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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, 03 Dec 2009 09:37:35 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/03/t1259858335sky13zpujlaqzm3.htm/, Retrieved Fri, 29 Mar 2024 09:07:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62893, Retrieved Fri, 29 Mar 2024 09:07:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsRW8(5)
Estimated Impact115
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [] [2009-11-26 18:47:15] [023d83ebdf42a2acf423907b4076e8a1]
-   PD    [(Partial) Autocorrelation Function] [Workshop 8: Review] [2009-12-03 16:37:35] [af31b947d6acaef3c71f428c4bb503e9] [Current]
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Dataseries X:
12.610
10.862
52.929
56.902
81.776
87.876
82.103
72.846
60.632
33.521
15.342
7.758
8.668
13.082
38.157
58.263
81.153
88.476
72.329
75.845
61.108
37.665
12.755
2.793
12.935
19.533
33.404
52.074
70.735
69.702
61.656
82.993
53.990
32.283
15.686
2.713
12.842
19.244
48.488
54.464
84.192
84.458
85.793
75.163
68.212
49.233
24.302
5.402
15.058
33.559
70.358
85.934
94.452
129.305
113.882
107.256
94.274
57.842
26.611
14.521




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62893&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]1 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=62893&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62893&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.484636-3.32250.000867
20.0818930.56140.288586
3-0.10111-0.69320.245806
40.1990411.36460.089445
5-0.198363-1.35990.090174
60.0705330.48360.315475
7-0.035409-0.24280.404627
8-0.142746-0.97860.16639
90.1884471.29190.10135
10-0.194835-1.33570.094036
110.2660721.82410.037249
12-0.206381-1.41490.081848
130.036190.24810.402567
140.0015370.01050.49582
150.1596151.09430.139708
16-0.137475-0.94250.175383
170.0008560.00590.497672
18-0.008167-0.0560.477794
190.0452830.31040.378798
20-0.005789-0.03970.484255
21-0.018294-0.12540.450364
220.0022390.01540.493908
230.0411480.28210.389554
24-0.195276-1.33870.093547
250.2024291.38780.085873
26-0.067898-0.46550.321867
27-0.083981-0.57570.283767
28-0.062051-0.42540.336244
290.207751.42430.080489
30-0.052397-0.35920.360522
31-0.023505-0.16110.436335
320.0553950.37980.352914
33-0.110686-0.75880.225874
340.1351650.92660.179423
35-0.080081-0.5490.292799
360.0569250.39030.349054
37-0.101409-0.69520.245169
380.1321010.90560.184873
39-0.134583-0.92270.180451
400.1035930.71020.240544
41-0.044168-0.30280.38169
42-0.019001-0.13030.448456
430.0220640.15130.440208
440.0165950.11380.454952
45-0.022284-0.15280.439617
460.0056530.03880.484625
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.484636 & -3.3225 & 0.000867 \tabularnewline
2 & 0.081893 & 0.5614 & 0.288586 \tabularnewline
3 & -0.10111 & -0.6932 & 0.245806 \tabularnewline
4 & 0.199041 & 1.3646 & 0.089445 \tabularnewline
5 & -0.198363 & -1.3599 & 0.090174 \tabularnewline
6 & 0.070533 & 0.4836 & 0.315475 \tabularnewline
7 & -0.035409 & -0.2428 & 0.404627 \tabularnewline
8 & -0.142746 & -0.9786 & 0.16639 \tabularnewline
9 & 0.188447 & 1.2919 & 0.10135 \tabularnewline
10 & -0.194835 & -1.3357 & 0.094036 \tabularnewline
11 & 0.266072 & 1.8241 & 0.037249 \tabularnewline
12 & -0.206381 & -1.4149 & 0.081848 \tabularnewline
13 & 0.03619 & 0.2481 & 0.402567 \tabularnewline
14 & 0.001537 & 0.0105 & 0.49582 \tabularnewline
15 & 0.159615 & 1.0943 & 0.139708 \tabularnewline
16 & -0.137475 & -0.9425 & 0.175383 \tabularnewline
17 & 0.000856 & 0.0059 & 0.497672 \tabularnewline
18 & -0.008167 & -0.056 & 0.477794 \tabularnewline
19 & 0.045283 & 0.3104 & 0.378798 \tabularnewline
20 & -0.005789 & -0.0397 & 0.484255 \tabularnewline
21 & -0.018294 & -0.1254 & 0.450364 \tabularnewline
22 & 0.002239 & 0.0154 & 0.493908 \tabularnewline
23 & 0.041148 & 0.2821 & 0.389554 \tabularnewline
24 & -0.195276 & -1.3387 & 0.093547 \tabularnewline
25 & 0.202429 & 1.3878 & 0.085873 \tabularnewline
26 & -0.067898 & -0.4655 & 0.321867 \tabularnewline
27 & -0.083981 & -0.5757 & 0.283767 \tabularnewline
28 & -0.062051 & -0.4254 & 0.336244 \tabularnewline
29 & 0.20775 & 1.4243 & 0.080489 \tabularnewline
30 & -0.052397 & -0.3592 & 0.360522 \tabularnewline
31 & -0.023505 & -0.1611 & 0.436335 \tabularnewline
32 & 0.055395 & 0.3798 & 0.352914 \tabularnewline
33 & -0.110686 & -0.7588 & 0.225874 \tabularnewline
34 & 0.135165 & 0.9266 & 0.179423 \tabularnewline
35 & -0.080081 & -0.549 & 0.292799 \tabularnewline
36 & 0.056925 & 0.3903 & 0.349054 \tabularnewline
37 & -0.101409 & -0.6952 & 0.245169 \tabularnewline
38 & 0.132101 & 0.9056 & 0.184873 \tabularnewline
39 & -0.134583 & -0.9227 & 0.180451 \tabularnewline
40 & 0.103593 & 0.7102 & 0.240544 \tabularnewline
41 & -0.044168 & -0.3028 & 0.38169 \tabularnewline
42 & -0.019001 & -0.1303 & 0.448456 \tabularnewline
43 & 0.022064 & 0.1513 & 0.440208 \tabularnewline
44 & 0.016595 & 0.1138 & 0.454952 \tabularnewline
45 & -0.022284 & -0.1528 & 0.439617 \tabularnewline
46 & 0.005653 & 0.0388 & 0.484625 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62893&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]-0.484636[/C][C]-3.3225[/C][C]0.000867[/C][/ROW]
[ROW][C]2[/C][C]0.081893[/C][C]0.5614[/C][C]0.288586[/C][/ROW]
[ROW][C]3[/C][C]-0.10111[/C][C]-0.6932[/C][C]0.245806[/C][/ROW]
[ROW][C]4[/C][C]0.199041[/C][C]1.3646[/C][C]0.089445[/C][/ROW]
[ROW][C]5[/C][C]-0.198363[/C][C]-1.3599[/C][C]0.090174[/C][/ROW]
[ROW][C]6[/C][C]0.070533[/C][C]0.4836[/C][C]0.315475[/C][/ROW]
[ROW][C]7[/C][C]-0.035409[/C][C]-0.2428[/C][C]0.404627[/C][/ROW]
[ROW][C]8[/C][C]-0.142746[/C][C]-0.9786[/C][C]0.16639[/C][/ROW]
[ROW][C]9[/C][C]0.188447[/C][C]1.2919[/C][C]0.10135[/C][/ROW]
[ROW][C]10[/C][C]-0.194835[/C][C]-1.3357[/C][C]0.094036[/C][/ROW]
[ROW][C]11[/C][C]0.266072[/C][C]1.8241[/C][C]0.037249[/C][/ROW]
[ROW][C]12[/C][C]-0.206381[/C][C]-1.4149[/C][C]0.081848[/C][/ROW]
[ROW][C]13[/C][C]0.03619[/C][C]0.2481[/C][C]0.402567[/C][/ROW]
[ROW][C]14[/C][C]0.001537[/C][C]0.0105[/C][C]0.49582[/C][/ROW]
[ROW][C]15[/C][C]0.159615[/C][C]1.0943[/C][C]0.139708[/C][/ROW]
[ROW][C]16[/C][C]-0.137475[/C][C]-0.9425[/C][C]0.175383[/C][/ROW]
[ROW][C]17[/C][C]0.000856[/C][C]0.0059[/C][C]0.497672[/C][/ROW]
[ROW][C]18[/C][C]-0.008167[/C][C]-0.056[/C][C]0.477794[/C][/ROW]
[ROW][C]19[/C][C]0.045283[/C][C]0.3104[/C][C]0.378798[/C][/ROW]
[ROW][C]20[/C][C]-0.005789[/C][C]-0.0397[/C][C]0.484255[/C][/ROW]
[ROW][C]21[/C][C]-0.018294[/C][C]-0.1254[/C][C]0.450364[/C][/ROW]
[ROW][C]22[/C][C]0.002239[/C][C]0.0154[/C][C]0.493908[/C][/ROW]
[ROW][C]23[/C][C]0.041148[/C][C]0.2821[/C][C]0.389554[/C][/ROW]
[ROW][C]24[/C][C]-0.195276[/C][C]-1.3387[/C][C]0.093547[/C][/ROW]
[ROW][C]25[/C][C]0.202429[/C][C]1.3878[/C][C]0.085873[/C][/ROW]
[ROW][C]26[/C][C]-0.067898[/C][C]-0.4655[/C][C]0.321867[/C][/ROW]
[ROW][C]27[/C][C]-0.083981[/C][C]-0.5757[/C][C]0.283767[/C][/ROW]
[ROW][C]28[/C][C]-0.062051[/C][C]-0.4254[/C][C]0.336244[/C][/ROW]
[ROW][C]29[/C][C]0.20775[/C][C]1.4243[/C][C]0.080489[/C][/ROW]
[ROW][C]30[/C][C]-0.052397[/C][C]-0.3592[/C][C]0.360522[/C][/ROW]
[ROW][C]31[/C][C]-0.023505[/C][C]-0.1611[/C][C]0.436335[/C][/ROW]
[ROW][C]32[/C][C]0.055395[/C][C]0.3798[/C][C]0.352914[/C][/ROW]
[ROW][C]33[/C][C]-0.110686[/C][C]-0.7588[/C][C]0.225874[/C][/ROW]
[ROW][C]34[/C][C]0.135165[/C][C]0.9266[/C][C]0.179423[/C][/ROW]
[ROW][C]35[/C][C]-0.080081[/C][C]-0.549[/C][C]0.292799[/C][/ROW]
[ROW][C]36[/C][C]0.056925[/C][C]0.3903[/C][C]0.349054[/C][/ROW]
[ROW][C]37[/C][C]-0.101409[/C][C]-0.6952[/C][C]0.245169[/C][/ROW]
[ROW][C]38[/C][C]0.132101[/C][C]0.9056[/C][C]0.184873[/C][/ROW]
[ROW][C]39[/C][C]-0.134583[/C][C]-0.9227[/C][C]0.180451[/C][/ROW]
[ROW][C]40[/C][C]0.103593[/C][C]0.7102[/C][C]0.240544[/C][/ROW]
[ROW][C]41[/C][C]-0.044168[/C][C]-0.3028[/C][C]0.38169[/C][/ROW]
[ROW][C]42[/C][C]-0.019001[/C][C]-0.1303[/C][C]0.448456[/C][/ROW]
[ROW][C]43[/C][C]0.022064[/C][C]0.1513[/C][C]0.440208[/C][/ROW]
[ROW][C]44[/C][C]0.016595[/C][C]0.1138[/C][C]0.454952[/C][/ROW]
[ROW][C]45[/C][C]-0.022284[/C][C]-0.1528[/C][C]0.439617[/C][/ROW]
[ROW][C]46[/C][C]0.005653[/C][C]0.0388[/C][C]0.484625[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62893&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62893&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
1-0.484636-3.32250.000867
20.0818930.56140.288586
3-0.10111-0.69320.245806
40.1990411.36460.089445
5-0.198363-1.35990.090174
60.0705330.48360.315475
7-0.035409-0.24280.404627
8-0.142746-0.97860.16639
90.1884471.29190.10135
10-0.194835-1.33570.094036
110.2660721.82410.037249
12-0.206381-1.41490.081848
130.036190.24810.402567
140.0015370.01050.49582
150.1596151.09430.139708
16-0.137475-0.94250.175383
170.0008560.00590.497672
18-0.008167-0.0560.477794
190.0452830.31040.378798
20-0.005789-0.03970.484255
21-0.018294-0.12540.450364
220.0022390.01540.493908
230.0411480.28210.389554
24-0.195276-1.33870.093547
250.2024291.38780.085873
26-0.067898-0.46550.321867
27-0.083981-0.57570.283767
28-0.062051-0.42540.336244
290.207751.42430.080489
30-0.052397-0.35920.360522
31-0.023505-0.16110.436335
320.0553950.37980.352914
33-0.110686-0.75880.225874
340.1351650.92660.179423
35-0.080081-0.5490.292799
360.0569250.39030.349054
37-0.101409-0.69520.245169
380.1321010.90560.184873
39-0.134583-0.92270.180451
400.1035930.71020.240544
41-0.044168-0.30280.38169
42-0.019001-0.13030.448456
430.0220640.15130.440208
440.0165950.11380.454952
45-0.022284-0.15280.439617
460.0056530.03880.484625
47NANANA
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.484636-3.32250.000867
2-0.19994-1.37070.088487
3-0.204732-1.40360.083509
40.0895290.61380.27116
5-0.074328-0.50960.306369
6-0.064669-0.44340.329773
7-0.05144-0.35270.362961
8-0.307027-2.10490.020338
9-0.007049-0.04830.48083
10-0.216201-1.48220.072481
110.1418780.97270.16785
120.0136490.09360.462924
13-0.198345-1.35980.090193
14-0.018997-0.13020.448467
150.0156870.10750.457408
160.0550450.37740.353799
170.0057520.03940.484357
18-0.139023-0.95310.17271
190.0691250.47390.318883
20-0.055738-0.38210.352046
210.0479960.3290.371792
220.0250420.17170.432212
230.0746890.5120.30551
24-0.227095-1.55690.063103
25-0.035691-0.24470.403882
26-0.053907-0.36960.356683
27-0.135915-0.93180.178105
28-0.171963-1.17890.122182
29-0.030694-0.21040.417122
300.0298590.20470.419344
310.0039040.02680.48938
320.0027470.01880.492527
33-0.125089-0.85760.197741
34-0.10793-0.73990.23151
350.0131780.09030.464199
36-0.05897-0.40430.343921
370.008550.05860.476754
380.1044120.71580.238825
390.0187130.12830.449233
40-0.06892-0.47250.319381
41-0.060357-0.41380.340456
420.0141190.09680.461652
430.0530010.36340.358983
440.0001790.00120.499513
45-0.084209-0.57730.283244
460.0091090.06240.475236
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.484636 & -3.3225 & 0.000867 \tabularnewline
2 & -0.19994 & -1.3707 & 0.088487 \tabularnewline
3 & -0.204732 & -1.4036 & 0.083509 \tabularnewline
4 & 0.089529 & 0.6138 & 0.27116 \tabularnewline
5 & -0.074328 & -0.5096 & 0.306369 \tabularnewline
6 & -0.064669 & -0.4434 & 0.329773 \tabularnewline
7 & -0.05144 & -0.3527 & 0.362961 \tabularnewline
8 & -0.307027 & -2.1049 & 0.020338 \tabularnewline
9 & -0.007049 & -0.0483 & 0.48083 \tabularnewline
10 & -0.216201 & -1.4822 & 0.072481 \tabularnewline
11 & 0.141878 & 0.9727 & 0.16785 \tabularnewline
12 & 0.013649 & 0.0936 & 0.462924 \tabularnewline
13 & -0.198345 & -1.3598 & 0.090193 \tabularnewline
14 & -0.018997 & -0.1302 & 0.448467 \tabularnewline
15 & 0.015687 & 0.1075 & 0.457408 \tabularnewline
16 & 0.055045 & 0.3774 & 0.353799 \tabularnewline
17 & 0.005752 & 0.0394 & 0.484357 \tabularnewline
18 & -0.139023 & -0.9531 & 0.17271 \tabularnewline
19 & 0.069125 & 0.4739 & 0.318883 \tabularnewline
20 & -0.055738 & -0.3821 & 0.352046 \tabularnewline
21 & 0.047996 & 0.329 & 0.371792 \tabularnewline
22 & 0.025042 & 0.1717 & 0.432212 \tabularnewline
23 & 0.074689 & 0.512 & 0.30551 \tabularnewline
24 & -0.227095 & -1.5569 & 0.063103 \tabularnewline
25 & -0.035691 & -0.2447 & 0.403882 \tabularnewline
26 & -0.053907 & -0.3696 & 0.356683 \tabularnewline
27 & -0.135915 & -0.9318 & 0.178105 \tabularnewline
28 & -0.171963 & -1.1789 & 0.122182 \tabularnewline
29 & -0.030694 & -0.2104 & 0.417122 \tabularnewline
30 & 0.029859 & 0.2047 & 0.419344 \tabularnewline
31 & 0.003904 & 0.0268 & 0.48938 \tabularnewline
32 & 0.002747 & 0.0188 & 0.492527 \tabularnewline
33 & -0.125089 & -0.8576 & 0.197741 \tabularnewline
34 & -0.10793 & -0.7399 & 0.23151 \tabularnewline
35 & 0.013178 & 0.0903 & 0.464199 \tabularnewline
36 & -0.05897 & -0.4043 & 0.343921 \tabularnewline
37 & 0.00855 & 0.0586 & 0.476754 \tabularnewline
38 & 0.104412 & 0.7158 & 0.238825 \tabularnewline
39 & 0.018713 & 0.1283 & 0.449233 \tabularnewline
40 & -0.06892 & -0.4725 & 0.319381 \tabularnewline
41 & -0.060357 & -0.4138 & 0.340456 \tabularnewline
42 & 0.014119 & 0.0968 & 0.461652 \tabularnewline
43 & 0.053001 & 0.3634 & 0.358983 \tabularnewline
44 & 0.000179 & 0.0012 & 0.499513 \tabularnewline
45 & -0.084209 & -0.5773 & 0.283244 \tabularnewline
46 & 0.009109 & 0.0624 & 0.475236 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62893&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]-0.484636[/C][C]-3.3225[/C][C]0.000867[/C][/ROW]
[ROW][C]2[/C][C]-0.19994[/C][C]-1.3707[/C][C]0.088487[/C][/ROW]
[ROW][C]3[/C][C]-0.204732[/C][C]-1.4036[/C][C]0.083509[/C][/ROW]
[ROW][C]4[/C][C]0.089529[/C][C]0.6138[/C][C]0.27116[/C][/ROW]
[ROW][C]5[/C][C]-0.074328[/C][C]-0.5096[/C][C]0.306369[/C][/ROW]
[ROW][C]6[/C][C]-0.064669[/C][C]-0.4434[/C][C]0.329773[/C][/ROW]
[ROW][C]7[/C][C]-0.05144[/C][C]-0.3527[/C][C]0.362961[/C][/ROW]
[ROW][C]8[/C][C]-0.307027[/C][C]-2.1049[/C][C]0.020338[/C][/ROW]
[ROW][C]9[/C][C]-0.007049[/C][C]-0.0483[/C][C]0.48083[/C][/ROW]
[ROW][C]10[/C][C]-0.216201[/C][C]-1.4822[/C][C]0.072481[/C][/ROW]
[ROW][C]11[/C][C]0.141878[/C][C]0.9727[/C][C]0.16785[/C][/ROW]
[ROW][C]12[/C][C]0.013649[/C][C]0.0936[/C][C]0.462924[/C][/ROW]
[ROW][C]13[/C][C]-0.198345[/C][C]-1.3598[/C][C]0.090193[/C][/ROW]
[ROW][C]14[/C][C]-0.018997[/C][C]-0.1302[/C][C]0.448467[/C][/ROW]
[ROW][C]15[/C][C]0.015687[/C][C]0.1075[/C][C]0.457408[/C][/ROW]
[ROW][C]16[/C][C]0.055045[/C][C]0.3774[/C][C]0.353799[/C][/ROW]
[ROW][C]17[/C][C]0.005752[/C][C]0.0394[/C][C]0.484357[/C][/ROW]
[ROW][C]18[/C][C]-0.139023[/C][C]-0.9531[/C][C]0.17271[/C][/ROW]
[ROW][C]19[/C][C]0.069125[/C][C]0.4739[/C][C]0.318883[/C][/ROW]
[ROW][C]20[/C][C]-0.055738[/C][C]-0.3821[/C][C]0.352046[/C][/ROW]
[ROW][C]21[/C][C]0.047996[/C][C]0.329[/C][C]0.371792[/C][/ROW]
[ROW][C]22[/C][C]0.025042[/C][C]0.1717[/C][C]0.432212[/C][/ROW]
[ROW][C]23[/C][C]0.074689[/C][C]0.512[/C][C]0.30551[/C][/ROW]
[ROW][C]24[/C][C]-0.227095[/C][C]-1.5569[/C][C]0.063103[/C][/ROW]
[ROW][C]25[/C][C]-0.035691[/C][C]-0.2447[/C][C]0.403882[/C][/ROW]
[ROW][C]26[/C][C]-0.053907[/C][C]-0.3696[/C][C]0.356683[/C][/ROW]
[ROW][C]27[/C][C]-0.135915[/C][C]-0.9318[/C][C]0.178105[/C][/ROW]
[ROW][C]28[/C][C]-0.171963[/C][C]-1.1789[/C][C]0.122182[/C][/ROW]
[ROW][C]29[/C][C]-0.030694[/C][C]-0.2104[/C][C]0.417122[/C][/ROW]
[ROW][C]30[/C][C]0.029859[/C][C]0.2047[/C][C]0.419344[/C][/ROW]
[ROW][C]31[/C][C]0.003904[/C][C]0.0268[/C][C]0.48938[/C][/ROW]
[ROW][C]32[/C][C]0.002747[/C][C]0.0188[/C][C]0.492527[/C][/ROW]
[ROW][C]33[/C][C]-0.125089[/C][C]-0.8576[/C][C]0.197741[/C][/ROW]
[ROW][C]34[/C][C]-0.10793[/C][C]-0.7399[/C][C]0.23151[/C][/ROW]
[ROW][C]35[/C][C]0.013178[/C][C]0.0903[/C][C]0.464199[/C][/ROW]
[ROW][C]36[/C][C]-0.05897[/C][C]-0.4043[/C][C]0.343921[/C][/ROW]
[ROW][C]37[/C][C]0.00855[/C][C]0.0586[/C][C]0.476754[/C][/ROW]
[ROW][C]38[/C][C]0.104412[/C][C]0.7158[/C][C]0.238825[/C][/ROW]
[ROW][C]39[/C][C]0.018713[/C][C]0.1283[/C][C]0.449233[/C][/ROW]
[ROW][C]40[/C][C]-0.06892[/C][C]-0.4725[/C][C]0.319381[/C][/ROW]
[ROW][C]41[/C][C]-0.060357[/C][C]-0.4138[/C][C]0.340456[/C][/ROW]
[ROW][C]42[/C][C]0.014119[/C][C]0.0968[/C][C]0.461652[/C][/ROW]
[ROW][C]43[/C][C]0.053001[/C][C]0.3634[/C][C]0.358983[/C][/ROW]
[ROW][C]44[/C][C]0.000179[/C][C]0.0012[/C][C]0.499513[/C][/ROW]
[ROW][C]45[/C][C]-0.084209[/C][C]-0.5773[/C][C]0.283244[/C][/ROW]
[ROW][C]46[/C][C]0.009109[/C][C]0.0624[/C][C]0.475236[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62893&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62893&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
1-0.484636-3.32250.000867
2-0.19994-1.37070.088487
3-0.204732-1.40360.083509
40.0895290.61380.27116
5-0.074328-0.50960.306369
6-0.064669-0.44340.329773
7-0.05144-0.35270.362961
8-0.307027-2.10490.020338
9-0.007049-0.04830.48083
10-0.216201-1.48220.072481
110.1418780.97270.16785
120.0136490.09360.462924
13-0.198345-1.35980.090193
14-0.018997-0.13020.448467
150.0156870.10750.457408
160.0550450.37740.353799
170.0057520.03940.484357
18-0.139023-0.95310.17271
190.0691250.47390.318883
20-0.055738-0.38210.352046
210.0479960.3290.371792
220.0250420.17170.432212
230.0746890.5120.30551
24-0.227095-1.55690.063103
25-0.035691-0.24470.403882
26-0.053907-0.36960.356683
27-0.135915-0.93180.178105
28-0.171963-1.17890.122182
29-0.030694-0.21040.417122
300.0298590.20470.419344
310.0039040.02680.48938
320.0027470.01880.492527
33-0.125089-0.85760.197741
34-0.10793-0.73990.23151
350.0131780.09030.464199
36-0.05897-0.40430.343921
370.008550.05860.476754
380.1044120.71580.238825
390.0187130.12830.449233
40-0.06892-0.47250.319381
41-0.060357-0.41380.340456
420.0141190.09680.461652
430.0530010.36340.358983
440.0001790.00120.499513
45-0.084209-0.57730.283244
460.0091090.06240.475236
47NANANA
48NANANA



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