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 computationWed, 22 Dec 2010 09:14:48 +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/22/t1293009170c3xe1fx9i05u3i5.htm/, Retrieved Mon, 06 May 2024 08:15:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114138, Retrieved Mon, 06 May 2024 08:15:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115
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]
-    D    [(Partial) Autocorrelation Function] [Workshop 9, Stati...] [2010-12-03 13:18:27] [d946de7cca328fbcf207448a112523ab]
-    D      [(Partial) Autocorrelation Function] [Autocorrelatie Fu...] [2010-12-19 14:18:56] [d946de7cca328fbcf207448a112523ab]
- R PD        [(Partial) Autocorrelation Function] [Paper ACF] [2010-12-19 14:22:07] [3635fb7041b1998c5a1332cf9de22bce]
-   PD          [(Partial) Autocorrelation Function] [Paper ACF D=1 d=1...] [2010-12-19 21:28:57] [3635fb7041b1998c5a1332cf9de22bce]
-   P             [(Partial) Autocorrelation Function] [ACF d=D=1] [2010-12-22 08:48:35] [8081b8996d5947580de3eb171e82db4f]
-                     [(Partial) Autocorrelation Function] [ACF d=D=1] [2010-12-22 09:14:48] [4d0f7ea43b071af5c75b527ee1ef14c2] [Current]
Feedback Forum

Post a new message
Dataseries X:
21.454
23.899
24.939
23.580
24.562
24.696
23.785
23.812
21.917
19.713
19.282
18.788
21.453
24.482
27.474
27.264
27.349
30.632
29.429
30.084
26.290
24.379
23.335
21.346
21.106
24.514
28.353
30.805
31.348
34.556
33.855
34.787
32.529
29.998
29.257
28.155
30.466
35.704
39.327
39.351
42.234
43.630
43.722
43.121
37.985
37.135
34.646
33.026
35.087
38.846
42.013
43.908
42.868
44.423
44.167
43.636
44.382
42.142
43.452
36.912
42.413
45.344
44.873
47.510
49.554
47.369
45.998
48.140
48.441
44.928
40.454
38.661
37.246
36.843
36.424
37.594
38.144
38.737
34.560
36.080
33.508
35.462
33.374
32.110




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114138&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114138&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114138&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' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.26118-2.20070.015504
20.0902640.76060.224715
30.0300710.25340.400352
40.0845610.71250.239239
5-0.029633-0.24970.401775
6-0.056848-0.4790.316703
70.0216740.18260.427804
80.0369370.31120.378268
9-0.220118-1.85480.033892
100.0991090.83510.20323
110.1171520.98710.163463
12-0.397945-3.35310.000642
130.2186771.84260.034781
14-0.14676-1.23660.110152
150.040.3370.36854
16-0.105838-0.89180.187754
17-0.106186-0.89470.186974
180.1091080.91940.180511
19-0.028402-0.23930.405774
200.0273130.23010.409322
210.158431.3350.093078
22-0.120502-1.01540.156688
230.0926490.78070.218794
240.0488650.41170.340885
25-0.051621-0.4350.332454
260.1891341.59370.057726
27-0.055818-0.47030.31978
280.0713380.60110.274842
290.0262430.22110.412812
30-0.048342-0.40730.342492
310.1001020.84350.200899
32-0.07637-0.64350.260985
33-0.067765-0.5710.284903
34-0.013356-0.11250.455356
35-0.065444-0.55140.291531
36-0.062305-0.5250.300613
370.0180590.15220.439742
38-0.151053-1.27280.103621
390.0951820.8020.212609
40-0.112939-0.95160.172255
410.1004670.84650.200046
42-0.046255-0.38970.348945
43-0.039421-0.33220.370372
44-0.030757-0.25920.398128
45-0.001313-0.01110.495602
460.0505410.42590.335748
47-0.007398-0.06230.475234
48-0.040202-0.33880.367899

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.26118 & -2.2007 & 0.015504 \tabularnewline
2 & 0.090264 & 0.7606 & 0.224715 \tabularnewline
3 & 0.030071 & 0.2534 & 0.400352 \tabularnewline
4 & 0.084561 & 0.7125 & 0.239239 \tabularnewline
5 & -0.029633 & -0.2497 & 0.401775 \tabularnewline
6 & -0.056848 & -0.479 & 0.316703 \tabularnewline
7 & 0.021674 & 0.1826 & 0.427804 \tabularnewline
8 & 0.036937 & 0.3112 & 0.378268 \tabularnewline
9 & -0.220118 & -1.8548 & 0.033892 \tabularnewline
10 & 0.099109 & 0.8351 & 0.20323 \tabularnewline
11 & 0.117152 & 0.9871 & 0.163463 \tabularnewline
12 & -0.397945 & -3.3531 & 0.000642 \tabularnewline
13 & 0.218677 & 1.8426 & 0.034781 \tabularnewline
14 & -0.14676 & -1.2366 & 0.110152 \tabularnewline
15 & 0.04 & 0.337 & 0.36854 \tabularnewline
16 & -0.105838 & -0.8918 & 0.187754 \tabularnewline
17 & -0.106186 & -0.8947 & 0.186974 \tabularnewline
18 & 0.109108 & 0.9194 & 0.180511 \tabularnewline
19 & -0.028402 & -0.2393 & 0.405774 \tabularnewline
20 & 0.027313 & 0.2301 & 0.409322 \tabularnewline
21 & 0.15843 & 1.335 & 0.093078 \tabularnewline
22 & -0.120502 & -1.0154 & 0.156688 \tabularnewline
23 & 0.092649 & 0.7807 & 0.218794 \tabularnewline
24 & 0.048865 & 0.4117 & 0.340885 \tabularnewline
25 & -0.051621 & -0.435 & 0.332454 \tabularnewline
26 & 0.189134 & 1.5937 & 0.057726 \tabularnewline
27 & -0.055818 & -0.4703 & 0.31978 \tabularnewline
28 & 0.071338 & 0.6011 & 0.274842 \tabularnewline
29 & 0.026243 & 0.2211 & 0.412812 \tabularnewline
30 & -0.048342 & -0.4073 & 0.342492 \tabularnewline
31 & 0.100102 & 0.8435 & 0.200899 \tabularnewline
32 & -0.07637 & -0.6435 & 0.260985 \tabularnewline
33 & -0.067765 & -0.571 & 0.284903 \tabularnewline
34 & -0.013356 & -0.1125 & 0.455356 \tabularnewline
35 & -0.065444 & -0.5514 & 0.291531 \tabularnewline
36 & -0.062305 & -0.525 & 0.300613 \tabularnewline
37 & 0.018059 & 0.1522 & 0.439742 \tabularnewline
38 & -0.151053 & -1.2728 & 0.103621 \tabularnewline
39 & 0.095182 & 0.802 & 0.212609 \tabularnewline
40 & -0.112939 & -0.9516 & 0.172255 \tabularnewline
41 & 0.100467 & 0.8465 & 0.200046 \tabularnewline
42 & -0.046255 & -0.3897 & 0.348945 \tabularnewline
43 & -0.039421 & -0.3322 & 0.370372 \tabularnewline
44 & -0.030757 & -0.2592 & 0.398128 \tabularnewline
45 & -0.001313 & -0.0111 & 0.495602 \tabularnewline
46 & 0.050541 & 0.4259 & 0.335748 \tabularnewline
47 & -0.007398 & -0.0623 & 0.475234 \tabularnewline
48 & -0.040202 & -0.3388 & 0.367899 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114138&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]-0.26118[/C][C]-2.2007[/C][C]0.015504[/C][/ROW]
[ROW][C]2[/C][C]0.090264[/C][C]0.7606[/C][C]0.224715[/C][/ROW]
[ROW][C]3[/C][C]0.030071[/C][C]0.2534[/C][C]0.400352[/C][/ROW]
[ROW][C]4[/C][C]0.084561[/C][C]0.7125[/C][C]0.239239[/C][/ROW]
[ROW][C]5[/C][C]-0.029633[/C][C]-0.2497[/C][C]0.401775[/C][/ROW]
[ROW][C]6[/C][C]-0.056848[/C][C]-0.479[/C][C]0.316703[/C][/ROW]
[ROW][C]7[/C][C]0.021674[/C][C]0.1826[/C][C]0.427804[/C][/ROW]
[ROW][C]8[/C][C]0.036937[/C][C]0.3112[/C][C]0.378268[/C][/ROW]
[ROW][C]9[/C][C]-0.220118[/C][C]-1.8548[/C][C]0.033892[/C][/ROW]
[ROW][C]10[/C][C]0.099109[/C][C]0.8351[/C][C]0.20323[/C][/ROW]
[ROW][C]11[/C][C]0.117152[/C][C]0.9871[/C][C]0.163463[/C][/ROW]
[ROW][C]12[/C][C]-0.397945[/C][C]-3.3531[/C][C]0.000642[/C][/ROW]
[ROW][C]13[/C][C]0.218677[/C][C]1.8426[/C][C]0.034781[/C][/ROW]
[ROW][C]14[/C][C]-0.14676[/C][C]-1.2366[/C][C]0.110152[/C][/ROW]
[ROW][C]15[/C][C]0.04[/C][C]0.337[/C][C]0.36854[/C][/ROW]
[ROW][C]16[/C][C]-0.105838[/C][C]-0.8918[/C][C]0.187754[/C][/ROW]
[ROW][C]17[/C][C]-0.106186[/C][C]-0.8947[/C][C]0.186974[/C][/ROW]
[ROW][C]18[/C][C]0.109108[/C][C]0.9194[/C][C]0.180511[/C][/ROW]
[ROW][C]19[/C][C]-0.028402[/C][C]-0.2393[/C][C]0.405774[/C][/ROW]
[ROW][C]20[/C][C]0.027313[/C][C]0.2301[/C][C]0.409322[/C][/ROW]
[ROW][C]21[/C][C]0.15843[/C][C]1.335[/C][C]0.093078[/C][/ROW]
[ROW][C]22[/C][C]-0.120502[/C][C]-1.0154[/C][C]0.156688[/C][/ROW]
[ROW][C]23[/C][C]0.092649[/C][C]0.7807[/C][C]0.218794[/C][/ROW]
[ROW][C]24[/C][C]0.048865[/C][C]0.4117[/C][C]0.340885[/C][/ROW]
[ROW][C]25[/C][C]-0.051621[/C][C]-0.435[/C][C]0.332454[/C][/ROW]
[ROW][C]26[/C][C]0.189134[/C][C]1.5937[/C][C]0.057726[/C][/ROW]
[ROW][C]27[/C][C]-0.055818[/C][C]-0.4703[/C][C]0.31978[/C][/ROW]
[ROW][C]28[/C][C]0.071338[/C][C]0.6011[/C][C]0.274842[/C][/ROW]
[ROW][C]29[/C][C]0.026243[/C][C]0.2211[/C][C]0.412812[/C][/ROW]
[ROW][C]30[/C][C]-0.048342[/C][C]-0.4073[/C][C]0.342492[/C][/ROW]
[ROW][C]31[/C][C]0.100102[/C][C]0.8435[/C][C]0.200899[/C][/ROW]
[ROW][C]32[/C][C]-0.07637[/C][C]-0.6435[/C][C]0.260985[/C][/ROW]
[ROW][C]33[/C][C]-0.067765[/C][C]-0.571[/C][C]0.284903[/C][/ROW]
[ROW][C]34[/C][C]-0.013356[/C][C]-0.1125[/C][C]0.455356[/C][/ROW]
[ROW][C]35[/C][C]-0.065444[/C][C]-0.5514[/C][C]0.291531[/C][/ROW]
[ROW][C]36[/C][C]-0.062305[/C][C]-0.525[/C][C]0.300613[/C][/ROW]
[ROW][C]37[/C][C]0.018059[/C][C]0.1522[/C][C]0.439742[/C][/ROW]
[ROW][C]38[/C][C]-0.151053[/C][C]-1.2728[/C][C]0.103621[/C][/ROW]
[ROW][C]39[/C][C]0.095182[/C][C]0.802[/C][C]0.212609[/C][/ROW]
[ROW][C]40[/C][C]-0.112939[/C][C]-0.9516[/C][C]0.172255[/C][/ROW]
[ROW][C]41[/C][C]0.100467[/C][C]0.8465[/C][C]0.200046[/C][/ROW]
[ROW][C]42[/C][C]-0.046255[/C][C]-0.3897[/C][C]0.348945[/C][/ROW]
[ROW][C]43[/C][C]-0.039421[/C][C]-0.3322[/C][C]0.370372[/C][/ROW]
[ROW][C]44[/C][C]-0.030757[/C][C]-0.2592[/C][C]0.398128[/C][/ROW]
[ROW][C]45[/C][C]-0.001313[/C][C]-0.0111[/C][C]0.495602[/C][/ROW]
[ROW][C]46[/C][C]0.050541[/C][C]0.4259[/C][C]0.335748[/C][/ROW]
[ROW][C]47[/C][C]-0.007398[/C][C]-0.0623[/C][C]0.475234[/C][/ROW]
[ROW][C]48[/C][C]-0.040202[/C][C]-0.3388[/C][C]0.367899[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114138&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114138&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
1-0.26118-2.20070.015504
20.0902640.76060.224715
30.0300710.25340.400352
40.0845610.71250.239239
5-0.029633-0.24970.401775
6-0.056848-0.4790.316703
70.0216740.18260.427804
80.0369370.31120.378268
9-0.220118-1.85480.033892
100.0991090.83510.20323
110.1171520.98710.163463
12-0.397945-3.35310.000642
130.2186771.84260.034781
14-0.14676-1.23660.110152
150.040.3370.36854
16-0.105838-0.89180.187754
17-0.106186-0.89470.186974
180.1091080.91940.180511
19-0.028402-0.23930.405774
200.0273130.23010.409322
210.158431.3350.093078
22-0.120502-1.01540.156688
230.0926490.78070.218794
240.0488650.41170.340885
25-0.051621-0.4350.332454
260.1891341.59370.057726
27-0.055818-0.47030.31978
280.0713380.60110.274842
290.0262430.22110.412812
30-0.048342-0.40730.342492
310.1001020.84350.200899
32-0.07637-0.64350.260985
33-0.067765-0.5710.284903
34-0.013356-0.11250.455356
35-0.065444-0.55140.291531
36-0.062305-0.5250.300613
370.0180590.15220.439742
38-0.151053-1.27280.103621
390.0951820.8020.212609
40-0.112939-0.95160.172255
410.1004670.84650.200046
42-0.046255-0.38970.348945
43-0.039421-0.33220.370372
44-0.030757-0.25920.398128
45-0.001313-0.01110.495602
460.0505410.42590.335748
47-0.007398-0.06230.475234
48-0.040202-0.33880.367899







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.26118-2.20070.015504
20.0236630.19940.421266
30.0636430.53630.296725
40.1135280.95660.171008
50.0140720.11860.452975
6-0.084417-0.71130.239611
7-0.027957-0.23560.407223
80.043020.36250.359031
9-0.204594-1.72390.044535
101.6e-051e-040.499946
110.1895761.59740.05731
12-0.374053-3.15180.001188
130.0881280.74260.230093
14-0.056169-0.47330.318729
15-0.083453-0.70320.242119
160.0028450.0240.490471
17-0.190403-1.60440.056536
18-0.007012-0.05910.476525
190.1094110.92190.179847
200.0851080.71710.237823
210.0412640.34770.364549
22-0.014103-0.11880.452871
230.058340.49160.312266
24-0.098338-0.82860.205051
250.0432350.36430.358358
260.1253971.05660.147135
270.0747030.62950.265535
280.050650.42680.335413
29-0.052251-0.44030.330539
30-0.004465-0.03760.485047
310.0486880.41030.341428
320.0100380.08460.466417
33-0.08391-0.7070.240928
34-0.158172-1.33280.093433
350.1014370.85470.19779
36-0.11903-1.0030.159642
370.0471720.39750.346104
38-0.028562-0.24070.405255
39-0.051819-0.43660.33185
400.0093130.07850.468836
410.0376020.31680.376147
42-0.025824-0.21760.414185
430.0264330.22270.412192
44-0.084146-0.7090.240314
45-0.129864-1.09430.138771
460.0299930.25270.400605
470.0142930.12040.452239
48-0.12993-1.09480.138651

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.26118 & -2.2007 & 0.015504 \tabularnewline
2 & 0.023663 & 0.1994 & 0.421266 \tabularnewline
3 & 0.063643 & 0.5363 & 0.296725 \tabularnewline
4 & 0.113528 & 0.9566 & 0.171008 \tabularnewline
5 & 0.014072 & 0.1186 & 0.452975 \tabularnewline
6 & -0.084417 & -0.7113 & 0.239611 \tabularnewline
7 & -0.027957 & -0.2356 & 0.407223 \tabularnewline
8 & 0.04302 & 0.3625 & 0.359031 \tabularnewline
9 & -0.204594 & -1.7239 & 0.044535 \tabularnewline
10 & 1.6e-05 & 1e-04 & 0.499946 \tabularnewline
11 & 0.189576 & 1.5974 & 0.05731 \tabularnewline
12 & -0.374053 & -3.1518 & 0.001188 \tabularnewline
13 & 0.088128 & 0.7426 & 0.230093 \tabularnewline
14 & -0.056169 & -0.4733 & 0.318729 \tabularnewline
15 & -0.083453 & -0.7032 & 0.242119 \tabularnewline
16 & 0.002845 & 0.024 & 0.490471 \tabularnewline
17 & -0.190403 & -1.6044 & 0.056536 \tabularnewline
18 & -0.007012 & -0.0591 & 0.476525 \tabularnewline
19 & 0.109411 & 0.9219 & 0.179847 \tabularnewline
20 & 0.085108 & 0.7171 & 0.237823 \tabularnewline
21 & 0.041264 & 0.3477 & 0.364549 \tabularnewline
22 & -0.014103 & -0.1188 & 0.452871 \tabularnewline
23 & 0.05834 & 0.4916 & 0.312266 \tabularnewline
24 & -0.098338 & -0.8286 & 0.205051 \tabularnewline
25 & 0.043235 & 0.3643 & 0.358358 \tabularnewline
26 & 0.125397 & 1.0566 & 0.147135 \tabularnewline
27 & 0.074703 & 0.6295 & 0.265535 \tabularnewline
28 & 0.05065 & 0.4268 & 0.335413 \tabularnewline
29 & -0.052251 & -0.4403 & 0.330539 \tabularnewline
30 & -0.004465 & -0.0376 & 0.485047 \tabularnewline
31 & 0.048688 & 0.4103 & 0.341428 \tabularnewline
32 & 0.010038 & 0.0846 & 0.466417 \tabularnewline
33 & -0.08391 & -0.707 & 0.240928 \tabularnewline
34 & -0.158172 & -1.3328 & 0.093433 \tabularnewline
35 & 0.101437 & 0.8547 & 0.19779 \tabularnewline
36 & -0.11903 & -1.003 & 0.159642 \tabularnewline
37 & 0.047172 & 0.3975 & 0.346104 \tabularnewline
38 & -0.028562 & -0.2407 & 0.405255 \tabularnewline
39 & -0.051819 & -0.4366 & 0.33185 \tabularnewline
40 & 0.009313 & 0.0785 & 0.468836 \tabularnewline
41 & 0.037602 & 0.3168 & 0.376147 \tabularnewline
42 & -0.025824 & -0.2176 & 0.414185 \tabularnewline
43 & 0.026433 & 0.2227 & 0.412192 \tabularnewline
44 & -0.084146 & -0.709 & 0.240314 \tabularnewline
45 & -0.129864 & -1.0943 & 0.138771 \tabularnewline
46 & 0.029993 & 0.2527 & 0.400605 \tabularnewline
47 & 0.014293 & 0.1204 & 0.452239 \tabularnewline
48 & -0.12993 & -1.0948 & 0.138651 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114138&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]-0.26118[/C][C]-2.2007[/C][C]0.015504[/C][/ROW]
[ROW][C]2[/C][C]0.023663[/C][C]0.1994[/C][C]0.421266[/C][/ROW]
[ROW][C]3[/C][C]0.063643[/C][C]0.5363[/C][C]0.296725[/C][/ROW]
[ROW][C]4[/C][C]0.113528[/C][C]0.9566[/C][C]0.171008[/C][/ROW]
[ROW][C]5[/C][C]0.014072[/C][C]0.1186[/C][C]0.452975[/C][/ROW]
[ROW][C]6[/C][C]-0.084417[/C][C]-0.7113[/C][C]0.239611[/C][/ROW]
[ROW][C]7[/C][C]-0.027957[/C][C]-0.2356[/C][C]0.407223[/C][/ROW]
[ROW][C]8[/C][C]0.04302[/C][C]0.3625[/C][C]0.359031[/C][/ROW]
[ROW][C]9[/C][C]-0.204594[/C][C]-1.7239[/C][C]0.044535[/C][/ROW]
[ROW][C]10[/C][C]1.6e-05[/C][C]1e-04[/C][C]0.499946[/C][/ROW]
[ROW][C]11[/C][C]0.189576[/C][C]1.5974[/C][C]0.05731[/C][/ROW]
[ROW][C]12[/C][C]-0.374053[/C][C]-3.1518[/C][C]0.001188[/C][/ROW]
[ROW][C]13[/C][C]0.088128[/C][C]0.7426[/C][C]0.230093[/C][/ROW]
[ROW][C]14[/C][C]-0.056169[/C][C]-0.4733[/C][C]0.318729[/C][/ROW]
[ROW][C]15[/C][C]-0.083453[/C][C]-0.7032[/C][C]0.242119[/C][/ROW]
[ROW][C]16[/C][C]0.002845[/C][C]0.024[/C][C]0.490471[/C][/ROW]
[ROW][C]17[/C][C]-0.190403[/C][C]-1.6044[/C][C]0.056536[/C][/ROW]
[ROW][C]18[/C][C]-0.007012[/C][C]-0.0591[/C][C]0.476525[/C][/ROW]
[ROW][C]19[/C][C]0.109411[/C][C]0.9219[/C][C]0.179847[/C][/ROW]
[ROW][C]20[/C][C]0.085108[/C][C]0.7171[/C][C]0.237823[/C][/ROW]
[ROW][C]21[/C][C]0.041264[/C][C]0.3477[/C][C]0.364549[/C][/ROW]
[ROW][C]22[/C][C]-0.014103[/C][C]-0.1188[/C][C]0.452871[/C][/ROW]
[ROW][C]23[/C][C]0.05834[/C][C]0.4916[/C][C]0.312266[/C][/ROW]
[ROW][C]24[/C][C]-0.098338[/C][C]-0.8286[/C][C]0.205051[/C][/ROW]
[ROW][C]25[/C][C]0.043235[/C][C]0.3643[/C][C]0.358358[/C][/ROW]
[ROW][C]26[/C][C]0.125397[/C][C]1.0566[/C][C]0.147135[/C][/ROW]
[ROW][C]27[/C][C]0.074703[/C][C]0.6295[/C][C]0.265535[/C][/ROW]
[ROW][C]28[/C][C]0.05065[/C][C]0.4268[/C][C]0.335413[/C][/ROW]
[ROW][C]29[/C][C]-0.052251[/C][C]-0.4403[/C][C]0.330539[/C][/ROW]
[ROW][C]30[/C][C]-0.004465[/C][C]-0.0376[/C][C]0.485047[/C][/ROW]
[ROW][C]31[/C][C]0.048688[/C][C]0.4103[/C][C]0.341428[/C][/ROW]
[ROW][C]32[/C][C]0.010038[/C][C]0.0846[/C][C]0.466417[/C][/ROW]
[ROW][C]33[/C][C]-0.08391[/C][C]-0.707[/C][C]0.240928[/C][/ROW]
[ROW][C]34[/C][C]-0.158172[/C][C]-1.3328[/C][C]0.093433[/C][/ROW]
[ROW][C]35[/C][C]0.101437[/C][C]0.8547[/C][C]0.19779[/C][/ROW]
[ROW][C]36[/C][C]-0.11903[/C][C]-1.003[/C][C]0.159642[/C][/ROW]
[ROW][C]37[/C][C]0.047172[/C][C]0.3975[/C][C]0.346104[/C][/ROW]
[ROW][C]38[/C][C]-0.028562[/C][C]-0.2407[/C][C]0.405255[/C][/ROW]
[ROW][C]39[/C][C]-0.051819[/C][C]-0.4366[/C][C]0.33185[/C][/ROW]
[ROW][C]40[/C][C]0.009313[/C][C]0.0785[/C][C]0.468836[/C][/ROW]
[ROW][C]41[/C][C]0.037602[/C][C]0.3168[/C][C]0.376147[/C][/ROW]
[ROW][C]42[/C][C]-0.025824[/C][C]-0.2176[/C][C]0.414185[/C][/ROW]
[ROW][C]43[/C][C]0.026433[/C][C]0.2227[/C][C]0.412192[/C][/ROW]
[ROW][C]44[/C][C]-0.084146[/C][C]-0.709[/C][C]0.240314[/C][/ROW]
[ROW][C]45[/C][C]-0.129864[/C][C]-1.0943[/C][C]0.138771[/C][/ROW]
[ROW][C]46[/C][C]0.029993[/C][C]0.2527[/C][C]0.400605[/C][/ROW]
[ROW][C]47[/C][C]0.014293[/C][C]0.1204[/C][C]0.452239[/C][/ROW]
[ROW][C]48[/C][C]-0.12993[/C][C]-1.0948[/C][C]0.138651[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114138&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114138&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
1-0.26118-2.20070.015504
20.0236630.19940.421266
30.0636430.53630.296725
40.1135280.95660.171008
50.0140720.11860.452975
6-0.084417-0.71130.239611
7-0.027957-0.23560.407223
80.043020.36250.359031
9-0.204594-1.72390.044535
101.6e-051e-040.499946
110.1895761.59740.05731
12-0.374053-3.15180.001188
130.0881280.74260.230093
14-0.056169-0.47330.318729
15-0.083453-0.70320.242119
160.0028450.0240.490471
17-0.190403-1.60440.056536
18-0.007012-0.05910.476525
190.1094110.92190.179847
200.0851080.71710.237823
210.0412640.34770.364549
22-0.014103-0.11880.452871
230.058340.49160.312266
24-0.098338-0.82860.205051
250.0432350.36430.358358
260.1253971.05660.147135
270.0747030.62950.265535
280.050650.42680.335413
29-0.052251-0.44030.330539
30-0.004465-0.03760.485047
310.0486880.41030.341428
320.0100380.08460.466417
33-0.08391-0.7070.240928
34-0.158172-1.33280.093433
350.1014370.85470.19779
36-0.11903-1.0030.159642
370.0471720.39750.346104
38-0.028562-0.24070.405255
39-0.051819-0.43660.33185
400.0093130.07850.468836
410.0376020.31680.376147
42-0.025824-0.21760.414185
430.0264330.22270.412192
44-0.084146-0.7090.240314
45-0.129864-1.09430.138771
460.0299930.25270.400605
470.0142930.12040.452239
48-0.12993-1.09480.138651



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')