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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 computationMon, 20 Dec 2010 14:26:33 +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/20/t1292855062rsj81inkr4t5qqh.htm/, Retrieved Fri, 03 May 2024 16:42:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112960, Retrieved Fri, 03 May 2024 16:42:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
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] [Test] [2010-12-05 10:22:51] [74be16979710d4c4e7c6647856088456]
-   P       [(Partial) Autocorrelation Function] [W9 - Blog 2] [2010-12-06 15:12:52] [1aa8d85d6b335d32b1f6be940e33a166]
-   PD          [(Partial) Autocorrelation Function] [ACF d=1D=0 Whisky] [2010-12-20 14:26:33] [47bfda5353cd53c1cf7ea7aa9038654a] [Current]
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Dataseries X:
16.46
16.49
16.59
16.58
16.60
16.55
16.57
16.51
16.50
16.49
16.44
16.26
16.33
16.72
16.75
16.74
16.84
16.79
16.66
16.69
16.84
16.86
16.76
16.72
16.29
16.29
16.46
16.54
16.70
16.82
16.88
16.89
16.92
16.88
16.91
16.80
16.78
17.03
17.18
17.12
17.11
17.14
17.17
17.21
17.22
17.19
17.15
17.10
17.21
17.33
17.30
17.33
17.35
17.43
17.46
17.50
17.54
17.56
17.44
17.41
17.72
17.79
17.83
17.76
17.95
17.91
17.96
17.98
17.89
17.88
17.91
17.51
17.63




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112960&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112960&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112960&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0614150.52110.30194
2-0.175811-1.49180.070059
3-0.038535-0.3270.372314
4-0.09901-0.84010.201809
5-0.163834-1.39020.084379
60.0442310.37530.354266
70.022250.18880.425391
8-0.028301-0.24010.405452
9-0.093713-0.79520.214561
10-0.065009-0.55160.291458
11-0.064655-0.54860.292482
120.1342211.13890.12926
130.0725820.61590.269958
14-0.044408-0.37680.353709
150.0187340.1590.437071
160.0241110.20460.419236
170.0532920.45220.326242
18-0.015832-0.13430.446755
19-0.052282-0.44360.329323
20-0.117387-0.99610.161277
21-0.007236-0.06140.475606
22-0.036739-0.31170.378069
230.0799910.67870.249737
240.1286031.09120.139404
250.0041520.03520.485998
26-0.026148-0.22190.412522
27-0.031356-0.26610.395475
280.0376920.31980.375014
29-0.017637-0.14970.440726
30-0.037768-0.32050.374769
31-0.072086-0.61170.271341
320.0266220.22590.41096
33-0.059311-0.50330.308156
34-0.001927-0.01630.493501
350.1351781.1470.127585
360.0258690.21950.413439
37-0.085498-0.72550.235256
38-0.042779-0.3630.358837
390.0003940.00330.498672
400.0053170.04510.482069
410.0278710.23650.406862
42-0.136215-1.15580.125788
43-0.086169-0.73120.233525
440.0557990.47350.318654
45-0.100678-0.85430.197892
46-0.010325-0.08760.465215
470.3129042.65510.004877
480.0212440.18030.428727

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.061415 & 0.5211 & 0.30194 \tabularnewline
2 & -0.175811 & -1.4918 & 0.070059 \tabularnewline
3 & -0.038535 & -0.327 & 0.372314 \tabularnewline
4 & -0.09901 & -0.8401 & 0.201809 \tabularnewline
5 & -0.163834 & -1.3902 & 0.084379 \tabularnewline
6 & 0.044231 & 0.3753 & 0.354266 \tabularnewline
7 & 0.02225 & 0.1888 & 0.425391 \tabularnewline
8 & -0.028301 & -0.2401 & 0.405452 \tabularnewline
9 & -0.093713 & -0.7952 & 0.214561 \tabularnewline
10 & -0.065009 & -0.5516 & 0.291458 \tabularnewline
11 & -0.064655 & -0.5486 & 0.292482 \tabularnewline
12 & 0.134221 & 1.1389 & 0.12926 \tabularnewline
13 & 0.072582 & 0.6159 & 0.269958 \tabularnewline
14 & -0.044408 & -0.3768 & 0.353709 \tabularnewline
15 & 0.018734 & 0.159 & 0.437071 \tabularnewline
16 & 0.024111 & 0.2046 & 0.419236 \tabularnewline
17 & 0.053292 & 0.4522 & 0.326242 \tabularnewline
18 & -0.015832 & -0.1343 & 0.446755 \tabularnewline
19 & -0.052282 & -0.4436 & 0.329323 \tabularnewline
20 & -0.117387 & -0.9961 & 0.161277 \tabularnewline
21 & -0.007236 & -0.0614 & 0.475606 \tabularnewline
22 & -0.036739 & -0.3117 & 0.378069 \tabularnewline
23 & 0.079991 & 0.6787 & 0.249737 \tabularnewline
24 & 0.128603 & 1.0912 & 0.139404 \tabularnewline
25 & 0.004152 & 0.0352 & 0.485998 \tabularnewline
26 & -0.026148 & -0.2219 & 0.412522 \tabularnewline
27 & -0.031356 & -0.2661 & 0.395475 \tabularnewline
28 & 0.037692 & 0.3198 & 0.375014 \tabularnewline
29 & -0.017637 & -0.1497 & 0.440726 \tabularnewline
30 & -0.037768 & -0.3205 & 0.374769 \tabularnewline
31 & -0.072086 & -0.6117 & 0.271341 \tabularnewline
32 & 0.026622 & 0.2259 & 0.41096 \tabularnewline
33 & -0.059311 & -0.5033 & 0.308156 \tabularnewline
34 & -0.001927 & -0.0163 & 0.493501 \tabularnewline
35 & 0.135178 & 1.147 & 0.127585 \tabularnewline
36 & 0.025869 & 0.2195 & 0.413439 \tabularnewline
37 & -0.085498 & -0.7255 & 0.235256 \tabularnewline
38 & -0.042779 & -0.363 & 0.358837 \tabularnewline
39 & 0.000394 & 0.0033 & 0.498672 \tabularnewline
40 & 0.005317 & 0.0451 & 0.482069 \tabularnewline
41 & 0.027871 & 0.2365 & 0.406862 \tabularnewline
42 & -0.136215 & -1.1558 & 0.125788 \tabularnewline
43 & -0.086169 & -0.7312 & 0.233525 \tabularnewline
44 & 0.055799 & 0.4735 & 0.318654 \tabularnewline
45 & -0.100678 & -0.8543 & 0.197892 \tabularnewline
46 & -0.010325 & -0.0876 & 0.465215 \tabularnewline
47 & 0.312904 & 2.6551 & 0.004877 \tabularnewline
48 & 0.021244 & 0.1803 & 0.428727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112960&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]0.061415[/C][C]0.5211[/C][C]0.30194[/C][/ROW]
[ROW][C]2[/C][C]-0.175811[/C][C]-1.4918[/C][C]0.070059[/C][/ROW]
[ROW][C]3[/C][C]-0.038535[/C][C]-0.327[/C][C]0.372314[/C][/ROW]
[ROW][C]4[/C][C]-0.09901[/C][C]-0.8401[/C][C]0.201809[/C][/ROW]
[ROW][C]5[/C][C]-0.163834[/C][C]-1.3902[/C][C]0.084379[/C][/ROW]
[ROW][C]6[/C][C]0.044231[/C][C]0.3753[/C][C]0.354266[/C][/ROW]
[ROW][C]7[/C][C]0.02225[/C][C]0.1888[/C][C]0.425391[/C][/ROW]
[ROW][C]8[/C][C]-0.028301[/C][C]-0.2401[/C][C]0.405452[/C][/ROW]
[ROW][C]9[/C][C]-0.093713[/C][C]-0.7952[/C][C]0.214561[/C][/ROW]
[ROW][C]10[/C][C]-0.065009[/C][C]-0.5516[/C][C]0.291458[/C][/ROW]
[ROW][C]11[/C][C]-0.064655[/C][C]-0.5486[/C][C]0.292482[/C][/ROW]
[ROW][C]12[/C][C]0.134221[/C][C]1.1389[/C][C]0.12926[/C][/ROW]
[ROW][C]13[/C][C]0.072582[/C][C]0.6159[/C][C]0.269958[/C][/ROW]
[ROW][C]14[/C][C]-0.044408[/C][C]-0.3768[/C][C]0.353709[/C][/ROW]
[ROW][C]15[/C][C]0.018734[/C][C]0.159[/C][C]0.437071[/C][/ROW]
[ROW][C]16[/C][C]0.024111[/C][C]0.2046[/C][C]0.419236[/C][/ROW]
[ROW][C]17[/C][C]0.053292[/C][C]0.4522[/C][C]0.326242[/C][/ROW]
[ROW][C]18[/C][C]-0.015832[/C][C]-0.1343[/C][C]0.446755[/C][/ROW]
[ROW][C]19[/C][C]-0.052282[/C][C]-0.4436[/C][C]0.329323[/C][/ROW]
[ROW][C]20[/C][C]-0.117387[/C][C]-0.9961[/C][C]0.161277[/C][/ROW]
[ROW][C]21[/C][C]-0.007236[/C][C]-0.0614[/C][C]0.475606[/C][/ROW]
[ROW][C]22[/C][C]-0.036739[/C][C]-0.3117[/C][C]0.378069[/C][/ROW]
[ROW][C]23[/C][C]0.079991[/C][C]0.6787[/C][C]0.249737[/C][/ROW]
[ROW][C]24[/C][C]0.128603[/C][C]1.0912[/C][C]0.139404[/C][/ROW]
[ROW][C]25[/C][C]0.004152[/C][C]0.0352[/C][C]0.485998[/C][/ROW]
[ROW][C]26[/C][C]-0.026148[/C][C]-0.2219[/C][C]0.412522[/C][/ROW]
[ROW][C]27[/C][C]-0.031356[/C][C]-0.2661[/C][C]0.395475[/C][/ROW]
[ROW][C]28[/C][C]0.037692[/C][C]0.3198[/C][C]0.375014[/C][/ROW]
[ROW][C]29[/C][C]-0.017637[/C][C]-0.1497[/C][C]0.440726[/C][/ROW]
[ROW][C]30[/C][C]-0.037768[/C][C]-0.3205[/C][C]0.374769[/C][/ROW]
[ROW][C]31[/C][C]-0.072086[/C][C]-0.6117[/C][C]0.271341[/C][/ROW]
[ROW][C]32[/C][C]0.026622[/C][C]0.2259[/C][C]0.41096[/C][/ROW]
[ROW][C]33[/C][C]-0.059311[/C][C]-0.5033[/C][C]0.308156[/C][/ROW]
[ROW][C]34[/C][C]-0.001927[/C][C]-0.0163[/C][C]0.493501[/C][/ROW]
[ROW][C]35[/C][C]0.135178[/C][C]1.147[/C][C]0.127585[/C][/ROW]
[ROW][C]36[/C][C]0.025869[/C][C]0.2195[/C][C]0.413439[/C][/ROW]
[ROW][C]37[/C][C]-0.085498[/C][C]-0.7255[/C][C]0.235256[/C][/ROW]
[ROW][C]38[/C][C]-0.042779[/C][C]-0.363[/C][C]0.358837[/C][/ROW]
[ROW][C]39[/C][C]0.000394[/C][C]0.0033[/C][C]0.498672[/C][/ROW]
[ROW][C]40[/C][C]0.005317[/C][C]0.0451[/C][C]0.482069[/C][/ROW]
[ROW][C]41[/C][C]0.027871[/C][C]0.2365[/C][C]0.406862[/C][/ROW]
[ROW][C]42[/C][C]-0.136215[/C][C]-1.1558[/C][C]0.125788[/C][/ROW]
[ROW][C]43[/C][C]-0.086169[/C][C]-0.7312[/C][C]0.233525[/C][/ROW]
[ROW][C]44[/C][C]0.055799[/C][C]0.4735[/C][C]0.318654[/C][/ROW]
[ROW][C]45[/C][C]-0.100678[/C][C]-0.8543[/C][C]0.197892[/C][/ROW]
[ROW][C]46[/C][C]-0.010325[/C][C]-0.0876[/C][C]0.465215[/C][/ROW]
[ROW][C]47[/C][C]0.312904[/C][C]2.6551[/C][C]0.004877[/C][/ROW]
[ROW][C]48[/C][C]0.021244[/C][C]0.1803[/C][C]0.428727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112960&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112960&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
10.0614150.52110.30194
2-0.175811-1.49180.070059
3-0.038535-0.3270.372314
4-0.09901-0.84010.201809
5-0.163834-1.39020.084379
60.0442310.37530.354266
70.022250.18880.425391
8-0.028301-0.24010.405452
9-0.093713-0.79520.214561
10-0.065009-0.55160.291458
11-0.064655-0.54860.292482
120.1342211.13890.12926
130.0725820.61590.269958
14-0.044408-0.37680.353709
150.0187340.1590.437071
160.0241110.20460.419236
170.0532920.45220.326242
18-0.015832-0.13430.446755
19-0.052282-0.44360.329323
20-0.117387-0.99610.161277
21-0.007236-0.06140.475606
22-0.036739-0.31170.378069
230.0799910.67870.249737
240.1286031.09120.139404
250.0041520.03520.485998
26-0.026148-0.22190.412522
27-0.031356-0.26610.395475
280.0376920.31980.375014
29-0.017637-0.14970.440726
30-0.037768-0.32050.374769
31-0.072086-0.61170.271341
320.0266220.22590.41096
33-0.059311-0.50330.308156
34-0.001927-0.01630.493501
350.1351781.1470.127585
360.0258690.21950.413439
37-0.085498-0.72550.235256
38-0.042779-0.3630.358837
390.0003940.00330.498672
400.0053170.04510.482069
410.0278710.23650.406862
42-0.136215-1.15580.125788
43-0.086169-0.73120.233525
440.0557990.47350.318654
45-0.100678-0.85430.197892
46-0.010325-0.08760.465215
470.3129042.65510.004877
480.0212440.18030.428727







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0614150.52110.30194
2-0.180263-1.52960.065251
3-0.015273-0.12960.448625
4-0.131671-1.11730.133797
5-0.166778-1.41520.080667
60.0207420.1760.430393
7-0.056519-0.47960.316491
8-0.042073-0.3570.361066
9-0.141848-1.20360.116339
10-0.102592-0.87050.193454
11-0.115554-0.98050.165058
120.0856080.72640.234971
13-0.020191-0.17130.432225
14-0.078175-0.66330.254616
15-0.000904-0.00770.496952
16-0.008787-0.07460.470387
170.1053110.89360.187259
18-0.047783-0.40550.343174
19-0.058372-0.49530.310947
20-0.142333-1.20770.115551
210.0158280.13430.446768
22-0.06492-0.55090.291715
230.0699750.59380.277266
240.0546870.4640.322012
25-0.038838-0.32960.371347
260.0531280.45080.326741
27-0.041547-0.35250.362731
280.1027860.87220.193008
29-0.079335-0.67320.251495
30-0.039031-0.33120.370732
31-0.112327-0.95310.171858
320.0766370.65030.258789
33-0.074206-0.62970.265456
340.0063650.0540.478537
350.117210.99460.16164
36-0.064655-0.54860.292482
370.0186860.15860.437232
38-0.116619-0.98950.162856
390.031420.26660.395265
40-0.092089-0.78140.218563
410.0057410.04870.48064
42-0.252282-2.14070.017843
43-0.047414-0.40230.344321
440.0154570.13120.448009
45-0.229735-1.94940.027573
460.0473490.40180.344522
470.0807780.68540.247639
48-0.009654-0.08190.467469

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.061415 & 0.5211 & 0.30194 \tabularnewline
2 & -0.180263 & -1.5296 & 0.065251 \tabularnewline
3 & -0.015273 & -0.1296 & 0.448625 \tabularnewline
4 & -0.131671 & -1.1173 & 0.133797 \tabularnewline
5 & -0.166778 & -1.4152 & 0.080667 \tabularnewline
6 & 0.020742 & 0.176 & 0.430393 \tabularnewline
7 & -0.056519 & -0.4796 & 0.316491 \tabularnewline
8 & -0.042073 & -0.357 & 0.361066 \tabularnewline
9 & -0.141848 & -1.2036 & 0.116339 \tabularnewline
10 & -0.102592 & -0.8705 & 0.193454 \tabularnewline
11 & -0.115554 & -0.9805 & 0.165058 \tabularnewline
12 & 0.085608 & 0.7264 & 0.234971 \tabularnewline
13 & -0.020191 & -0.1713 & 0.432225 \tabularnewline
14 & -0.078175 & -0.6633 & 0.254616 \tabularnewline
15 & -0.000904 & -0.0077 & 0.496952 \tabularnewline
16 & -0.008787 & -0.0746 & 0.470387 \tabularnewline
17 & 0.105311 & 0.8936 & 0.187259 \tabularnewline
18 & -0.047783 & -0.4055 & 0.343174 \tabularnewline
19 & -0.058372 & -0.4953 & 0.310947 \tabularnewline
20 & -0.142333 & -1.2077 & 0.115551 \tabularnewline
21 & 0.015828 & 0.1343 & 0.446768 \tabularnewline
22 & -0.06492 & -0.5509 & 0.291715 \tabularnewline
23 & 0.069975 & 0.5938 & 0.277266 \tabularnewline
24 & 0.054687 & 0.464 & 0.322012 \tabularnewline
25 & -0.038838 & -0.3296 & 0.371347 \tabularnewline
26 & 0.053128 & 0.4508 & 0.326741 \tabularnewline
27 & -0.041547 & -0.3525 & 0.362731 \tabularnewline
28 & 0.102786 & 0.8722 & 0.193008 \tabularnewline
29 & -0.079335 & -0.6732 & 0.251495 \tabularnewline
30 & -0.039031 & -0.3312 & 0.370732 \tabularnewline
31 & -0.112327 & -0.9531 & 0.171858 \tabularnewline
32 & 0.076637 & 0.6503 & 0.258789 \tabularnewline
33 & -0.074206 & -0.6297 & 0.265456 \tabularnewline
34 & 0.006365 & 0.054 & 0.478537 \tabularnewline
35 & 0.11721 & 0.9946 & 0.16164 \tabularnewline
36 & -0.064655 & -0.5486 & 0.292482 \tabularnewline
37 & 0.018686 & 0.1586 & 0.437232 \tabularnewline
38 & -0.116619 & -0.9895 & 0.162856 \tabularnewline
39 & 0.03142 & 0.2666 & 0.395265 \tabularnewline
40 & -0.092089 & -0.7814 & 0.218563 \tabularnewline
41 & 0.005741 & 0.0487 & 0.48064 \tabularnewline
42 & -0.252282 & -2.1407 & 0.017843 \tabularnewline
43 & -0.047414 & -0.4023 & 0.344321 \tabularnewline
44 & 0.015457 & 0.1312 & 0.448009 \tabularnewline
45 & -0.229735 & -1.9494 & 0.027573 \tabularnewline
46 & 0.047349 & 0.4018 & 0.344522 \tabularnewline
47 & 0.080778 & 0.6854 & 0.247639 \tabularnewline
48 & -0.009654 & -0.0819 & 0.467469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112960&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]0.061415[/C][C]0.5211[/C][C]0.30194[/C][/ROW]
[ROW][C]2[/C][C]-0.180263[/C][C]-1.5296[/C][C]0.065251[/C][/ROW]
[ROW][C]3[/C][C]-0.015273[/C][C]-0.1296[/C][C]0.448625[/C][/ROW]
[ROW][C]4[/C][C]-0.131671[/C][C]-1.1173[/C][C]0.133797[/C][/ROW]
[ROW][C]5[/C][C]-0.166778[/C][C]-1.4152[/C][C]0.080667[/C][/ROW]
[ROW][C]6[/C][C]0.020742[/C][C]0.176[/C][C]0.430393[/C][/ROW]
[ROW][C]7[/C][C]-0.056519[/C][C]-0.4796[/C][C]0.316491[/C][/ROW]
[ROW][C]8[/C][C]-0.042073[/C][C]-0.357[/C][C]0.361066[/C][/ROW]
[ROW][C]9[/C][C]-0.141848[/C][C]-1.2036[/C][C]0.116339[/C][/ROW]
[ROW][C]10[/C][C]-0.102592[/C][C]-0.8705[/C][C]0.193454[/C][/ROW]
[ROW][C]11[/C][C]-0.115554[/C][C]-0.9805[/C][C]0.165058[/C][/ROW]
[ROW][C]12[/C][C]0.085608[/C][C]0.7264[/C][C]0.234971[/C][/ROW]
[ROW][C]13[/C][C]-0.020191[/C][C]-0.1713[/C][C]0.432225[/C][/ROW]
[ROW][C]14[/C][C]-0.078175[/C][C]-0.6633[/C][C]0.254616[/C][/ROW]
[ROW][C]15[/C][C]-0.000904[/C][C]-0.0077[/C][C]0.496952[/C][/ROW]
[ROW][C]16[/C][C]-0.008787[/C][C]-0.0746[/C][C]0.470387[/C][/ROW]
[ROW][C]17[/C][C]0.105311[/C][C]0.8936[/C][C]0.187259[/C][/ROW]
[ROW][C]18[/C][C]-0.047783[/C][C]-0.4055[/C][C]0.343174[/C][/ROW]
[ROW][C]19[/C][C]-0.058372[/C][C]-0.4953[/C][C]0.310947[/C][/ROW]
[ROW][C]20[/C][C]-0.142333[/C][C]-1.2077[/C][C]0.115551[/C][/ROW]
[ROW][C]21[/C][C]0.015828[/C][C]0.1343[/C][C]0.446768[/C][/ROW]
[ROW][C]22[/C][C]-0.06492[/C][C]-0.5509[/C][C]0.291715[/C][/ROW]
[ROW][C]23[/C][C]0.069975[/C][C]0.5938[/C][C]0.277266[/C][/ROW]
[ROW][C]24[/C][C]0.054687[/C][C]0.464[/C][C]0.322012[/C][/ROW]
[ROW][C]25[/C][C]-0.038838[/C][C]-0.3296[/C][C]0.371347[/C][/ROW]
[ROW][C]26[/C][C]0.053128[/C][C]0.4508[/C][C]0.326741[/C][/ROW]
[ROW][C]27[/C][C]-0.041547[/C][C]-0.3525[/C][C]0.362731[/C][/ROW]
[ROW][C]28[/C][C]0.102786[/C][C]0.8722[/C][C]0.193008[/C][/ROW]
[ROW][C]29[/C][C]-0.079335[/C][C]-0.6732[/C][C]0.251495[/C][/ROW]
[ROW][C]30[/C][C]-0.039031[/C][C]-0.3312[/C][C]0.370732[/C][/ROW]
[ROW][C]31[/C][C]-0.112327[/C][C]-0.9531[/C][C]0.171858[/C][/ROW]
[ROW][C]32[/C][C]0.076637[/C][C]0.6503[/C][C]0.258789[/C][/ROW]
[ROW][C]33[/C][C]-0.074206[/C][C]-0.6297[/C][C]0.265456[/C][/ROW]
[ROW][C]34[/C][C]0.006365[/C][C]0.054[/C][C]0.478537[/C][/ROW]
[ROW][C]35[/C][C]0.11721[/C][C]0.9946[/C][C]0.16164[/C][/ROW]
[ROW][C]36[/C][C]-0.064655[/C][C]-0.5486[/C][C]0.292482[/C][/ROW]
[ROW][C]37[/C][C]0.018686[/C][C]0.1586[/C][C]0.437232[/C][/ROW]
[ROW][C]38[/C][C]-0.116619[/C][C]-0.9895[/C][C]0.162856[/C][/ROW]
[ROW][C]39[/C][C]0.03142[/C][C]0.2666[/C][C]0.395265[/C][/ROW]
[ROW][C]40[/C][C]-0.092089[/C][C]-0.7814[/C][C]0.218563[/C][/ROW]
[ROW][C]41[/C][C]0.005741[/C][C]0.0487[/C][C]0.48064[/C][/ROW]
[ROW][C]42[/C][C]-0.252282[/C][C]-2.1407[/C][C]0.017843[/C][/ROW]
[ROW][C]43[/C][C]-0.047414[/C][C]-0.4023[/C][C]0.344321[/C][/ROW]
[ROW][C]44[/C][C]0.015457[/C][C]0.1312[/C][C]0.448009[/C][/ROW]
[ROW][C]45[/C][C]-0.229735[/C][C]-1.9494[/C][C]0.027573[/C][/ROW]
[ROW][C]46[/C][C]0.047349[/C][C]0.4018[/C][C]0.344522[/C][/ROW]
[ROW][C]47[/C][C]0.080778[/C][C]0.6854[/C][C]0.247639[/C][/ROW]
[ROW][C]48[/C][C]-0.009654[/C][C]-0.0819[/C][C]0.467469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112960&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112960&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
10.0614150.52110.30194
2-0.180263-1.52960.065251
3-0.015273-0.12960.448625
4-0.131671-1.11730.133797
5-0.166778-1.41520.080667
60.0207420.1760.430393
7-0.056519-0.47960.316491
8-0.042073-0.3570.361066
9-0.141848-1.20360.116339
10-0.102592-0.87050.193454
11-0.115554-0.98050.165058
120.0856080.72640.234971
13-0.020191-0.17130.432225
14-0.078175-0.66330.254616
15-0.000904-0.00770.496952
16-0.008787-0.07460.470387
170.1053110.89360.187259
18-0.047783-0.40550.343174
19-0.058372-0.49530.310947
20-0.142333-1.20770.115551
210.0158280.13430.446768
22-0.06492-0.55090.291715
230.0699750.59380.277266
240.0546870.4640.322012
25-0.038838-0.32960.371347
260.0531280.45080.326741
27-0.041547-0.35250.362731
280.1027860.87220.193008
29-0.079335-0.67320.251495
30-0.039031-0.33120.370732
31-0.112327-0.95310.171858
320.0766370.65030.258789
33-0.074206-0.62970.265456
340.0063650.0540.478537
350.117210.99460.16164
36-0.064655-0.54860.292482
370.0186860.15860.437232
38-0.116619-0.98950.162856
390.031420.26660.395265
40-0.092089-0.78140.218563
410.0057410.04870.48064
42-0.252282-2.14070.017843
43-0.047414-0.40230.344321
440.0154570.13120.448009
45-0.229735-1.94940.027573
460.0473490.40180.344522
470.0807780.68540.247639
48-0.009654-0.08190.467469



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')