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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 computationThu, 20 Dec 2012 09:26:06 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/20/t13560135830w7gd2r459l39jl.htm/, Retrieved Thu, 28 Mar 2024 08:29:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=202706, Retrieved Thu, 28 Mar 2024 08:29:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
- R P           [(Partial) Autocorrelation Function] [paper arima 1] [2012-12-11 15:13:54] [dbae308bdff61c0f4902cc85498d0d35]
-                 [(Partial) Autocorrelation Function] [paper arima 8] [2012-12-11 15:45:05] [dbae308bdff61c0f4902cc85498d0d35]
-   P                 [(Partial) Autocorrelation Function] [Paper - Arima ACF...] [2012-12-20 14:26:06] [3c495a368e5e62141567adbfb0420229] [Current]
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Dataseries X:
9700
9081
9084
9743
8587
9731
9563
9998
9437
10038
9918
9252
9737
9035
9133
9487
8700
9627
8947
9283
8829
9947
9628
9318
9605
8640
9214
9567
8547
9185
9470
9123
9278
10170
9434
9655
9429
8739
9552
9687
9019
9672
9206
9069
9788
10312
10105
9863
9656
9295
9946
9701
9049
10190
9706
9765
9893
9994
10433
10073
10112
9266
9820
10097
9115
10411
9678
10408
10153
10368
10581
10597
10680
9738
9556




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202706&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202706&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202706&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'Gwilym Jenkins' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.565353-4.86333e-06
20.0863490.74280.229975
30.1638761.40970.081407
4-0.242834-2.08890.020076
50.1030450.88640.189129
6-0.032838-0.28250.389181
70.05890.50670.306943
8-0.25188-2.16680.016737
90.2751782.36720.01027
10-0.096092-0.82660.205557
11-0.295228-2.53960.006598
120.6258465.38370
13-0.435343-3.7450.000177
140.1736771.4940.06971
150.0865520.74460.229451
16-0.206755-1.77860.039708
170.0639550.55020.291932
180.0702780.60460.273664
19-0.091461-0.78680.216961
20-0.07793-0.67040.25235
210.1593981.37120.087229
22-0.130452-1.12220.132705
23-0.089844-0.77290.22103
240.3712163.19330.001033
25-0.283351-2.43750.008596
260.0886060.76220.224176
270.1358411.16850.123169
28-0.199534-1.71650.045131
290.0624420.53710.29639
300.0184040.15830.43732
31-0.115124-0.99030.162619
320.0590730.50820.306424
330.0374320.3220.37418
34-0.044692-0.38450.350872
35-0.113408-0.97560.166228
360.2817432.42360.008905
37-0.220074-1.89320.031124
380.0999840.86010.196258
390.0996430.85720.197062
40-0.213406-1.83580.035203
410.1796741.54560.063232
42-0.116968-1.00620.158801
43-5.9e-05-5e-040.499798
440.0006010.00520.497946
45-0.021433-0.18440.427111
460.0734730.6320.264655
47-0.167242-1.43870.07723
480.2693282.31680.011641

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.565353 & -4.8633 & 3e-06 \tabularnewline
2 & 0.086349 & 0.7428 & 0.229975 \tabularnewline
3 & 0.163876 & 1.4097 & 0.081407 \tabularnewline
4 & -0.242834 & -2.0889 & 0.020076 \tabularnewline
5 & 0.103045 & 0.8864 & 0.189129 \tabularnewline
6 & -0.032838 & -0.2825 & 0.389181 \tabularnewline
7 & 0.0589 & 0.5067 & 0.306943 \tabularnewline
8 & -0.25188 & -2.1668 & 0.016737 \tabularnewline
9 & 0.275178 & 2.3672 & 0.01027 \tabularnewline
10 & -0.096092 & -0.8266 & 0.205557 \tabularnewline
11 & -0.295228 & -2.5396 & 0.006598 \tabularnewline
12 & 0.625846 & 5.3837 & 0 \tabularnewline
13 & -0.435343 & -3.745 & 0.000177 \tabularnewline
14 & 0.173677 & 1.494 & 0.06971 \tabularnewline
15 & 0.086552 & 0.7446 & 0.229451 \tabularnewline
16 & -0.206755 & -1.7786 & 0.039708 \tabularnewline
17 & 0.063955 & 0.5502 & 0.291932 \tabularnewline
18 & 0.070278 & 0.6046 & 0.273664 \tabularnewline
19 & -0.091461 & -0.7868 & 0.216961 \tabularnewline
20 & -0.07793 & -0.6704 & 0.25235 \tabularnewline
21 & 0.159398 & 1.3712 & 0.087229 \tabularnewline
22 & -0.130452 & -1.1222 & 0.132705 \tabularnewline
23 & -0.089844 & -0.7729 & 0.22103 \tabularnewline
24 & 0.371216 & 3.1933 & 0.001033 \tabularnewline
25 & -0.283351 & -2.4375 & 0.008596 \tabularnewline
26 & 0.088606 & 0.7622 & 0.224176 \tabularnewline
27 & 0.135841 & 1.1685 & 0.123169 \tabularnewline
28 & -0.199534 & -1.7165 & 0.045131 \tabularnewline
29 & 0.062442 & 0.5371 & 0.29639 \tabularnewline
30 & 0.018404 & 0.1583 & 0.43732 \tabularnewline
31 & -0.115124 & -0.9903 & 0.162619 \tabularnewline
32 & 0.059073 & 0.5082 & 0.306424 \tabularnewline
33 & 0.037432 & 0.322 & 0.37418 \tabularnewline
34 & -0.044692 & -0.3845 & 0.350872 \tabularnewline
35 & -0.113408 & -0.9756 & 0.166228 \tabularnewline
36 & 0.281743 & 2.4236 & 0.008905 \tabularnewline
37 & -0.220074 & -1.8932 & 0.031124 \tabularnewline
38 & 0.099984 & 0.8601 & 0.196258 \tabularnewline
39 & 0.099643 & 0.8572 & 0.197062 \tabularnewline
40 & -0.213406 & -1.8358 & 0.035203 \tabularnewline
41 & 0.179674 & 1.5456 & 0.063232 \tabularnewline
42 & -0.116968 & -1.0062 & 0.158801 \tabularnewline
43 & -5.9e-05 & -5e-04 & 0.499798 \tabularnewline
44 & 0.000601 & 0.0052 & 0.497946 \tabularnewline
45 & -0.021433 & -0.1844 & 0.427111 \tabularnewline
46 & 0.073473 & 0.632 & 0.264655 \tabularnewline
47 & -0.167242 & -1.4387 & 0.07723 \tabularnewline
48 & 0.269328 & 2.3168 & 0.011641 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202706&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]-0.565353[/C][C]-4.8633[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.086349[/C][C]0.7428[/C][C]0.229975[/C][/ROW]
[ROW][C]3[/C][C]0.163876[/C][C]1.4097[/C][C]0.081407[/C][/ROW]
[ROW][C]4[/C][C]-0.242834[/C][C]-2.0889[/C][C]0.020076[/C][/ROW]
[ROW][C]5[/C][C]0.103045[/C][C]0.8864[/C][C]0.189129[/C][/ROW]
[ROW][C]6[/C][C]-0.032838[/C][C]-0.2825[/C][C]0.389181[/C][/ROW]
[ROW][C]7[/C][C]0.0589[/C][C]0.5067[/C][C]0.306943[/C][/ROW]
[ROW][C]8[/C][C]-0.25188[/C][C]-2.1668[/C][C]0.016737[/C][/ROW]
[ROW][C]9[/C][C]0.275178[/C][C]2.3672[/C][C]0.01027[/C][/ROW]
[ROW][C]10[/C][C]-0.096092[/C][C]-0.8266[/C][C]0.205557[/C][/ROW]
[ROW][C]11[/C][C]-0.295228[/C][C]-2.5396[/C][C]0.006598[/C][/ROW]
[ROW][C]12[/C][C]0.625846[/C][C]5.3837[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.435343[/C][C]-3.745[/C][C]0.000177[/C][/ROW]
[ROW][C]14[/C][C]0.173677[/C][C]1.494[/C][C]0.06971[/C][/ROW]
[ROW][C]15[/C][C]0.086552[/C][C]0.7446[/C][C]0.229451[/C][/ROW]
[ROW][C]16[/C][C]-0.206755[/C][C]-1.7786[/C][C]0.039708[/C][/ROW]
[ROW][C]17[/C][C]0.063955[/C][C]0.5502[/C][C]0.291932[/C][/ROW]
[ROW][C]18[/C][C]0.070278[/C][C]0.6046[/C][C]0.273664[/C][/ROW]
[ROW][C]19[/C][C]-0.091461[/C][C]-0.7868[/C][C]0.216961[/C][/ROW]
[ROW][C]20[/C][C]-0.07793[/C][C]-0.6704[/C][C]0.25235[/C][/ROW]
[ROW][C]21[/C][C]0.159398[/C][C]1.3712[/C][C]0.087229[/C][/ROW]
[ROW][C]22[/C][C]-0.130452[/C][C]-1.1222[/C][C]0.132705[/C][/ROW]
[ROW][C]23[/C][C]-0.089844[/C][C]-0.7729[/C][C]0.22103[/C][/ROW]
[ROW][C]24[/C][C]0.371216[/C][C]3.1933[/C][C]0.001033[/C][/ROW]
[ROW][C]25[/C][C]-0.283351[/C][C]-2.4375[/C][C]0.008596[/C][/ROW]
[ROW][C]26[/C][C]0.088606[/C][C]0.7622[/C][C]0.224176[/C][/ROW]
[ROW][C]27[/C][C]0.135841[/C][C]1.1685[/C][C]0.123169[/C][/ROW]
[ROW][C]28[/C][C]-0.199534[/C][C]-1.7165[/C][C]0.045131[/C][/ROW]
[ROW][C]29[/C][C]0.062442[/C][C]0.5371[/C][C]0.29639[/C][/ROW]
[ROW][C]30[/C][C]0.018404[/C][C]0.1583[/C][C]0.43732[/C][/ROW]
[ROW][C]31[/C][C]-0.115124[/C][C]-0.9903[/C][C]0.162619[/C][/ROW]
[ROW][C]32[/C][C]0.059073[/C][C]0.5082[/C][C]0.306424[/C][/ROW]
[ROW][C]33[/C][C]0.037432[/C][C]0.322[/C][C]0.37418[/C][/ROW]
[ROW][C]34[/C][C]-0.044692[/C][C]-0.3845[/C][C]0.350872[/C][/ROW]
[ROW][C]35[/C][C]-0.113408[/C][C]-0.9756[/C][C]0.166228[/C][/ROW]
[ROW][C]36[/C][C]0.281743[/C][C]2.4236[/C][C]0.008905[/C][/ROW]
[ROW][C]37[/C][C]-0.220074[/C][C]-1.8932[/C][C]0.031124[/C][/ROW]
[ROW][C]38[/C][C]0.099984[/C][C]0.8601[/C][C]0.196258[/C][/ROW]
[ROW][C]39[/C][C]0.099643[/C][C]0.8572[/C][C]0.197062[/C][/ROW]
[ROW][C]40[/C][C]-0.213406[/C][C]-1.8358[/C][C]0.035203[/C][/ROW]
[ROW][C]41[/C][C]0.179674[/C][C]1.5456[/C][C]0.063232[/C][/ROW]
[ROW][C]42[/C][C]-0.116968[/C][C]-1.0062[/C][C]0.158801[/C][/ROW]
[ROW][C]43[/C][C]-5.9e-05[/C][C]-5e-04[/C][C]0.499798[/C][/ROW]
[ROW][C]44[/C][C]0.000601[/C][C]0.0052[/C][C]0.497946[/C][/ROW]
[ROW][C]45[/C][C]-0.021433[/C][C]-0.1844[/C][C]0.427111[/C][/ROW]
[ROW][C]46[/C][C]0.073473[/C][C]0.632[/C][C]0.264655[/C][/ROW]
[ROW][C]47[/C][C]-0.167242[/C][C]-1.4387[/C][C]0.07723[/C][/ROW]
[ROW][C]48[/C][C]0.269328[/C][C]2.3168[/C][C]0.011641[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202706&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202706&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
1-0.565353-4.86333e-06
20.0863490.74280.229975
30.1638761.40970.081407
4-0.242834-2.08890.020076
50.1030450.88640.189129
6-0.032838-0.28250.389181
70.05890.50670.306943
8-0.25188-2.16680.016737
90.2751782.36720.01027
10-0.096092-0.82660.205557
11-0.295228-2.53960.006598
120.6258465.38370
13-0.435343-3.7450.000177
140.1736771.4940.06971
150.0865520.74460.229451
16-0.206755-1.77860.039708
170.0639550.55020.291932
180.0702780.60460.273664
19-0.091461-0.78680.216961
20-0.07793-0.67040.25235
210.1593981.37120.087229
22-0.130452-1.12220.132705
23-0.089844-0.77290.22103
240.3712163.19330.001033
25-0.283351-2.43750.008596
260.0886060.76220.224176
270.1358411.16850.123169
28-0.199534-1.71650.045131
290.0624420.53710.29639
300.0184040.15830.43732
31-0.115124-0.99030.162619
320.0590730.50820.306424
330.0374320.3220.37418
34-0.044692-0.38450.350872
35-0.113408-0.97560.166228
360.2817432.42360.008905
37-0.220074-1.89320.031124
380.0999840.86010.196258
390.0996430.85720.197062
40-0.213406-1.83580.035203
410.1796741.54560.063232
42-0.116968-1.00620.158801
43-5.9e-05-5e-040.499798
440.0006010.00520.497946
45-0.021433-0.18440.427111
460.0734730.6320.264655
47-0.167242-1.43870.07723
480.2693282.31680.011641







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.565353-4.86333e-06
2-0.34286-2.94940.00213
30.0592850.510.305789
4-0.104493-0.89890.185816
5-0.132637-1.1410.128777
6-0.144253-1.24090.10928
70.0595110.51190.305112
8-0.342814-2.9490.002132
9-0.113958-0.98030.165065
10-0.00473-0.04070.483825
11-0.492498-4.23663.2e-05
120.1888881.62490.054221
130.1394431.19950.117074
140.1058140.91030.182823
150.0956270.82260.206684
160.0148490.12770.449352
17-0.108111-0.930.177697
180.0818410.7040.241815
19-0.104499-0.89890.185801
200.068750.59140.278024
21-0.084762-0.72920.234105
22-0.068488-0.58920.278775
23-0.006232-0.05360.478695
240.0711250.61180.271258
250.1421311.22270.112669
26-0.033479-0.2880.387075
270.0002380.0020.499186
280.100020.86040.196174
290.0272050.2340.407805
30-0.175625-1.51080.067551
31-0.116927-1.00580.158885
32-0.004827-0.04150.483496
33-0.001153-0.00990.496056
340.1040570.89510.18681
35-0.04906-0.4220.337112
36-0.046461-0.39970.345274
37-0.110146-0.94750.17323
38-0.024983-0.21490.415212
39-0.008269-0.07110.471741
40-0.100559-0.8650.194905
410.0260490.22410.411656
42-0.073003-0.6280.265969
430.0589920.50750.306669
440.0372690.32060.37471
45-0.179514-1.54420.063399
46-0.021799-0.18750.425882
47-0.040694-0.35010.363644
48-0.00172-0.01480.494118

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.565353 & -4.8633 & 3e-06 \tabularnewline
2 & -0.34286 & -2.9494 & 0.00213 \tabularnewline
3 & 0.059285 & 0.51 & 0.305789 \tabularnewline
4 & -0.104493 & -0.8989 & 0.185816 \tabularnewline
5 & -0.132637 & -1.141 & 0.128777 \tabularnewline
6 & -0.144253 & -1.2409 & 0.10928 \tabularnewline
7 & 0.059511 & 0.5119 & 0.305112 \tabularnewline
8 & -0.342814 & -2.949 & 0.002132 \tabularnewline
9 & -0.113958 & -0.9803 & 0.165065 \tabularnewline
10 & -0.00473 & -0.0407 & 0.483825 \tabularnewline
11 & -0.492498 & -4.2366 & 3.2e-05 \tabularnewline
12 & 0.188888 & 1.6249 & 0.054221 \tabularnewline
13 & 0.139443 & 1.1995 & 0.117074 \tabularnewline
14 & 0.105814 & 0.9103 & 0.182823 \tabularnewline
15 & 0.095627 & 0.8226 & 0.206684 \tabularnewline
16 & 0.014849 & 0.1277 & 0.449352 \tabularnewline
17 & -0.108111 & -0.93 & 0.177697 \tabularnewline
18 & 0.081841 & 0.704 & 0.241815 \tabularnewline
19 & -0.104499 & -0.8989 & 0.185801 \tabularnewline
20 & 0.06875 & 0.5914 & 0.278024 \tabularnewline
21 & -0.084762 & -0.7292 & 0.234105 \tabularnewline
22 & -0.068488 & -0.5892 & 0.278775 \tabularnewline
23 & -0.006232 & -0.0536 & 0.478695 \tabularnewline
24 & 0.071125 & 0.6118 & 0.271258 \tabularnewline
25 & 0.142131 & 1.2227 & 0.112669 \tabularnewline
26 & -0.033479 & -0.288 & 0.387075 \tabularnewline
27 & 0.000238 & 0.002 & 0.499186 \tabularnewline
28 & 0.10002 & 0.8604 & 0.196174 \tabularnewline
29 & 0.027205 & 0.234 & 0.407805 \tabularnewline
30 & -0.175625 & -1.5108 & 0.067551 \tabularnewline
31 & -0.116927 & -1.0058 & 0.158885 \tabularnewline
32 & -0.004827 & -0.0415 & 0.483496 \tabularnewline
33 & -0.001153 & -0.0099 & 0.496056 \tabularnewline
34 & 0.104057 & 0.8951 & 0.18681 \tabularnewline
35 & -0.04906 & -0.422 & 0.337112 \tabularnewline
36 & -0.046461 & -0.3997 & 0.345274 \tabularnewline
37 & -0.110146 & -0.9475 & 0.17323 \tabularnewline
38 & -0.024983 & -0.2149 & 0.415212 \tabularnewline
39 & -0.008269 & -0.0711 & 0.471741 \tabularnewline
40 & -0.100559 & -0.865 & 0.194905 \tabularnewline
41 & 0.026049 & 0.2241 & 0.411656 \tabularnewline
42 & -0.073003 & -0.628 & 0.265969 \tabularnewline
43 & 0.058992 & 0.5075 & 0.306669 \tabularnewline
44 & 0.037269 & 0.3206 & 0.37471 \tabularnewline
45 & -0.179514 & -1.5442 & 0.063399 \tabularnewline
46 & -0.021799 & -0.1875 & 0.425882 \tabularnewline
47 & -0.040694 & -0.3501 & 0.363644 \tabularnewline
48 & -0.00172 & -0.0148 & 0.494118 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=202706&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]-0.565353[/C][C]-4.8633[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.34286[/C][C]-2.9494[/C][C]0.00213[/C][/ROW]
[ROW][C]3[/C][C]0.059285[/C][C]0.51[/C][C]0.305789[/C][/ROW]
[ROW][C]4[/C][C]-0.104493[/C][C]-0.8989[/C][C]0.185816[/C][/ROW]
[ROW][C]5[/C][C]-0.132637[/C][C]-1.141[/C][C]0.128777[/C][/ROW]
[ROW][C]6[/C][C]-0.144253[/C][C]-1.2409[/C][C]0.10928[/C][/ROW]
[ROW][C]7[/C][C]0.059511[/C][C]0.5119[/C][C]0.305112[/C][/ROW]
[ROW][C]8[/C][C]-0.342814[/C][C]-2.949[/C][C]0.002132[/C][/ROW]
[ROW][C]9[/C][C]-0.113958[/C][C]-0.9803[/C][C]0.165065[/C][/ROW]
[ROW][C]10[/C][C]-0.00473[/C][C]-0.0407[/C][C]0.483825[/C][/ROW]
[ROW][C]11[/C][C]-0.492498[/C][C]-4.2366[/C][C]3.2e-05[/C][/ROW]
[ROW][C]12[/C][C]0.188888[/C][C]1.6249[/C][C]0.054221[/C][/ROW]
[ROW][C]13[/C][C]0.139443[/C][C]1.1995[/C][C]0.117074[/C][/ROW]
[ROW][C]14[/C][C]0.105814[/C][C]0.9103[/C][C]0.182823[/C][/ROW]
[ROW][C]15[/C][C]0.095627[/C][C]0.8226[/C][C]0.206684[/C][/ROW]
[ROW][C]16[/C][C]0.014849[/C][C]0.1277[/C][C]0.449352[/C][/ROW]
[ROW][C]17[/C][C]-0.108111[/C][C]-0.93[/C][C]0.177697[/C][/ROW]
[ROW][C]18[/C][C]0.081841[/C][C]0.704[/C][C]0.241815[/C][/ROW]
[ROW][C]19[/C][C]-0.104499[/C][C]-0.8989[/C][C]0.185801[/C][/ROW]
[ROW][C]20[/C][C]0.06875[/C][C]0.5914[/C][C]0.278024[/C][/ROW]
[ROW][C]21[/C][C]-0.084762[/C][C]-0.7292[/C][C]0.234105[/C][/ROW]
[ROW][C]22[/C][C]-0.068488[/C][C]-0.5892[/C][C]0.278775[/C][/ROW]
[ROW][C]23[/C][C]-0.006232[/C][C]-0.0536[/C][C]0.478695[/C][/ROW]
[ROW][C]24[/C][C]0.071125[/C][C]0.6118[/C][C]0.271258[/C][/ROW]
[ROW][C]25[/C][C]0.142131[/C][C]1.2227[/C][C]0.112669[/C][/ROW]
[ROW][C]26[/C][C]-0.033479[/C][C]-0.288[/C][C]0.387075[/C][/ROW]
[ROW][C]27[/C][C]0.000238[/C][C]0.002[/C][C]0.499186[/C][/ROW]
[ROW][C]28[/C][C]0.10002[/C][C]0.8604[/C][C]0.196174[/C][/ROW]
[ROW][C]29[/C][C]0.027205[/C][C]0.234[/C][C]0.407805[/C][/ROW]
[ROW][C]30[/C][C]-0.175625[/C][C]-1.5108[/C][C]0.067551[/C][/ROW]
[ROW][C]31[/C][C]-0.116927[/C][C]-1.0058[/C][C]0.158885[/C][/ROW]
[ROW][C]32[/C][C]-0.004827[/C][C]-0.0415[/C][C]0.483496[/C][/ROW]
[ROW][C]33[/C][C]-0.001153[/C][C]-0.0099[/C][C]0.496056[/C][/ROW]
[ROW][C]34[/C][C]0.104057[/C][C]0.8951[/C][C]0.18681[/C][/ROW]
[ROW][C]35[/C][C]-0.04906[/C][C]-0.422[/C][C]0.337112[/C][/ROW]
[ROW][C]36[/C][C]-0.046461[/C][C]-0.3997[/C][C]0.345274[/C][/ROW]
[ROW][C]37[/C][C]-0.110146[/C][C]-0.9475[/C][C]0.17323[/C][/ROW]
[ROW][C]38[/C][C]-0.024983[/C][C]-0.2149[/C][C]0.415212[/C][/ROW]
[ROW][C]39[/C][C]-0.008269[/C][C]-0.0711[/C][C]0.471741[/C][/ROW]
[ROW][C]40[/C][C]-0.100559[/C][C]-0.865[/C][C]0.194905[/C][/ROW]
[ROW][C]41[/C][C]0.026049[/C][C]0.2241[/C][C]0.411656[/C][/ROW]
[ROW][C]42[/C][C]-0.073003[/C][C]-0.628[/C][C]0.265969[/C][/ROW]
[ROW][C]43[/C][C]0.058992[/C][C]0.5075[/C][C]0.306669[/C][/ROW]
[ROW][C]44[/C][C]0.037269[/C][C]0.3206[/C][C]0.37471[/C][/ROW]
[ROW][C]45[/C][C]-0.179514[/C][C]-1.5442[/C][C]0.063399[/C][/ROW]
[ROW][C]46[/C][C]-0.021799[/C][C]-0.1875[/C][C]0.425882[/C][/ROW]
[ROW][C]47[/C][C]-0.040694[/C][C]-0.3501[/C][C]0.363644[/C][/ROW]
[ROW][C]48[/C][C]-0.00172[/C][C]-0.0148[/C][C]0.494118[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=202706&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=202706&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
1-0.565353-4.86333e-06
2-0.34286-2.94940.00213
30.0592850.510.305789
4-0.104493-0.89890.185816
5-0.132637-1.1410.128777
6-0.144253-1.24090.10928
70.0595110.51190.305112
8-0.342814-2.9490.002132
9-0.113958-0.98030.165065
10-0.00473-0.04070.483825
11-0.492498-4.23663.2e-05
120.1888881.62490.054221
130.1394431.19950.117074
140.1058140.91030.182823
150.0956270.82260.206684
160.0148490.12770.449352
17-0.108111-0.930.177697
180.0818410.7040.241815
19-0.104499-0.89890.185801
200.068750.59140.278024
21-0.084762-0.72920.234105
22-0.068488-0.58920.278775
23-0.006232-0.05360.478695
240.0711250.61180.271258
250.1421311.22270.112669
26-0.033479-0.2880.387075
270.0002380.0020.499186
280.100020.86040.196174
290.0272050.2340.407805
30-0.175625-1.51080.067551
31-0.116927-1.00580.158885
32-0.004827-0.04150.483496
33-0.001153-0.00990.496056
340.1040570.89510.18681
35-0.04906-0.4220.337112
36-0.046461-0.39970.345274
37-0.110146-0.94750.17323
38-0.024983-0.21490.415212
39-0.008269-0.07110.471741
40-0.100559-0.8650.194905
410.0260490.22410.411656
42-0.073003-0.6280.265969
430.0589920.50750.306669
440.0372690.32060.37471
45-0.179514-1.54420.063399
46-0.021799-0.18750.425882
47-0.040694-0.35010.363644
48-0.00172-0.01480.494118



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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')