46[/C][C]0.000135[/C][C]0.001[/C][C]0.499602[/C][/ROW]
[ROW][C]47[/C][C]0.000395[/C][C]0.0029[/C][C]0.498836[/C][/ROW]
[ROW][C]48[/C][C]0.00384[/C][C]0.0285[/C][C]0.488692[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109379&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109379&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
1-0.189284-1.40380.083005
2-0.196031-1.45380.075841
30.0040620.03010.488038
40.0854550.63370.264436
5-0.278359-2.06440.021856
6-0.023909-0.17730.429957
7-0.00613-0.04550.481954
80.1014010.7520.227627
90.1234480.91550.181959
10-0.173117-1.28390.102286
110.115170.85410.198372
120.0738230.54750.29313
130.0355990.2640.396381
14-0.165713-1.2290.11216
15-0.055916-0.41470.339992
16-0.124535-0.92360.179871
170.2299061.7050.046916
18-0.083332-0.6180.26956
19-0.057872-0.42920.33473
200.1147160.85080.199296
210.0220720.16370.435288
22-0.070304-0.52140.302096
23-0.048299-0.35820.360783
240.1028510.76280.224432
25-0.015715-0.11650.453824
26-0.042173-0.31280.377821
27-0.033664-0.24970.401891
280.0941420.69820.244006
29-0.064033-0.47490.318377
300.0240150.17810.429648
31-0.009458-0.07010.472166
320.0319190.23670.406878
33-0.083256-0.61740.269744
340.0583340.43260.333492
350.002930.02170.49137
360.0147420.10930.456669
370.0095740.0710.471826
38-0.045684-0.33880.368026
390.0421950.31290.377761
40-0.020119-0.14920.440968
41-0.005936-0.0440.482524
42-0.007837-0.05810.476932
430.0272870.20240.42019
44-0.012061-0.08940.464525
450.0017370.01290.494885
460.0001350.0010.499602
470.0003950.00290.498836
480.003840.02850.488692







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.189284-1.40380.083005
2-0.240475-1.78340.040018
3-0.096305-0.71420.239058
40.0185560.13760.445524
5-0.299937-2.22440.015123
6-0.167047-1.23890.11033
7-0.222247-1.64820.052503
8-0.058755-0.43570.332366
90.1128020.83660.20323
10-0.231703-1.71840.045679
110.0456040.33820.368246
12-0.012182-0.09030.464171
130.1341750.99510.16203
140.0194880.14450.442806
15-0.176454-1.30860.098053
16-0.223726-1.65920.051384
170.1138330.84420.201104
18-0.013738-0.10190.45961
19-0.065741-0.48750.313905
20-0.109862-0.81480.209363
21-0.19273-1.42930.079283
220.0178260.13220.447655
23-0.066177-0.49080.312766
240.0185340.13750.445587
25-0.056962-0.42240.337174
26-0.188701-1.39940.083648
270.1026770.76150.224814
280.0507710.37650.353988
29-0.08789-0.65180.25862
30-0.054763-0.40610.343111
31-0.150156-1.11360.13515
320.084040.62330.267845
33-0.042629-0.31610.376544
34-0.086529-0.64170.261863
35-0.070236-0.52090.302269
36-0.090097-0.66820.253406
370.0375530.27850.390835
38-0.034302-0.25440.400072
39-0.062377-0.46260.322739
40-0.045766-0.33940.367798
41-0.072533-0.53790.2964
420.0415120.30790.379675
430.0101030.07490.470274
44-0.062499-0.46350.322417
45-0.089505-0.66380.2548
460.0201370.14930.440915
47-0.017907-0.13280.447417
48-0.021977-0.1630.435562

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.189284 & -1.4038 & 0.083005 \tabularnewline
2 & -0.240475 & -1.7834 & 0.040018 \tabularnewline
3 & -0.096305 & -0.7142 & 0.239058 \tabularnewline
4 & 0.018556 & 0.1376 & 0.445524 \tabularnewline
5 & -0.299937 & -2.2244 & 0.015123 \tabularnewline
6 & -0.167047 & -1.2389 & 0.11033 \tabularnewline
7 & -0.222247 & -1.6482 & 0.052503 \tabularnewline
8 & -0.058755 & -0.4357 & 0.332366 \tabularnewline
9 & 0.112802 & 0.8366 & 0.20323 \tabularnewline
10 & -0.231703 & -1.7184 & 0.045679 \tabularnewline
11 & 0.045604 & 0.3382 & 0.368246 \tabularnewline
12 & -0.012182 & -0.0903 & 0.464171 \tabularnewline
13 & 0.134175 & 0.9951 & 0.16203 \tabularnewline
14 & 0.019488 & 0.1445 & 0.442806 \tabularnewline
15 & -0.176454 & -1.3086 & 0.098053 \tabularnewline
16 & -0.223726 & -1.6592 & 0.051384 \tabularnewline
17 & 0.113833 & 0.8442 & 0.201104 \tabularnewline
18 & -0.013738 & -0.1019 & 0.45961 \tabularnewline
19 & -0.065741 & -0.4875 & 0.313905 \tabularnewline
20 & -0.109862 & -0.8148 & 0.209363 \tabularnewline
21 & -0.19273 & -1.4293 & 0.079283 \tabularnewline
22 & 0.017826 & 0.1322 & 0.447655 \tabularnewline
23 & -0.066177 & -0.4908 & 0.312766 \tabularnewline
24 & 0.018534 & 0.1375 & 0.445587 \tabularnewline
25 & -0.056962 & -0.4224 & 0.337174 \tabularnewline
26 & -0.188701 & -1.3994 & 0.083648 \tabularnewline
27 & 0.102677 & 0.7615 & 0.224814 \tabularnewline
28 & 0.050771 & 0.3765 & 0.353988 \tabularnewline
29 & -0.08789 & -0.6518 & 0.25862 \tabularnewline
30 & -0.054763 & -0.4061 & 0.343111 \tabularnewline
31 & -0.150156 & -1.1136 & 0.13515 \tabularnewline
32 & 0.08404 & 0.6233 & 0.267845 \tabularnewline
33 & -0.042629 & -0.3161 & 0.376544 \tabularnewline
34 & -0.086529 & -0.6417 & 0.261863 \tabularnewline
35 & -0.070236 & -0.5209 & 0.302269 \tabularnewline
36 & -0.090097 & -0.6682 & 0.253406 \tabularnewline
37 & 0.037553 & 0.2785 & 0.390835 \tabularnewline
38 & -0.034302 & -0.2544 & 0.400072 \tabularnewline
39 & -0.062377 & -0.4626 & 0.322739 \tabularnewline
40 & -0.045766 & -0.3394 & 0.367798 \tabularnewline
41 & -0.072533 & -0.5379 & 0.2964 \tabularnewline
42 & 0.041512 & 0.3079 & 0.379675 \tabularnewline
43 & 0.010103 & 0.0749 & 0.470274 \tabularnewline
44 & -0.062499 & -0.4635 & 0.322417 \tabularnewline
45 & -0.089505 & -0.6638 & 0.2548 \tabularnewline
46 & 0.020137 & 0.1493 & 0.440915 \tabularnewline
47 & -0.017907 & -0.1328 & 0.447417 \tabularnewline
48 & -0.021977 & -0.163 & 0.435562 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109379&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]-0.189284[/C][C]-1.4038[/C][C]0.083005[/C][/ROW]
[ROW][C]2[/C][C]-0.240475[/C][C]-1.7834[/C][C]0.040018[/C][/ROW]
[ROW][C]3[/C][C]-0.096305[/C][C]-0.7142[/C][C]0.239058[/C][/ROW]
[ROW][C]4[/C][C]0.018556[/C][C]0.1376[/C][C]0.445524[/C][/ROW]
[ROW][C]5[/C][C]-0.299937[/C][C]-2.2244[/C][C]0.015123[/C][/ROW]
[ROW][C]6[/C][C]-0.167047[/C][C]-1.2389[/C][C]0.11033[/C][/ROW]
[ROW][C]7[/C][C]-0.222247[/C][C]-1.6482[/C][C]0.052503[/C][/ROW]
[ROW][C]8[/C][C]-0.058755[/C][C]-0.4357[/C][C]0.332366[/C][/ROW]
[ROW][C]9[/C][C]0.112802[/C][C]0.8366[/C][C]0.20323[/C][/ROW]
[ROW][C]10[/C][C]-0.231703[/C][C]-1.7184[/C][C]0.045679[/C][/ROW]
[ROW][C]11[/C][C]0.045604[/C][C]0.3382[/C][C]0.368246[/C][/ROW]
[ROW][C]12[/C][C]-0.012182[/C][C]-0.0903[/C][C]0.464171[/C][/ROW]
[ROW][C]13[/C][C]0.134175[/C][C]0.9951[/C][C]0.16203[/C][/ROW]
[ROW][C]14[/C][C]0.019488[/C][C]0.1445[/C][C]0.442806[/C][/ROW]
[ROW][C]15[/C][C]-0.176454[/C][C]-1.3086[/C][C]0.098053[/C][/ROW]
[ROW][C]16[/C][C]-0.223726[/C][C]-1.6592[/C][C]0.051384[/C][/ROW]
[ROW][C]17[/C][C]0.113833[/C][C]0.8442[/C][C]0.201104[/C][/ROW]
[ROW][C]18[/C][C]-0.013738[/C][C]-0.1019[/C][C]0.45961[/C][/ROW]
[ROW][C]19[/C][C]-0.065741[/C][C]-0.4875[/C][C]0.313905[/C][/ROW]
[ROW][C]20[/C][C]-0.109862[/C][C]-0.8148[/C][C]0.209363[/C][/ROW]
[ROW][C]21[/C][C]-0.19273[/C][C]-1.4293[/C][C]0.079283[/C][/ROW]
[ROW][C]22[/C][C]0.017826[/C][C]0.1322[/C][C]0.447655[/C][/ROW]
[ROW][C]23[/C][C]-0.066177[/C][C]-0.4908[/C][C]0.312766[/C][/ROW]
[ROW][C]24[/C][C]0.018534[/C][C]0.1375[/C][C]0.445587[/C][/ROW]
[ROW][C]25[/C][C]-0.056962[/C][C]-0.4224[/C][C]0.337174[/C][/ROW]
[ROW][C]26[/C][C]-0.188701[/C][C]-1.3994[/C][C]0.083648[/C][/ROW]
[ROW][C]27[/C][C]0.102677[/C][C]0.7615[/C][C]0.224814[/C][/ROW]
[ROW][C]28[/C][C]0.050771[/C][C]0.3765[/C][C]0.353988[/C][/ROW]
[ROW][C]29[/C][C]-0.08789[/C][C]-0.6518[/C][C]0.25862[/C][/ROW]
[ROW][C]30[/C][C]-0.054763[/C][C]-0.4061[/C][C]0.343111[/C][/ROW]
[ROW][C]31[/C][C]-0.150156[/C][C]-1.1136[/C][C]0.13515[/C][/ROW]
[ROW][C]32[/C][C]0.08404[/C][C]0.6233[/C][C]0.267845[/C][/ROW]
[ROW][C]33[/C][C]-0.042629[/C][C]-0.3161[/C][C]0.376544[/C][/ROW]
[ROW][C]34[/C][C]-0.086529[/C][C]-0.6417[/C][C]0.261863[/C][/ROW]
[ROW][C]35[/C][C]-0.070236[/C][C]-0.5209[/C][C]0.302269[/C][/ROW]
[ROW][C]36[/C][C]-0.090097[/C][C]-0.6682[/C][C]0.253406[/C][/ROW]
[ROW][C]37[/C][C]0.037553[/C][C]0.2785[/C][C]0.390835[/C][/ROW]
[ROW][C]38[/C][C]-0.034302[/C][C]-0.2544[/C][C]0.400072[/C][/ROW]
[ROW][C]39[/C][C]-0.062377[/C][C]-0.4626[/C][C]0.322739[/C][/ROW]
[ROW][C]40[/C][C]-0.045766[/C][C]-0.3394[/C][C]0.367798[/C][/ROW]
[ROW][C]41[/C][C]-0.072533[/C][C]-0.5379[/C][C]0.2964[/C][/ROW]
[ROW][C]42[/C][C]0.041512[/C][C]0.3079[/C][C]0.379675[/C][/ROW]
[ROW][C]43[/C][C]0.010103[/C][C]0.0749[/C][C]0.470274[/C][/ROW]
[ROW][C]44[/C][C]-0.062499[/C][C]-0.4635[/C][C]0.322417[/C][/ROW]
[ROW][C]45[/C][C]-0.089505[/C][C]-0.6638[/C][C]0.2548[/C][/ROW]
[ROW][C]46[/C][C]0.020137[/C][C]0.1493[/C][C]0.440915[/C][/ROW]
[ROW][C]47[/C][C]-0.017907[/C][C]-0.1328[/C][C]0.447417[/C][/ROW]
[ROW][C]48[/C][C]-0.021977[/C][C]-0.163[/C][C]0.435562[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109379&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109379&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
1-0.189284-1.40380.083005
2-0.240475-1.78340.040018
3-0.096305-0.71420.239058
40.0185560.13760.445524
5-0.299937-2.22440.015123
6-0.167047-1.23890.11033
7-0.222247-1.64820.052503
8-0.058755-0.43570.332366
90.1128020.83660.20323
10-0.231703-1.71840.045679
110.0456040.33820.368246
12-0.012182-0.09030.464171
130.1341750.99510.16203
140.0194880.14450.442806
15-0.176454-1.30860.098053
16-0.223726-1.65920.051384
170.1138330.84420.201104
18-0.013738-0.10190.45961
19-0.065741-0.48750.313905
20-0.109862-0.81480.209363
21-0.19273-1.42930.079283
220.0178260.13220.447655
23-0.066177-0.49080.312766
240.0185340.13750.445587
25-0.056962-0.42240.337174
26-0.188701-1.39940.083648
270.1026770.76150.224814
280.0507710.37650.353988
29-0.08789-0.65180.25862
30-0.054763-0.40610.343111
31-0.150156-1.11360.13515
320.084040.62330.267845
33-0.042629-0.31610.376544
34-0.086529-0.64170.261863
35-0.070236-0.52090.302269
36-0.090097-0.66820.253406
370.0375530.27850.390835
38-0.034302-0.25440.400072
39-0.062377-0.46260.322739
40-0.045766-0.33940.367798
41-0.072533-0.53790.2964
420.0415120.30790.379675
430.0101030.07490.470274
44-0.062499-0.46350.322417
45-0.089505-0.66380.2548
460.0201370.14930.440915
47-0.017907-0.13280.447417
48-0.021977-0.1630.435562



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 2 ; 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')