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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, 13 Dec 2010 19:58:53 +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/13/t1292270301uhv6lghwp705wx4.htm/, Retrieved Mon, 06 May 2024 22:17:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109136, Retrieved Mon, 06 May 2024 22:17:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [] [2010-12-13 08:35:23] [21eff0c210342db4afbdafe426a7c254]
-   PD  [(Partial) Autocorrelation Function] [] [2010-12-13 09:29:04] [21eff0c210342db4afbdafe426a7c254]
-    D    [(Partial) Autocorrelation Function] [] [2010-12-13 09:39:12] [21eff0c210342db4afbdafe426a7c254]
-   P         [(Partial) Autocorrelation Function] [] [2010-12-13 19:58:53] [81d69fb83507cea26168920232cdff1b] [Current]
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Dataseries X:
76.14
75.93
74.49
74.73
75.56
84.19
79.30
74.70
77.09
74.88
77.56
74.08
68.38
71.63
64.65
69.13
58.10
50.28
46.95
41.76
43.91
41.53
54.04
72.69
99.29
114.57
132.55
131.52
122.77
109.05
101.84
93.75
90.82
89.43
91.27
82.15
76.91
70.13
73.67
68.19
65.10
65.10
60.60
57.58
53.40
61.00
58.13
57.95
61.97
71.81
72.51
68.29
68.61
68.00
60.93
59.71
62.36
56.47




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109136&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109136&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109136&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9434676.39890
20.8209125.56771e-06
30.6457494.37973.4e-05
40.4517323.06380.001824
50.2513531.70480.047493
60.0631890.42860.335118
7-0.10901-0.73930.231727
8-0.268423-1.82050.037594
9-0.41225-2.7960.003762
10-0.527866-3.58020.000412
11-0.603666-4.09438.5e-05
12-0.636477-4.31684.2e-05
13-0.608917-4.12997.6e-05
14-0.536146-3.63630.000348
15-0.430771-2.92160.002691
16-0.321058-2.17750.017304
17-0.209198-1.41880.081342
18-0.107425-0.72860.234972
19-0.020473-0.13890.445084
200.0439670.29820.383448
210.096970.65770.25701
220.130960.88820.189523
230.1512261.02570.155206
240.1551291.05210.149116
250.1529181.03710.152546
260.1378270.93480.17739
270.1157490.7850.218225
280.0912680.6190.269483
290.0668350.45330.326233
300.0441410.29940.383
310.0185610.12590.450184
320.003030.02060.491846
33-0.009375-0.06360.474788
34-0.013858-0.0940.462762
35-0.016622-0.11270.455366
36-0.014492-0.09830.461065
37-0.012608-0.08550.466112
38-0.0103-0.06990.472305
39-0.008241-0.05590.477836
40-0.00353-0.02390.490501
41-0.001312-0.00890.49647
42-0.001673-0.01130.495498
43-0.000481-0.00330.498707
44-0.000903-0.00610.497569
459.3e-056e-040.499751
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.943467 & 6.3989 & 0 \tabularnewline
2 & 0.820912 & 5.5677 & 1e-06 \tabularnewline
3 & 0.645749 & 4.3797 & 3.4e-05 \tabularnewline
4 & 0.451732 & 3.0638 & 0.001824 \tabularnewline
5 & 0.251353 & 1.7048 & 0.047493 \tabularnewline
6 & 0.063189 & 0.4286 & 0.335118 \tabularnewline
7 & -0.10901 & -0.7393 & 0.231727 \tabularnewline
8 & -0.268423 & -1.8205 & 0.037594 \tabularnewline
9 & -0.41225 & -2.796 & 0.003762 \tabularnewline
10 & -0.527866 & -3.5802 & 0.000412 \tabularnewline
11 & -0.603666 & -4.0943 & 8.5e-05 \tabularnewline
12 & -0.636477 & -4.3168 & 4.2e-05 \tabularnewline
13 & -0.608917 & -4.1299 & 7.6e-05 \tabularnewline
14 & -0.536146 & -3.6363 & 0.000348 \tabularnewline
15 & -0.430771 & -2.9216 & 0.002691 \tabularnewline
16 & -0.321058 & -2.1775 & 0.017304 \tabularnewline
17 & -0.209198 & -1.4188 & 0.081342 \tabularnewline
18 & -0.107425 & -0.7286 & 0.234972 \tabularnewline
19 & -0.020473 & -0.1389 & 0.445084 \tabularnewline
20 & 0.043967 & 0.2982 & 0.383448 \tabularnewline
21 & 0.09697 & 0.6577 & 0.25701 \tabularnewline
22 & 0.13096 & 0.8882 & 0.189523 \tabularnewline
23 & 0.151226 & 1.0257 & 0.155206 \tabularnewline
24 & 0.155129 & 1.0521 & 0.149116 \tabularnewline
25 & 0.152918 & 1.0371 & 0.152546 \tabularnewline
26 & 0.137827 & 0.9348 & 0.17739 \tabularnewline
27 & 0.115749 & 0.785 & 0.218225 \tabularnewline
28 & 0.091268 & 0.619 & 0.269483 \tabularnewline
29 & 0.066835 & 0.4533 & 0.326233 \tabularnewline
30 & 0.044141 & 0.2994 & 0.383 \tabularnewline
31 & 0.018561 & 0.1259 & 0.450184 \tabularnewline
32 & 0.00303 & 0.0206 & 0.491846 \tabularnewline
33 & -0.009375 & -0.0636 & 0.474788 \tabularnewline
34 & -0.013858 & -0.094 & 0.462762 \tabularnewline
35 & -0.016622 & -0.1127 & 0.455366 \tabularnewline
36 & -0.014492 & -0.0983 & 0.461065 \tabularnewline
37 & -0.012608 & -0.0855 & 0.466112 \tabularnewline
38 & -0.0103 & -0.0699 & 0.472305 \tabularnewline
39 & -0.008241 & -0.0559 & 0.477836 \tabularnewline
40 & -0.00353 & -0.0239 & 0.490501 \tabularnewline
41 & -0.001312 & -0.0089 & 0.49647 \tabularnewline
42 & -0.001673 & -0.0113 & 0.495498 \tabularnewline
43 & -0.000481 & -0.0033 & 0.498707 \tabularnewline
44 & -0.000903 & -0.0061 & 0.497569 \tabularnewline
45 & 9.3e-05 & 6e-04 & 0.499751 \tabularnewline
46 & NA & NA & NA \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109136&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]0.943467[/C][C]6.3989[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.820912[/C][C]5.5677[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.645749[/C][C]4.3797[/C][C]3.4e-05[/C][/ROW]
[ROW][C]4[/C][C]0.451732[/C][C]3.0638[/C][C]0.001824[/C][/ROW]
[ROW][C]5[/C][C]0.251353[/C][C]1.7048[/C][C]0.047493[/C][/ROW]
[ROW][C]6[/C][C]0.063189[/C][C]0.4286[/C][C]0.335118[/C][/ROW]
[ROW][C]7[/C][C]-0.10901[/C][C]-0.7393[/C][C]0.231727[/C][/ROW]
[ROW][C]8[/C][C]-0.268423[/C][C]-1.8205[/C][C]0.037594[/C][/ROW]
[ROW][C]9[/C][C]-0.41225[/C][C]-2.796[/C][C]0.003762[/C][/ROW]
[ROW][C]10[/C][C]-0.527866[/C][C]-3.5802[/C][C]0.000412[/C][/ROW]
[ROW][C]11[/C][C]-0.603666[/C][C]-4.0943[/C][C]8.5e-05[/C][/ROW]
[ROW][C]12[/C][C]-0.636477[/C][C]-4.3168[/C][C]4.2e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.608917[/C][C]-4.1299[/C][C]7.6e-05[/C][/ROW]
[ROW][C]14[/C][C]-0.536146[/C][C]-3.6363[/C][C]0.000348[/C][/ROW]
[ROW][C]15[/C][C]-0.430771[/C][C]-2.9216[/C][C]0.002691[/C][/ROW]
[ROW][C]16[/C][C]-0.321058[/C][C]-2.1775[/C][C]0.017304[/C][/ROW]
[ROW][C]17[/C][C]-0.209198[/C][C]-1.4188[/C][C]0.081342[/C][/ROW]
[ROW][C]18[/C][C]-0.107425[/C][C]-0.7286[/C][C]0.234972[/C][/ROW]
[ROW][C]19[/C][C]-0.020473[/C][C]-0.1389[/C][C]0.445084[/C][/ROW]
[ROW][C]20[/C][C]0.043967[/C][C]0.2982[/C][C]0.383448[/C][/ROW]
[ROW][C]21[/C][C]0.09697[/C][C]0.6577[/C][C]0.25701[/C][/ROW]
[ROW][C]22[/C][C]0.13096[/C][C]0.8882[/C][C]0.189523[/C][/ROW]
[ROW][C]23[/C][C]0.151226[/C][C]1.0257[/C][C]0.155206[/C][/ROW]
[ROW][C]24[/C][C]0.155129[/C][C]1.0521[/C][C]0.149116[/C][/ROW]
[ROW][C]25[/C][C]0.152918[/C][C]1.0371[/C][C]0.152546[/C][/ROW]
[ROW][C]26[/C][C]0.137827[/C][C]0.9348[/C][C]0.17739[/C][/ROW]
[ROW][C]27[/C][C]0.115749[/C][C]0.785[/C][C]0.218225[/C][/ROW]
[ROW][C]28[/C][C]0.091268[/C][C]0.619[/C][C]0.269483[/C][/ROW]
[ROW][C]29[/C][C]0.066835[/C][C]0.4533[/C][C]0.326233[/C][/ROW]
[ROW][C]30[/C][C]0.044141[/C][C]0.2994[/C][C]0.383[/C][/ROW]
[ROW][C]31[/C][C]0.018561[/C][C]0.1259[/C][C]0.450184[/C][/ROW]
[ROW][C]32[/C][C]0.00303[/C][C]0.0206[/C][C]0.491846[/C][/ROW]
[ROW][C]33[/C][C]-0.009375[/C][C]-0.0636[/C][C]0.474788[/C][/ROW]
[ROW][C]34[/C][C]-0.013858[/C][C]-0.094[/C][C]0.462762[/C][/ROW]
[ROW][C]35[/C][C]-0.016622[/C][C]-0.1127[/C][C]0.455366[/C][/ROW]
[ROW][C]36[/C][C]-0.014492[/C][C]-0.0983[/C][C]0.461065[/C][/ROW]
[ROW][C]37[/C][C]-0.012608[/C][C]-0.0855[/C][C]0.466112[/C][/ROW]
[ROW][C]38[/C][C]-0.0103[/C][C]-0.0699[/C][C]0.472305[/C][/ROW]
[ROW][C]39[/C][C]-0.008241[/C][C]-0.0559[/C][C]0.477836[/C][/ROW]
[ROW][C]40[/C][C]-0.00353[/C][C]-0.0239[/C][C]0.490501[/C][/ROW]
[ROW][C]41[/C][C]-0.001312[/C][C]-0.0089[/C][C]0.49647[/C][/ROW]
[ROW][C]42[/C][C]-0.001673[/C][C]-0.0113[/C][C]0.495498[/C][/ROW]
[ROW][C]43[/C][C]-0.000481[/C][C]-0.0033[/C][C]0.498707[/C][/ROW]
[ROW][C]44[/C][C]-0.000903[/C][C]-0.0061[/C][C]0.497569[/C][/ROW]
[ROW][C]45[/C][C]9.3e-05[/C][C]6e-04[/C][C]0.499751[/C][/ROW]
[ROW][C]46[/C][C]NA[/C][C]NA[/C][C]NA[/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=109136&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109136&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
10.9434676.39890
20.8209125.56771e-06
30.6457494.37973.4e-05
40.4517323.06380.001824
50.2513531.70480.047493
60.0631890.42860.335118
7-0.10901-0.73930.231727
8-0.268423-1.82050.037594
9-0.41225-2.7960.003762
10-0.527866-3.58020.000412
11-0.603666-4.09438.5e-05
12-0.636477-4.31684.2e-05
13-0.608917-4.12997.6e-05
14-0.536146-3.63630.000348
15-0.430771-2.92160.002691
16-0.321058-2.17750.017304
17-0.209198-1.41880.081342
18-0.107425-0.72860.234972
19-0.020473-0.13890.445084
200.0439670.29820.383448
210.096970.65770.25701
220.130960.88820.189523
230.1512261.02570.155206
240.1551291.05210.149116
250.1529181.03710.152546
260.1378270.93480.17739
270.1157490.7850.218225
280.0912680.6190.269483
290.0668350.45330.326233
300.0441410.29940.383
310.0185610.12590.450184
320.003030.02060.491846
33-0.009375-0.06360.474788
34-0.013858-0.0940.462762
35-0.016622-0.11270.455366
36-0.014492-0.09830.461065
37-0.012608-0.08550.466112
38-0.0103-0.06990.472305
39-0.008241-0.05590.477836
40-0.00353-0.02390.490501
41-0.001312-0.00890.49647
42-0.001673-0.01130.495498
43-0.000481-0.00330.498707
44-0.000903-0.00610.497569
459.3e-056e-040.499751
46NANANA
47NANANA
48NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9434676.39890
2-0.630015-4.2734.8e-05
3-0.336621-2.28310.013547
40.0921540.6250.267523
5-0.103298-0.70060.243539
6-0.051003-0.34590.365491
7-0.121837-0.82630.206438
8-0.279298-1.89430.032242
9-0.123277-0.83610.203709
100.0944040.64030.262583
110.0679750.4610.323475
12-0.072162-0.48940.313434
130.2674461.81390.038109
14-0.125495-0.85110.199548
15-0.175532-1.19050.119975
16-0.145215-0.98490.164913
170.0759560.51520.304455
18-0.022119-0.150.440703
19-0.122916-0.83370.204391
20-0.227605-1.54370.064758
210.0348050.23610.407218
22-0.063718-0.43220.333823
230.0978410.66360.255133
24-0.012553-0.08510.466259
250.1315970.89250.188377
26-0.170431-1.15590.126841
27-0.002936-0.01990.4921
28-0.075202-0.510.306228
29-0.032715-0.22190.412693
300.0148820.10090.460022
31-0.143365-0.97240.167981
32-0.049747-0.33740.368675
33-0.035782-0.24270.404663
340.000760.00520.497954
350.051330.34810.364662
36-0.081318-0.55150.291972
370.1101250.74690.229462
38-0.078339-0.53130.298877
390.0075630.05130.479657
40-0.07404-0.50220.308973
41-0.033125-0.22470.411618
42-0.079184-0.53710.296909
430.001320.0090.496448
44-0.077104-0.52290.30176
450.0570440.38690.350309
46NANANA
47NANANA
48NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.943467 & 6.3989 & 0 \tabularnewline
2 & -0.630015 & -4.273 & 4.8e-05 \tabularnewline
3 & -0.336621 & -2.2831 & 0.013547 \tabularnewline
4 & 0.092154 & 0.625 & 0.267523 \tabularnewline
5 & -0.103298 & -0.7006 & 0.243539 \tabularnewline
6 & -0.051003 & -0.3459 & 0.365491 \tabularnewline
7 & -0.121837 & -0.8263 & 0.206438 \tabularnewline
8 & -0.279298 & -1.8943 & 0.032242 \tabularnewline
9 & -0.123277 & -0.8361 & 0.203709 \tabularnewline
10 & 0.094404 & 0.6403 & 0.262583 \tabularnewline
11 & 0.067975 & 0.461 & 0.323475 \tabularnewline
12 & -0.072162 & -0.4894 & 0.313434 \tabularnewline
13 & 0.267446 & 1.8139 & 0.038109 \tabularnewline
14 & -0.125495 & -0.8511 & 0.199548 \tabularnewline
15 & -0.175532 & -1.1905 & 0.119975 \tabularnewline
16 & -0.145215 & -0.9849 & 0.164913 \tabularnewline
17 & 0.075956 & 0.5152 & 0.304455 \tabularnewline
18 & -0.022119 & -0.15 & 0.440703 \tabularnewline
19 & -0.122916 & -0.8337 & 0.204391 \tabularnewline
20 & -0.227605 & -1.5437 & 0.064758 \tabularnewline
21 & 0.034805 & 0.2361 & 0.407218 \tabularnewline
22 & -0.063718 & -0.4322 & 0.333823 \tabularnewline
23 & 0.097841 & 0.6636 & 0.255133 \tabularnewline
24 & -0.012553 & -0.0851 & 0.466259 \tabularnewline
25 & 0.131597 & 0.8925 & 0.188377 \tabularnewline
26 & -0.170431 & -1.1559 & 0.126841 \tabularnewline
27 & -0.002936 & -0.0199 & 0.4921 \tabularnewline
28 & -0.075202 & -0.51 & 0.306228 \tabularnewline
29 & -0.032715 & -0.2219 & 0.412693 \tabularnewline
30 & 0.014882 & 0.1009 & 0.460022 \tabularnewline
31 & -0.143365 & -0.9724 & 0.167981 \tabularnewline
32 & -0.049747 & -0.3374 & 0.368675 \tabularnewline
33 & -0.035782 & -0.2427 & 0.404663 \tabularnewline
34 & 0.00076 & 0.0052 & 0.497954 \tabularnewline
35 & 0.05133 & 0.3481 & 0.364662 \tabularnewline
36 & -0.081318 & -0.5515 & 0.291972 \tabularnewline
37 & 0.110125 & 0.7469 & 0.229462 \tabularnewline
38 & -0.078339 & -0.5313 & 0.298877 \tabularnewline
39 & 0.007563 & 0.0513 & 0.479657 \tabularnewline
40 & -0.07404 & -0.5022 & 0.308973 \tabularnewline
41 & -0.033125 & -0.2247 & 0.411618 \tabularnewline
42 & -0.079184 & -0.5371 & 0.296909 \tabularnewline
43 & 0.00132 & 0.009 & 0.496448 \tabularnewline
44 & -0.077104 & -0.5229 & 0.30176 \tabularnewline
45 & 0.057044 & 0.3869 & 0.350309 \tabularnewline
46 & NA & NA & NA \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109136&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]0.943467[/C][C]6.3989[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.630015[/C][C]-4.273[/C][C]4.8e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.336621[/C][C]-2.2831[/C][C]0.013547[/C][/ROW]
[ROW][C]4[/C][C]0.092154[/C][C]0.625[/C][C]0.267523[/C][/ROW]
[ROW][C]5[/C][C]-0.103298[/C][C]-0.7006[/C][C]0.243539[/C][/ROW]
[ROW][C]6[/C][C]-0.051003[/C][C]-0.3459[/C][C]0.365491[/C][/ROW]
[ROW][C]7[/C][C]-0.121837[/C][C]-0.8263[/C][C]0.206438[/C][/ROW]
[ROW][C]8[/C][C]-0.279298[/C][C]-1.8943[/C][C]0.032242[/C][/ROW]
[ROW][C]9[/C][C]-0.123277[/C][C]-0.8361[/C][C]0.203709[/C][/ROW]
[ROW][C]10[/C][C]0.094404[/C][C]0.6403[/C][C]0.262583[/C][/ROW]
[ROW][C]11[/C][C]0.067975[/C][C]0.461[/C][C]0.323475[/C][/ROW]
[ROW][C]12[/C][C]-0.072162[/C][C]-0.4894[/C][C]0.313434[/C][/ROW]
[ROW][C]13[/C][C]0.267446[/C][C]1.8139[/C][C]0.038109[/C][/ROW]
[ROW][C]14[/C][C]-0.125495[/C][C]-0.8511[/C][C]0.199548[/C][/ROW]
[ROW][C]15[/C][C]-0.175532[/C][C]-1.1905[/C][C]0.119975[/C][/ROW]
[ROW][C]16[/C][C]-0.145215[/C][C]-0.9849[/C][C]0.164913[/C][/ROW]
[ROW][C]17[/C][C]0.075956[/C][C]0.5152[/C][C]0.304455[/C][/ROW]
[ROW][C]18[/C][C]-0.022119[/C][C]-0.15[/C][C]0.440703[/C][/ROW]
[ROW][C]19[/C][C]-0.122916[/C][C]-0.8337[/C][C]0.204391[/C][/ROW]
[ROW][C]20[/C][C]-0.227605[/C][C]-1.5437[/C][C]0.064758[/C][/ROW]
[ROW][C]21[/C][C]0.034805[/C][C]0.2361[/C][C]0.407218[/C][/ROW]
[ROW][C]22[/C][C]-0.063718[/C][C]-0.4322[/C][C]0.333823[/C][/ROW]
[ROW][C]23[/C][C]0.097841[/C][C]0.6636[/C][C]0.255133[/C][/ROW]
[ROW][C]24[/C][C]-0.012553[/C][C]-0.0851[/C][C]0.466259[/C][/ROW]
[ROW][C]25[/C][C]0.131597[/C][C]0.8925[/C][C]0.188377[/C][/ROW]
[ROW][C]26[/C][C]-0.170431[/C][C]-1.1559[/C][C]0.126841[/C][/ROW]
[ROW][C]27[/C][C]-0.002936[/C][C]-0.0199[/C][C]0.4921[/C][/ROW]
[ROW][C]28[/C][C]-0.075202[/C][C]-0.51[/C][C]0.306228[/C][/ROW]
[ROW][C]29[/C][C]-0.032715[/C][C]-0.2219[/C][C]0.412693[/C][/ROW]
[ROW][C]30[/C][C]0.014882[/C][C]0.1009[/C][C]0.460022[/C][/ROW]
[ROW][C]31[/C][C]-0.143365[/C][C]-0.9724[/C][C]0.167981[/C][/ROW]
[ROW][C]32[/C][C]-0.049747[/C][C]-0.3374[/C][C]0.368675[/C][/ROW]
[ROW][C]33[/C][C]-0.035782[/C][C]-0.2427[/C][C]0.404663[/C][/ROW]
[ROW][C]34[/C][C]0.00076[/C][C]0.0052[/C][C]0.497954[/C][/ROW]
[ROW][C]35[/C][C]0.05133[/C][C]0.3481[/C][C]0.364662[/C][/ROW]
[ROW][C]36[/C][C]-0.081318[/C][C]-0.5515[/C][C]0.291972[/C][/ROW]
[ROW][C]37[/C][C]0.110125[/C][C]0.7469[/C][C]0.229462[/C][/ROW]
[ROW][C]38[/C][C]-0.078339[/C][C]-0.5313[/C][C]0.298877[/C][/ROW]
[ROW][C]39[/C][C]0.007563[/C][C]0.0513[/C][C]0.479657[/C][/ROW]
[ROW][C]40[/C][C]-0.07404[/C][C]-0.5022[/C][C]0.308973[/C][/ROW]
[ROW][C]41[/C][C]-0.033125[/C][C]-0.2247[/C][C]0.411618[/C][/ROW]
[ROW][C]42[/C][C]-0.079184[/C][C]-0.5371[/C][C]0.296909[/C][/ROW]
[ROW][C]43[/C][C]0.00132[/C][C]0.009[/C][C]0.496448[/C][/ROW]
[ROW][C]44[/C][C]-0.077104[/C][C]-0.5229[/C][C]0.30176[/C][/ROW]
[ROW][C]45[/C][C]0.057044[/C][C]0.3869[/C][C]0.350309[/C][/ROW]
[ROW][C]46[/C][C]NA[/C][C]NA[/C][C]NA[/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=109136&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109136&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
10.9434676.39890
2-0.630015-4.2734.8e-05
3-0.336621-2.28310.013547
40.0921540.6250.267523
5-0.103298-0.70060.243539
6-0.051003-0.34590.365491
7-0.121837-0.82630.206438
8-0.279298-1.89430.032242
9-0.123277-0.83610.203709
100.0944040.64030.262583
110.0679750.4610.323475
12-0.072162-0.48940.313434
130.2674461.81390.038109
14-0.125495-0.85110.199548
15-0.175532-1.19050.119975
16-0.145215-0.98490.164913
170.0759560.51520.304455
18-0.022119-0.150.440703
19-0.122916-0.83370.204391
20-0.227605-1.54370.064758
210.0348050.23610.407218
22-0.063718-0.43220.333823
230.0978410.66360.255133
24-0.012553-0.08510.466259
250.1315970.89250.188377
26-0.170431-1.15590.126841
27-0.002936-0.01990.4921
28-0.075202-0.510.306228
29-0.032715-0.22190.412693
300.0148820.10090.460022
31-0.143365-0.97240.167981
32-0.049747-0.33740.368675
33-0.035782-0.24270.404663
340.000760.00520.497954
350.051330.34810.364662
36-0.081318-0.55150.291972
370.1101250.74690.229462
38-0.078339-0.53130.298877
390.0075630.05130.479657
40-0.07404-0.50220.308973
41-0.033125-0.22470.411618
42-0.079184-0.53710.296909
430.001320.0090.496448
44-0.077104-0.52290.30176
450.0570440.38690.350309
46NANANA
47NANANA
48NANANA



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