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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, 07 Dec 2010 16:00:18 +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/07/t1291737499bk4zigrciojdtz3.htm/, Retrieved Fri, 03 May 2024 18:29:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106460, Retrieved Fri, 03 May 2024 18:29:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162
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 09:05:21] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [ACF geen differen...] [2010-12-03 12:24:26] [9f32078fdcdc094ca748857d5ebdb3de]
-    D      [(Partial) Autocorrelation Function] [] [2010-12-07 15:41:58] [ed939ef6f97e5f2afb6796311d9e7a5f]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-07 16:00:18] [f9aa24c2294a5d3925c7278aa2e9a372] [Current]
Feedback Forum

Post a new message
Dataseries X:
31.514
27.071
29.462
26.105
22.397
23.843
21.705
18.089
20.764
25.316
17.704
15.548
28.029
29.383
36.438
32.034
22.679
24.319
18.004
17.537
20.366
22.782
19.169
13.807
29.743
25.591
29.096
26.482
22.405
27.044
17.970
18.730
19.684
19.785
18.479
10.698
31.956
29.506
34.506
27.165
26.736
23.691
18.157
17.328
18.205
20.995
17.382
9.367
31.124
26.551
30.651
25.859
25.100
25.778
20.418
18.688
20.424
24.776
19.814
12.738
31.566
30.111
30.019
31.934
25.826
26.835
20.205
17.789
20.520
22.518
15.572
11.509
25.447
24.090
27.786
26.195
20.516
22.759
19.028
16.971
20.036
22.485
18.730
14.538
27.561
25.985
34.670
32.066
27.186
29.586
21.359
21.553
19.573
24.256




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106460&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106460&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106460&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.370752-3.33680.000641
20.1682721.51440.066903
3-0.161982-1.45780.074376
4-0.110399-0.99360.161691
50.0259290.23340.408034
6-0.008737-0.07860.46876
7-0.028594-0.25740.39878
80.1395981.25640.106294
90.0784830.70630.241
10-0.063258-0.56930.285356
11-0.065504-0.58950.278571
12-0.152153-1.36940.087333
13-0.148289-1.33460.092873
140.0503990.45360.325668
150.1337051.20330.116174
16-0.011602-0.10440.458546
170.0432810.38950.348952
18-0.006554-0.0590.476556
19-0.094668-0.8520.198359
20-0.04626-0.41630.339131
210.1109630.99870.160466
22-0.277767-2.49990.007221
230.4221073.7990.00014
24-0.190466-1.71420.045159
250.1819931.63790.052657
260.0028960.02610.489637
27-0.07523-0.67710.250146
28-0.048023-0.43220.333371
290.0593150.53380.297459
30-0.042238-0.38010.352419
310.0211210.19010.424858
320.0542240.4880.313427
33-0.101076-0.90970.182845
340.1145881.03130.152737
35-0.03405-0.30640.380026
36-0.11262-1.01360.1569
370.0155980.14040.444352
38-0.061452-0.55310.29087
390.0274330.24690.402807
400.0300960.27090.393592
41-0.017588-0.15830.437311
420.0199330.17940.429039
430.0030160.02710.489205
440.0973750.87640.191709
45-0.157563-1.41810.080004
460.1471121.3240.094613
47-0.102253-0.92030.180081
48-0.033412-0.30070.382204

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.370752 & -3.3368 & 0.000641 \tabularnewline
2 & 0.168272 & 1.5144 & 0.066903 \tabularnewline
3 & -0.161982 & -1.4578 & 0.074376 \tabularnewline
4 & -0.110399 & -0.9936 & 0.161691 \tabularnewline
5 & 0.025929 & 0.2334 & 0.408034 \tabularnewline
6 & -0.008737 & -0.0786 & 0.46876 \tabularnewline
7 & -0.028594 & -0.2574 & 0.39878 \tabularnewline
8 & 0.139598 & 1.2564 & 0.106294 \tabularnewline
9 & 0.078483 & 0.7063 & 0.241 \tabularnewline
10 & -0.063258 & -0.5693 & 0.285356 \tabularnewline
11 & -0.065504 & -0.5895 & 0.278571 \tabularnewline
12 & -0.152153 & -1.3694 & 0.087333 \tabularnewline
13 & -0.148289 & -1.3346 & 0.092873 \tabularnewline
14 & 0.050399 & 0.4536 & 0.325668 \tabularnewline
15 & 0.133705 & 1.2033 & 0.116174 \tabularnewline
16 & -0.011602 & -0.1044 & 0.458546 \tabularnewline
17 & 0.043281 & 0.3895 & 0.348952 \tabularnewline
18 & -0.006554 & -0.059 & 0.476556 \tabularnewline
19 & -0.094668 & -0.852 & 0.198359 \tabularnewline
20 & -0.04626 & -0.4163 & 0.339131 \tabularnewline
21 & 0.110963 & 0.9987 & 0.160466 \tabularnewline
22 & -0.277767 & -2.4999 & 0.007221 \tabularnewline
23 & 0.422107 & 3.799 & 0.00014 \tabularnewline
24 & -0.190466 & -1.7142 & 0.045159 \tabularnewline
25 & 0.181993 & 1.6379 & 0.052657 \tabularnewline
26 & 0.002896 & 0.0261 & 0.489637 \tabularnewline
27 & -0.07523 & -0.6771 & 0.250146 \tabularnewline
28 & -0.048023 & -0.4322 & 0.333371 \tabularnewline
29 & 0.059315 & 0.5338 & 0.297459 \tabularnewline
30 & -0.042238 & -0.3801 & 0.352419 \tabularnewline
31 & 0.021121 & 0.1901 & 0.424858 \tabularnewline
32 & 0.054224 & 0.488 & 0.313427 \tabularnewline
33 & -0.101076 & -0.9097 & 0.182845 \tabularnewline
34 & 0.114588 & 1.0313 & 0.152737 \tabularnewline
35 & -0.03405 & -0.3064 & 0.380026 \tabularnewline
36 & -0.11262 & -1.0136 & 0.1569 \tabularnewline
37 & 0.015598 & 0.1404 & 0.444352 \tabularnewline
38 & -0.061452 & -0.5531 & 0.29087 \tabularnewline
39 & 0.027433 & 0.2469 & 0.402807 \tabularnewline
40 & 0.030096 & 0.2709 & 0.393592 \tabularnewline
41 & -0.017588 & -0.1583 & 0.437311 \tabularnewline
42 & 0.019933 & 0.1794 & 0.429039 \tabularnewline
43 & 0.003016 & 0.0271 & 0.489205 \tabularnewline
44 & 0.097375 & 0.8764 & 0.191709 \tabularnewline
45 & -0.157563 & -1.4181 & 0.080004 \tabularnewline
46 & 0.147112 & 1.324 & 0.094613 \tabularnewline
47 & -0.102253 & -0.9203 & 0.180081 \tabularnewline
48 & -0.033412 & -0.3007 & 0.382204 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106460&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]-0.370752[/C][C]-3.3368[/C][C]0.000641[/C][/ROW]
[ROW][C]2[/C][C]0.168272[/C][C]1.5144[/C][C]0.066903[/C][/ROW]
[ROW][C]3[/C][C]-0.161982[/C][C]-1.4578[/C][C]0.074376[/C][/ROW]
[ROW][C]4[/C][C]-0.110399[/C][C]-0.9936[/C][C]0.161691[/C][/ROW]
[ROW][C]5[/C][C]0.025929[/C][C]0.2334[/C][C]0.408034[/C][/ROW]
[ROW][C]6[/C][C]-0.008737[/C][C]-0.0786[/C][C]0.46876[/C][/ROW]
[ROW][C]7[/C][C]-0.028594[/C][C]-0.2574[/C][C]0.39878[/C][/ROW]
[ROW][C]8[/C][C]0.139598[/C][C]1.2564[/C][C]0.106294[/C][/ROW]
[ROW][C]9[/C][C]0.078483[/C][C]0.7063[/C][C]0.241[/C][/ROW]
[ROW][C]10[/C][C]-0.063258[/C][C]-0.5693[/C][C]0.285356[/C][/ROW]
[ROW][C]11[/C][C]-0.065504[/C][C]-0.5895[/C][C]0.278571[/C][/ROW]
[ROW][C]12[/C][C]-0.152153[/C][C]-1.3694[/C][C]0.087333[/C][/ROW]
[ROW][C]13[/C][C]-0.148289[/C][C]-1.3346[/C][C]0.092873[/C][/ROW]
[ROW][C]14[/C][C]0.050399[/C][C]0.4536[/C][C]0.325668[/C][/ROW]
[ROW][C]15[/C][C]0.133705[/C][C]1.2033[/C][C]0.116174[/C][/ROW]
[ROW][C]16[/C][C]-0.011602[/C][C]-0.1044[/C][C]0.458546[/C][/ROW]
[ROW][C]17[/C][C]0.043281[/C][C]0.3895[/C][C]0.348952[/C][/ROW]
[ROW][C]18[/C][C]-0.006554[/C][C]-0.059[/C][C]0.476556[/C][/ROW]
[ROW][C]19[/C][C]-0.094668[/C][C]-0.852[/C][C]0.198359[/C][/ROW]
[ROW][C]20[/C][C]-0.04626[/C][C]-0.4163[/C][C]0.339131[/C][/ROW]
[ROW][C]21[/C][C]0.110963[/C][C]0.9987[/C][C]0.160466[/C][/ROW]
[ROW][C]22[/C][C]-0.277767[/C][C]-2.4999[/C][C]0.007221[/C][/ROW]
[ROW][C]23[/C][C]0.422107[/C][C]3.799[/C][C]0.00014[/C][/ROW]
[ROW][C]24[/C][C]-0.190466[/C][C]-1.7142[/C][C]0.045159[/C][/ROW]
[ROW][C]25[/C][C]0.181993[/C][C]1.6379[/C][C]0.052657[/C][/ROW]
[ROW][C]26[/C][C]0.002896[/C][C]0.0261[/C][C]0.489637[/C][/ROW]
[ROW][C]27[/C][C]-0.07523[/C][C]-0.6771[/C][C]0.250146[/C][/ROW]
[ROW][C]28[/C][C]-0.048023[/C][C]-0.4322[/C][C]0.333371[/C][/ROW]
[ROW][C]29[/C][C]0.059315[/C][C]0.5338[/C][C]0.297459[/C][/ROW]
[ROW][C]30[/C][C]-0.042238[/C][C]-0.3801[/C][C]0.352419[/C][/ROW]
[ROW][C]31[/C][C]0.021121[/C][C]0.1901[/C][C]0.424858[/C][/ROW]
[ROW][C]32[/C][C]0.054224[/C][C]0.488[/C][C]0.313427[/C][/ROW]
[ROW][C]33[/C][C]-0.101076[/C][C]-0.9097[/C][C]0.182845[/C][/ROW]
[ROW][C]34[/C][C]0.114588[/C][C]1.0313[/C][C]0.152737[/C][/ROW]
[ROW][C]35[/C][C]-0.03405[/C][C]-0.3064[/C][C]0.380026[/C][/ROW]
[ROW][C]36[/C][C]-0.11262[/C][C]-1.0136[/C][C]0.1569[/C][/ROW]
[ROW][C]37[/C][C]0.015598[/C][C]0.1404[/C][C]0.444352[/C][/ROW]
[ROW][C]38[/C][C]-0.061452[/C][C]-0.5531[/C][C]0.29087[/C][/ROW]
[ROW][C]39[/C][C]0.027433[/C][C]0.2469[/C][C]0.402807[/C][/ROW]
[ROW][C]40[/C][C]0.030096[/C][C]0.2709[/C][C]0.393592[/C][/ROW]
[ROW][C]41[/C][C]-0.017588[/C][C]-0.1583[/C][C]0.437311[/C][/ROW]
[ROW][C]42[/C][C]0.019933[/C][C]0.1794[/C][C]0.429039[/C][/ROW]
[ROW][C]43[/C][C]0.003016[/C][C]0.0271[/C][C]0.489205[/C][/ROW]
[ROW][C]44[/C][C]0.097375[/C][C]0.8764[/C][C]0.191709[/C][/ROW]
[ROW][C]45[/C][C]-0.157563[/C][C]-1.4181[/C][C]0.080004[/C][/ROW]
[ROW][C]46[/C][C]0.147112[/C][C]1.324[/C][C]0.094613[/C][/ROW]
[ROW][C]47[/C][C]-0.102253[/C][C]-0.9203[/C][C]0.180081[/C][/ROW]
[ROW][C]48[/C][C]-0.033412[/C][C]-0.3007[/C][C]0.382204[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106460&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106460&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
1-0.370752-3.33680.000641
20.1682721.51440.066903
3-0.161982-1.45780.074376
4-0.110399-0.99360.161691
50.0259290.23340.408034
6-0.008737-0.07860.46876
7-0.028594-0.25740.39878
80.1395981.25640.106294
90.0784830.70630.241
10-0.063258-0.56930.285356
11-0.065504-0.58950.278571
12-0.152153-1.36940.087333
13-0.148289-1.33460.092873
140.0503990.45360.325668
150.1337051.20330.116174
16-0.011602-0.10440.458546
170.0432810.38950.348952
18-0.006554-0.0590.476556
19-0.094668-0.8520.198359
20-0.04626-0.41630.339131
210.1109630.99870.160466
22-0.277767-2.49990.007221
230.4221073.7990.00014
24-0.190466-1.71420.045159
250.1819931.63790.052657
260.0028960.02610.489637
27-0.07523-0.67710.250146
28-0.048023-0.43220.333371
290.0593150.53380.297459
30-0.042238-0.38010.352419
310.0211210.19010.424858
320.0542240.4880.313427
33-0.101076-0.90970.182845
340.1145881.03130.152737
35-0.03405-0.30640.380026
36-0.11262-1.01360.1569
370.0155980.14040.444352
38-0.061452-0.55310.29087
390.0274330.24690.402807
400.0300960.27090.393592
41-0.017588-0.15830.437311
420.0199330.17940.429039
430.0030160.02710.489205
440.0973750.87640.191709
45-0.157563-1.41810.080004
460.1471121.3240.094613
47-0.102253-0.92030.180081
48-0.033412-0.30070.382204







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.370752-3.33680.000641
20.0357250.32150.37432
3-0.102826-0.92540.178746
4-0.241293-2.17160.016404
5-0.092028-0.82820.204981
6-0.023313-0.20980.41717
7-0.112041-1.00840.158141
80.0683290.6150.270153
90.2014031.81260.036798
10-0.002032-0.01830.492727
11-0.117613-1.05850.146483
12-0.154051-1.38650.084706
13-0.2995-2.69550.004272
14-0.227169-2.04450.022075
150.0645720.58120.281376
16-0.046482-0.41830.338405
17-0.165075-1.48570.070623
18-0.013857-0.12470.45053
19-0.073179-0.65860.256006
20-0.196306-1.76670.040519
210.1998821.79890.037876
22-0.237506-2.13760.017784
230.0394380.35490.361778
24-0.043488-0.39140.348266
25-0.084161-0.75740.22549
260.0054210.04880.480603
270.109450.9850.163767
28-0.043284-0.38960.348945
290.0063550.05720.477266
300.0644230.57980.281828
31-0.117595-1.05840.146521
32-0.084635-0.76170.22422
33-0.072939-0.65650.256696
340.0158890.1430.443323
350.0145810.13120.447959
36-0.051901-0.46710.320838
370.0045510.0410.483714
38-0.132855-1.19570.117652
39-0.013711-0.12340.451047
400.0299230.26930.394189
41-0.118234-1.06410.145221
420.0040580.03650.485476
430.0627760.5650.286823
44-0.046469-0.41820.338445
450.0281010.25290.400491
460.0800180.72020.236749
470.04880.43920.330842
48-0.184525-1.66070.050317

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.370752 & -3.3368 & 0.000641 \tabularnewline
2 & 0.035725 & 0.3215 & 0.37432 \tabularnewline
3 & -0.102826 & -0.9254 & 0.178746 \tabularnewline
4 & -0.241293 & -2.1716 & 0.016404 \tabularnewline
5 & -0.092028 & -0.8282 & 0.204981 \tabularnewline
6 & -0.023313 & -0.2098 & 0.41717 \tabularnewline
7 & -0.112041 & -1.0084 & 0.158141 \tabularnewline
8 & 0.068329 & 0.615 & 0.270153 \tabularnewline
9 & 0.201403 & 1.8126 & 0.036798 \tabularnewline
10 & -0.002032 & -0.0183 & 0.492727 \tabularnewline
11 & -0.117613 & -1.0585 & 0.146483 \tabularnewline
12 & -0.154051 & -1.3865 & 0.084706 \tabularnewline
13 & -0.2995 & -2.6955 & 0.004272 \tabularnewline
14 & -0.227169 & -2.0445 & 0.022075 \tabularnewline
15 & 0.064572 & 0.5812 & 0.281376 \tabularnewline
16 & -0.046482 & -0.4183 & 0.338405 \tabularnewline
17 & -0.165075 & -1.4857 & 0.070623 \tabularnewline
18 & -0.013857 & -0.1247 & 0.45053 \tabularnewline
19 & -0.073179 & -0.6586 & 0.256006 \tabularnewline
20 & -0.196306 & -1.7667 & 0.040519 \tabularnewline
21 & 0.199882 & 1.7989 & 0.037876 \tabularnewline
22 & -0.237506 & -2.1376 & 0.017784 \tabularnewline
23 & 0.039438 & 0.3549 & 0.361778 \tabularnewline
24 & -0.043488 & -0.3914 & 0.348266 \tabularnewline
25 & -0.084161 & -0.7574 & 0.22549 \tabularnewline
26 & 0.005421 & 0.0488 & 0.480603 \tabularnewline
27 & 0.10945 & 0.985 & 0.163767 \tabularnewline
28 & -0.043284 & -0.3896 & 0.348945 \tabularnewline
29 & 0.006355 & 0.0572 & 0.477266 \tabularnewline
30 & 0.064423 & 0.5798 & 0.281828 \tabularnewline
31 & -0.117595 & -1.0584 & 0.146521 \tabularnewline
32 & -0.084635 & -0.7617 & 0.22422 \tabularnewline
33 & -0.072939 & -0.6565 & 0.256696 \tabularnewline
34 & 0.015889 & 0.143 & 0.443323 \tabularnewline
35 & 0.014581 & 0.1312 & 0.447959 \tabularnewline
36 & -0.051901 & -0.4671 & 0.320838 \tabularnewline
37 & 0.004551 & 0.041 & 0.483714 \tabularnewline
38 & -0.132855 & -1.1957 & 0.117652 \tabularnewline
39 & -0.013711 & -0.1234 & 0.451047 \tabularnewline
40 & 0.029923 & 0.2693 & 0.394189 \tabularnewline
41 & -0.118234 & -1.0641 & 0.145221 \tabularnewline
42 & 0.004058 & 0.0365 & 0.485476 \tabularnewline
43 & 0.062776 & 0.565 & 0.286823 \tabularnewline
44 & -0.046469 & -0.4182 & 0.338445 \tabularnewline
45 & 0.028101 & 0.2529 & 0.400491 \tabularnewline
46 & 0.080018 & 0.7202 & 0.236749 \tabularnewline
47 & 0.0488 & 0.4392 & 0.330842 \tabularnewline
48 & -0.184525 & -1.6607 & 0.050317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106460&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]-0.370752[/C][C]-3.3368[/C][C]0.000641[/C][/ROW]
[ROW][C]2[/C][C]0.035725[/C][C]0.3215[/C][C]0.37432[/C][/ROW]
[ROW][C]3[/C][C]-0.102826[/C][C]-0.9254[/C][C]0.178746[/C][/ROW]
[ROW][C]4[/C][C]-0.241293[/C][C]-2.1716[/C][C]0.016404[/C][/ROW]
[ROW][C]5[/C][C]-0.092028[/C][C]-0.8282[/C][C]0.204981[/C][/ROW]
[ROW][C]6[/C][C]-0.023313[/C][C]-0.2098[/C][C]0.41717[/C][/ROW]
[ROW][C]7[/C][C]-0.112041[/C][C]-1.0084[/C][C]0.158141[/C][/ROW]
[ROW][C]8[/C][C]0.068329[/C][C]0.615[/C][C]0.270153[/C][/ROW]
[ROW][C]9[/C][C]0.201403[/C][C]1.8126[/C][C]0.036798[/C][/ROW]
[ROW][C]10[/C][C]-0.002032[/C][C]-0.0183[/C][C]0.492727[/C][/ROW]
[ROW][C]11[/C][C]-0.117613[/C][C]-1.0585[/C][C]0.146483[/C][/ROW]
[ROW][C]12[/C][C]-0.154051[/C][C]-1.3865[/C][C]0.084706[/C][/ROW]
[ROW][C]13[/C][C]-0.2995[/C][C]-2.6955[/C][C]0.004272[/C][/ROW]
[ROW][C]14[/C][C]-0.227169[/C][C]-2.0445[/C][C]0.022075[/C][/ROW]
[ROW][C]15[/C][C]0.064572[/C][C]0.5812[/C][C]0.281376[/C][/ROW]
[ROW][C]16[/C][C]-0.046482[/C][C]-0.4183[/C][C]0.338405[/C][/ROW]
[ROW][C]17[/C][C]-0.165075[/C][C]-1.4857[/C][C]0.070623[/C][/ROW]
[ROW][C]18[/C][C]-0.013857[/C][C]-0.1247[/C][C]0.45053[/C][/ROW]
[ROW][C]19[/C][C]-0.073179[/C][C]-0.6586[/C][C]0.256006[/C][/ROW]
[ROW][C]20[/C][C]-0.196306[/C][C]-1.7667[/C][C]0.040519[/C][/ROW]
[ROW][C]21[/C][C]0.199882[/C][C]1.7989[/C][C]0.037876[/C][/ROW]
[ROW][C]22[/C][C]-0.237506[/C][C]-2.1376[/C][C]0.017784[/C][/ROW]
[ROW][C]23[/C][C]0.039438[/C][C]0.3549[/C][C]0.361778[/C][/ROW]
[ROW][C]24[/C][C]-0.043488[/C][C]-0.3914[/C][C]0.348266[/C][/ROW]
[ROW][C]25[/C][C]-0.084161[/C][C]-0.7574[/C][C]0.22549[/C][/ROW]
[ROW][C]26[/C][C]0.005421[/C][C]0.0488[/C][C]0.480603[/C][/ROW]
[ROW][C]27[/C][C]0.10945[/C][C]0.985[/C][C]0.163767[/C][/ROW]
[ROW][C]28[/C][C]-0.043284[/C][C]-0.3896[/C][C]0.348945[/C][/ROW]
[ROW][C]29[/C][C]0.006355[/C][C]0.0572[/C][C]0.477266[/C][/ROW]
[ROW][C]30[/C][C]0.064423[/C][C]0.5798[/C][C]0.281828[/C][/ROW]
[ROW][C]31[/C][C]-0.117595[/C][C]-1.0584[/C][C]0.146521[/C][/ROW]
[ROW][C]32[/C][C]-0.084635[/C][C]-0.7617[/C][C]0.22422[/C][/ROW]
[ROW][C]33[/C][C]-0.072939[/C][C]-0.6565[/C][C]0.256696[/C][/ROW]
[ROW][C]34[/C][C]0.015889[/C][C]0.143[/C][C]0.443323[/C][/ROW]
[ROW][C]35[/C][C]0.014581[/C][C]0.1312[/C][C]0.447959[/C][/ROW]
[ROW][C]36[/C][C]-0.051901[/C][C]-0.4671[/C][C]0.320838[/C][/ROW]
[ROW][C]37[/C][C]0.004551[/C][C]0.041[/C][C]0.483714[/C][/ROW]
[ROW][C]38[/C][C]-0.132855[/C][C]-1.1957[/C][C]0.117652[/C][/ROW]
[ROW][C]39[/C][C]-0.013711[/C][C]-0.1234[/C][C]0.451047[/C][/ROW]
[ROW][C]40[/C][C]0.029923[/C][C]0.2693[/C][C]0.394189[/C][/ROW]
[ROW][C]41[/C][C]-0.118234[/C][C]-1.0641[/C][C]0.145221[/C][/ROW]
[ROW][C]42[/C][C]0.004058[/C][C]0.0365[/C][C]0.485476[/C][/ROW]
[ROW][C]43[/C][C]0.062776[/C][C]0.565[/C][C]0.286823[/C][/ROW]
[ROW][C]44[/C][C]-0.046469[/C][C]-0.4182[/C][C]0.338445[/C][/ROW]
[ROW][C]45[/C][C]0.028101[/C][C]0.2529[/C][C]0.400491[/C][/ROW]
[ROW][C]46[/C][C]0.080018[/C][C]0.7202[/C][C]0.236749[/C][/ROW]
[ROW][C]47[/C][C]0.0488[/C][C]0.4392[/C][C]0.330842[/C][/ROW]
[ROW][C]48[/C][C]-0.184525[/C][C]-1.6607[/C][C]0.050317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106460&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106460&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
1-0.370752-3.33680.000641
20.0357250.32150.37432
3-0.102826-0.92540.178746
4-0.241293-2.17160.016404
5-0.092028-0.82820.204981
6-0.023313-0.20980.41717
7-0.112041-1.00840.158141
80.0683290.6150.270153
90.2014031.81260.036798
10-0.002032-0.01830.492727
11-0.117613-1.05850.146483
12-0.154051-1.38650.084706
13-0.2995-2.69550.004272
14-0.227169-2.04450.022075
150.0645720.58120.281376
16-0.046482-0.41830.338405
17-0.165075-1.48570.070623
18-0.013857-0.12470.45053
19-0.073179-0.65860.256006
20-0.196306-1.76670.040519
210.1998821.79890.037876
22-0.237506-2.13760.017784
230.0394380.35490.361778
24-0.043488-0.39140.348266
25-0.084161-0.75740.22549
260.0054210.04880.480603
270.109450.9850.163767
28-0.043284-0.38960.348945
290.0063550.05720.477266
300.0644230.57980.281828
31-0.117595-1.05840.146521
32-0.084635-0.76170.22422
33-0.072939-0.65650.256696
340.0158890.1430.443323
350.0145810.13120.447959
36-0.051901-0.46710.320838
370.0045510.0410.483714
38-0.132855-1.19570.117652
39-0.013711-0.12340.451047
400.0299230.26930.394189
41-0.118234-1.06410.145221
420.0040580.03650.485476
430.0627760.5650.286823
44-0.046469-0.41820.338445
450.0281010.25290.400491
460.0800180.72020.236749
470.04880.43920.330842
48-0.184525-1.66070.050317



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