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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 computationFri, 17 Dec 2010 14:09:32 +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/17/t12925948607jcaxbd2xgmznv1.htm/, Retrieved Sun, 28 Apr 2024 23:01:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111478, Retrieved Sun, 28 Apr 2024 23:01:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Monthly US soldie...] [2010-11-02 12:07:39] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Soldiers] [2010-11-29 09:48:36] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [] [2010-12-03 11:32:19] [8a9a6f7c332640af31ddca253a8ded58]
-   PD      [(Partial) Autocorrelation Function] [] [2010-12-03 14:14:33] [8a9a6f7c332640af31ddca253a8ded58]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-17 14:09:32] [df17410ebb98883e83037e1662207ccb] [Current]
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Dataseries X:
101.76
102.37
102.38
102.86
102.87
102.92
102.95
103.02
104.08
104.16
104.24
104.33
104.73
104.86
105.03
105.62
105.63
105.63
105.94
106.61
107.69
107.78
107.93
108.48
108.14
108.48
108.48
108.89
108.93
109.21
109.47
109.80
111.73
111.85
112.12
112.15
112.17
112.67
112.80
113.44
113.53
114.53
114.51
115.05
116.67
117.07
116.92
117.00
117.02
117.35
117.36
117.82
117.88
118.24
118.50
118.80
119.76
120.09




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=111478&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=111478&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111478&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
1-0.085651-0.64660.260228
2-0.038335-0.28940.386654
3-0.06786-0.51230.305199
4-0.145992-1.10220.137501
50.074780.56460.287288
6-0.232557-1.75580.04225
70.1613581.21820.114078
8-0.236061-1.78220.04002
90.0107020.08080.467944
10-0.096398-0.72780.234861
11-9e-04-0.00680.497302
120.6108734.6121.2e-05
13-0.016346-0.12340.451108
14-0.061554-0.46470.321951
15-0.108155-0.81660.208792
16-0.209846-1.58430.059329
170.0831650.62790.266294
18-0.104474-0.78880.21676
190.0891340.67290.25185
20-0.117726-0.88880.188921
210.0127650.09640.46178
220.0272570.20580.418846
23-0.108413-0.81850.208241
240.4216163.18310.00118
25-0.018754-0.14160.443951
26-0.001498-0.01130.495508
27-0.179903-1.35820.08987
28-0.141332-1.0670.145227
290.1191510.89960.186067
30-0.117955-0.89050.188459
310.0807050.60930.272369
32-0.080898-0.61080.27189
330.0496130.37460.354684
34-0.080301-0.60630.273375
35-0.061521-0.46450.32204
360.1930961.45780.075186
37-0.020726-0.15650.438104
38-0.0297-0.22420.41169
39-0.091087-0.68770.247217
40-0.031871-0.24060.405355
410.0624420.47140.319567
42-0.035809-0.27040.393932
430.0591350.44650.328478
440.0154760.11680.453697
45-0.010661-0.08050.468064
46-0.004777-0.03610.485677
47-0.029801-0.2250.411395
480.0732060.55270.291317

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.085651 & -0.6466 & 0.260228 \tabularnewline
2 & -0.038335 & -0.2894 & 0.386654 \tabularnewline
3 & -0.06786 & -0.5123 & 0.305199 \tabularnewline
4 & -0.145992 & -1.1022 & 0.137501 \tabularnewline
5 & 0.07478 & 0.5646 & 0.287288 \tabularnewline
6 & -0.232557 & -1.7558 & 0.04225 \tabularnewline
7 & 0.161358 & 1.2182 & 0.114078 \tabularnewline
8 & -0.236061 & -1.7822 & 0.04002 \tabularnewline
9 & 0.010702 & 0.0808 & 0.467944 \tabularnewline
10 & -0.096398 & -0.7278 & 0.234861 \tabularnewline
11 & -9e-04 & -0.0068 & 0.497302 \tabularnewline
12 & 0.610873 & 4.612 & 1.2e-05 \tabularnewline
13 & -0.016346 & -0.1234 & 0.451108 \tabularnewline
14 & -0.061554 & -0.4647 & 0.321951 \tabularnewline
15 & -0.108155 & -0.8166 & 0.208792 \tabularnewline
16 & -0.209846 & -1.5843 & 0.059329 \tabularnewline
17 & 0.083165 & 0.6279 & 0.266294 \tabularnewline
18 & -0.104474 & -0.7888 & 0.21676 \tabularnewline
19 & 0.089134 & 0.6729 & 0.25185 \tabularnewline
20 & -0.117726 & -0.8888 & 0.188921 \tabularnewline
21 & 0.012765 & 0.0964 & 0.46178 \tabularnewline
22 & 0.027257 & 0.2058 & 0.418846 \tabularnewline
23 & -0.108413 & -0.8185 & 0.208241 \tabularnewline
24 & 0.421616 & 3.1831 & 0.00118 \tabularnewline
25 & -0.018754 & -0.1416 & 0.443951 \tabularnewline
26 & -0.001498 & -0.0113 & 0.495508 \tabularnewline
27 & -0.179903 & -1.3582 & 0.08987 \tabularnewline
28 & -0.141332 & -1.067 & 0.145227 \tabularnewline
29 & 0.119151 & 0.8996 & 0.186067 \tabularnewline
30 & -0.117955 & -0.8905 & 0.188459 \tabularnewline
31 & 0.080705 & 0.6093 & 0.272369 \tabularnewline
32 & -0.080898 & -0.6108 & 0.27189 \tabularnewline
33 & 0.049613 & 0.3746 & 0.354684 \tabularnewline
34 & -0.080301 & -0.6063 & 0.273375 \tabularnewline
35 & -0.061521 & -0.4645 & 0.32204 \tabularnewline
36 & 0.193096 & 1.4578 & 0.075186 \tabularnewline
37 & -0.020726 & -0.1565 & 0.438104 \tabularnewline
38 & -0.0297 & -0.2242 & 0.41169 \tabularnewline
39 & -0.091087 & -0.6877 & 0.247217 \tabularnewline
40 & -0.031871 & -0.2406 & 0.405355 \tabularnewline
41 & 0.062442 & 0.4714 & 0.319567 \tabularnewline
42 & -0.035809 & -0.2704 & 0.393932 \tabularnewline
43 & 0.059135 & 0.4465 & 0.328478 \tabularnewline
44 & 0.015476 & 0.1168 & 0.453697 \tabularnewline
45 & -0.010661 & -0.0805 & 0.468064 \tabularnewline
46 & -0.004777 & -0.0361 & 0.485677 \tabularnewline
47 & -0.029801 & -0.225 & 0.411395 \tabularnewline
48 & 0.073206 & 0.5527 & 0.291317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111478&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]-0.085651[/C][C]-0.6466[/C][C]0.260228[/C][/ROW]
[ROW][C]2[/C][C]-0.038335[/C][C]-0.2894[/C][C]0.386654[/C][/ROW]
[ROW][C]3[/C][C]-0.06786[/C][C]-0.5123[/C][C]0.305199[/C][/ROW]
[ROW][C]4[/C][C]-0.145992[/C][C]-1.1022[/C][C]0.137501[/C][/ROW]
[ROW][C]5[/C][C]0.07478[/C][C]0.5646[/C][C]0.287288[/C][/ROW]
[ROW][C]6[/C][C]-0.232557[/C][C]-1.7558[/C][C]0.04225[/C][/ROW]
[ROW][C]7[/C][C]0.161358[/C][C]1.2182[/C][C]0.114078[/C][/ROW]
[ROW][C]8[/C][C]-0.236061[/C][C]-1.7822[/C][C]0.04002[/C][/ROW]
[ROW][C]9[/C][C]0.010702[/C][C]0.0808[/C][C]0.467944[/C][/ROW]
[ROW][C]10[/C][C]-0.096398[/C][C]-0.7278[/C][C]0.234861[/C][/ROW]
[ROW][C]11[/C][C]-9e-04[/C][C]-0.0068[/C][C]0.497302[/C][/ROW]
[ROW][C]12[/C][C]0.610873[/C][C]4.612[/C][C]1.2e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.016346[/C][C]-0.1234[/C][C]0.451108[/C][/ROW]
[ROW][C]14[/C][C]-0.061554[/C][C]-0.4647[/C][C]0.321951[/C][/ROW]
[ROW][C]15[/C][C]-0.108155[/C][C]-0.8166[/C][C]0.208792[/C][/ROW]
[ROW][C]16[/C][C]-0.209846[/C][C]-1.5843[/C][C]0.059329[/C][/ROW]
[ROW][C]17[/C][C]0.083165[/C][C]0.6279[/C][C]0.266294[/C][/ROW]
[ROW][C]18[/C][C]-0.104474[/C][C]-0.7888[/C][C]0.21676[/C][/ROW]
[ROW][C]19[/C][C]0.089134[/C][C]0.6729[/C][C]0.25185[/C][/ROW]
[ROW][C]20[/C][C]-0.117726[/C][C]-0.8888[/C][C]0.188921[/C][/ROW]
[ROW][C]21[/C][C]0.012765[/C][C]0.0964[/C][C]0.46178[/C][/ROW]
[ROW][C]22[/C][C]0.027257[/C][C]0.2058[/C][C]0.418846[/C][/ROW]
[ROW][C]23[/C][C]-0.108413[/C][C]-0.8185[/C][C]0.208241[/C][/ROW]
[ROW][C]24[/C][C]0.421616[/C][C]3.1831[/C][C]0.00118[/C][/ROW]
[ROW][C]25[/C][C]-0.018754[/C][C]-0.1416[/C][C]0.443951[/C][/ROW]
[ROW][C]26[/C][C]-0.001498[/C][C]-0.0113[/C][C]0.495508[/C][/ROW]
[ROW][C]27[/C][C]-0.179903[/C][C]-1.3582[/C][C]0.08987[/C][/ROW]
[ROW][C]28[/C][C]-0.141332[/C][C]-1.067[/C][C]0.145227[/C][/ROW]
[ROW][C]29[/C][C]0.119151[/C][C]0.8996[/C][C]0.186067[/C][/ROW]
[ROW][C]30[/C][C]-0.117955[/C][C]-0.8905[/C][C]0.188459[/C][/ROW]
[ROW][C]31[/C][C]0.080705[/C][C]0.6093[/C][C]0.272369[/C][/ROW]
[ROW][C]32[/C][C]-0.080898[/C][C]-0.6108[/C][C]0.27189[/C][/ROW]
[ROW][C]33[/C][C]0.049613[/C][C]0.3746[/C][C]0.354684[/C][/ROW]
[ROW][C]34[/C][C]-0.080301[/C][C]-0.6063[/C][C]0.273375[/C][/ROW]
[ROW][C]35[/C][C]-0.061521[/C][C]-0.4645[/C][C]0.32204[/C][/ROW]
[ROW][C]36[/C][C]0.193096[/C][C]1.4578[/C][C]0.075186[/C][/ROW]
[ROW][C]37[/C][C]-0.020726[/C][C]-0.1565[/C][C]0.438104[/C][/ROW]
[ROW][C]38[/C][C]-0.0297[/C][C]-0.2242[/C][C]0.41169[/C][/ROW]
[ROW][C]39[/C][C]-0.091087[/C][C]-0.6877[/C][C]0.247217[/C][/ROW]
[ROW][C]40[/C][C]-0.031871[/C][C]-0.2406[/C][C]0.405355[/C][/ROW]
[ROW][C]41[/C][C]0.062442[/C][C]0.4714[/C][C]0.319567[/C][/ROW]
[ROW][C]42[/C][C]-0.035809[/C][C]-0.2704[/C][C]0.393932[/C][/ROW]
[ROW][C]43[/C][C]0.059135[/C][C]0.4465[/C][C]0.328478[/C][/ROW]
[ROW][C]44[/C][C]0.015476[/C][C]0.1168[/C][C]0.453697[/C][/ROW]
[ROW][C]45[/C][C]-0.010661[/C][C]-0.0805[/C][C]0.468064[/C][/ROW]
[ROW][C]46[/C][C]-0.004777[/C][C]-0.0361[/C][C]0.485677[/C][/ROW]
[ROW][C]47[/C][C]-0.029801[/C][C]-0.225[/C][C]0.411395[/C][/ROW]
[ROW][C]48[/C][C]0.073206[/C][C]0.5527[/C][C]0.291317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111478&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111478&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
1-0.085651-0.64660.260228
2-0.038335-0.28940.386654
3-0.06786-0.51230.305199
4-0.145992-1.10220.137501
50.074780.56460.287288
6-0.232557-1.75580.04225
70.1613581.21820.114078
8-0.236061-1.78220.04002
90.0107020.08080.467944
10-0.096398-0.72780.234861
11-9e-04-0.00680.497302
120.6108734.6121.2e-05
13-0.016346-0.12340.451108
14-0.061554-0.46470.321951
15-0.108155-0.81660.208792
16-0.209846-1.58430.059329
170.0831650.62790.266294
18-0.104474-0.78880.21676
190.0891340.67290.25185
20-0.117726-0.88880.188921
210.0127650.09640.46178
220.0272570.20580.418846
23-0.108413-0.81850.208241
240.4216163.18310.00118
25-0.018754-0.14160.443951
26-0.001498-0.01130.495508
27-0.179903-1.35820.08987
28-0.141332-1.0670.145227
290.1191510.89960.186067
30-0.117955-0.89050.188459
310.0807050.60930.272369
32-0.080898-0.61080.27189
330.0496130.37460.354684
34-0.080301-0.60630.273375
35-0.061521-0.46450.32204
360.1930961.45780.075186
37-0.020726-0.15650.438104
38-0.0297-0.22420.41169
39-0.091087-0.68770.247217
40-0.031871-0.24060.405355
410.0624420.47140.319567
42-0.035809-0.27040.393932
430.0591350.44650.328478
440.0154760.11680.453697
45-0.010661-0.08050.468064
46-0.004777-0.03610.485677
47-0.029801-0.2250.411395
480.0732060.55270.291317







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.085651-0.64660.260228
2-0.046009-0.34740.364801
3-0.075952-0.57340.284307
4-0.163313-1.2330.111321
50.0393580.29710.383716
6-0.25321-1.91170.030473
70.110310.83280.204211
8-0.29866-2.25480.014001
9-0.01619-0.12220.451573
10-0.26968-2.0360.023202
110.0184270.13910.444922
120.5055643.81690.000168
130.1639141.23750.110483
14-0.161131-1.21650.114402
150.0188030.1420.443808
16-0.344694-2.60240.005889
170.1477341.11540.134687
180.026790.20230.420217
19-0.021734-0.16410.435122
200.0597740.45130.326749
210.0573450.43290.333344
220.0544040.41070.341402
23-0.068656-0.51830.303114
24-0.160069-1.20850.115923
250.0103310.0780.469051
260.0638950.48240.315686
27-0.060369-0.45580.325142
280.1833641.38440.085821
29-0.006615-0.04990.480172
30-0.089796-0.67790.250275
31-0.066809-0.50440.307962
32-0.05904-0.44570.328736
33-0.058932-0.44490.32903
34-0.108014-0.81550.209095
35-0.023262-0.17560.430607
36-0.065183-0.49210.312263
37-0.068865-0.51990.302567
38-0.098824-0.74610.229335
390.0505180.38140.352161
400.0453420.34230.366682
41-0.043489-0.32830.37193
42-0.019035-0.14370.443117
43-0.013831-0.10440.458601
44-0.007519-0.05680.477466
450.0380450.28720.387489
460.0319920.24150.405005
470.0923220.6970.244313
480.0133590.10090.460009

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.085651 & -0.6466 & 0.260228 \tabularnewline
2 & -0.046009 & -0.3474 & 0.364801 \tabularnewline
3 & -0.075952 & -0.5734 & 0.284307 \tabularnewline
4 & -0.163313 & -1.233 & 0.111321 \tabularnewline
5 & 0.039358 & 0.2971 & 0.383716 \tabularnewline
6 & -0.25321 & -1.9117 & 0.030473 \tabularnewline
7 & 0.11031 & 0.8328 & 0.204211 \tabularnewline
8 & -0.29866 & -2.2548 & 0.014001 \tabularnewline
9 & -0.01619 & -0.1222 & 0.451573 \tabularnewline
10 & -0.26968 & -2.036 & 0.023202 \tabularnewline
11 & 0.018427 & 0.1391 & 0.444922 \tabularnewline
12 & 0.505564 & 3.8169 & 0.000168 \tabularnewline
13 & 0.163914 & 1.2375 & 0.110483 \tabularnewline
14 & -0.161131 & -1.2165 & 0.114402 \tabularnewline
15 & 0.018803 & 0.142 & 0.443808 \tabularnewline
16 & -0.344694 & -2.6024 & 0.005889 \tabularnewline
17 & 0.147734 & 1.1154 & 0.134687 \tabularnewline
18 & 0.02679 & 0.2023 & 0.420217 \tabularnewline
19 & -0.021734 & -0.1641 & 0.435122 \tabularnewline
20 & 0.059774 & 0.4513 & 0.326749 \tabularnewline
21 & 0.057345 & 0.4329 & 0.333344 \tabularnewline
22 & 0.054404 & 0.4107 & 0.341402 \tabularnewline
23 & -0.068656 & -0.5183 & 0.303114 \tabularnewline
24 & -0.160069 & -1.2085 & 0.115923 \tabularnewline
25 & 0.010331 & 0.078 & 0.469051 \tabularnewline
26 & 0.063895 & 0.4824 & 0.315686 \tabularnewline
27 & -0.060369 & -0.4558 & 0.325142 \tabularnewline
28 & 0.183364 & 1.3844 & 0.085821 \tabularnewline
29 & -0.006615 & -0.0499 & 0.480172 \tabularnewline
30 & -0.089796 & -0.6779 & 0.250275 \tabularnewline
31 & -0.066809 & -0.5044 & 0.307962 \tabularnewline
32 & -0.05904 & -0.4457 & 0.328736 \tabularnewline
33 & -0.058932 & -0.4449 & 0.32903 \tabularnewline
34 & -0.108014 & -0.8155 & 0.209095 \tabularnewline
35 & -0.023262 & -0.1756 & 0.430607 \tabularnewline
36 & -0.065183 & -0.4921 & 0.312263 \tabularnewline
37 & -0.068865 & -0.5199 & 0.302567 \tabularnewline
38 & -0.098824 & -0.7461 & 0.229335 \tabularnewline
39 & 0.050518 & 0.3814 & 0.352161 \tabularnewline
40 & 0.045342 & 0.3423 & 0.366682 \tabularnewline
41 & -0.043489 & -0.3283 & 0.37193 \tabularnewline
42 & -0.019035 & -0.1437 & 0.443117 \tabularnewline
43 & -0.013831 & -0.1044 & 0.458601 \tabularnewline
44 & -0.007519 & -0.0568 & 0.477466 \tabularnewline
45 & 0.038045 & 0.2872 & 0.387489 \tabularnewline
46 & 0.031992 & 0.2415 & 0.405005 \tabularnewline
47 & 0.092322 & 0.697 & 0.244313 \tabularnewline
48 & 0.013359 & 0.1009 & 0.460009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111478&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]-0.085651[/C][C]-0.6466[/C][C]0.260228[/C][/ROW]
[ROW][C]2[/C][C]-0.046009[/C][C]-0.3474[/C][C]0.364801[/C][/ROW]
[ROW][C]3[/C][C]-0.075952[/C][C]-0.5734[/C][C]0.284307[/C][/ROW]
[ROW][C]4[/C][C]-0.163313[/C][C]-1.233[/C][C]0.111321[/C][/ROW]
[ROW][C]5[/C][C]0.039358[/C][C]0.2971[/C][C]0.383716[/C][/ROW]
[ROW][C]6[/C][C]-0.25321[/C][C]-1.9117[/C][C]0.030473[/C][/ROW]
[ROW][C]7[/C][C]0.11031[/C][C]0.8328[/C][C]0.204211[/C][/ROW]
[ROW][C]8[/C][C]-0.29866[/C][C]-2.2548[/C][C]0.014001[/C][/ROW]
[ROW][C]9[/C][C]-0.01619[/C][C]-0.1222[/C][C]0.451573[/C][/ROW]
[ROW][C]10[/C][C]-0.26968[/C][C]-2.036[/C][C]0.023202[/C][/ROW]
[ROW][C]11[/C][C]0.018427[/C][C]0.1391[/C][C]0.444922[/C][/ROW]
[ROW][C]12[/C][C]0.505564[/C][C]3.8169[/C][C]0.000168[/C][/ROW]
[ROW][C]13[/C][C]0.163914[/C][C]1.2375[/C][C]0.110483[/C][/ROW]
[ROW][C]14[/C][C]-0.161131[/C][C]-1.2165[/C][C]0.114402[/C][/ROW]
[ROW][C]15[/C][C]0.018803[/C][C]0.142[/C][C]0.443808[/C][/ROW]
[ROW][C]16[/C][C]-0.344694[/C][C]-2.6024[/C][C]0.005889[/C][/ROW]
[ROW][C]17[/C][C]0.147734[/C][C]1.1154[/C][C]0.134687[/C][/ROW]
[ROW][C]18[/C][C]0.02679[/C][C]0.2023[/C][C]0.420217[/C][/ROW]
[ROW][C]19[/C][C]-0.021734[/C][C]-0.1641[/C][C]0.435122[/C][/ROW]
[ROW][C]20[/C][C]0.059774[/C][C]0.4513[/C][C]0.326749[/C][/ROW]
[ROW][C]21[/C][C]0.057345[/C][C]0.4329[/C][C]0.333344[/C][/ROW]
[ROW][C]22[/C][C]0.054404[/C][C]0.4107[/C][C]0.341402[/C][/ROW]
[ROW][C]23[/C][C]-0.068656[/C][C]-0.5183[/C][C]0.303114[/C][/ROW]
[ROW][C]24[/C][C]-0.160069[/C][C]-1.2085[/C][C]0.115923[/C][/ROW]
[ROW][C]25[/C][C]0.010331[/C][C]0.078[/C][C]0.469051[/C][/ROW]
[ROW][C]26[/C][C]0.063895[/C][C]0.4824[/C][C]0.315686[/C][/ROW]
[ROW][C]27[/C][C]-0.060369[/C][C]-0.4558[/C][C]0.325142[/C][/ROW]
[ROW][C]28[/C][C]0.183364[/C][C]1.3844[/C][C]0.085821[/C][/ROW]
[ROW][C]29[/C][C]-0.006615[/C][C]-0.0499[/C][C]0.480172[/C][/ROW]
[ROW][C]30[/C][C]-0.089796[/C][C]-0.6779[/C][C]0.250275[/C][/ROW]
[ROW][C]31[/C][C]-0.066809[/C][C]-0.5044[/C][C]0.307962[/C][/ROW]
[ROW][C]32[/C][C]-0.05904[/C][C]-0.4457[/C][C]0.328736[/C][/ROW]
[ROW][C]33[/C][C]-0.058932[/C][C]-0.4449[/C][C]0.32903[/C][/ROW]
[ROW][C]34[/C][C]-0.108014[/C][C]-0.8155[/C][C]0.209095[/C][/ROW]
[ROW][C]35[/C][C]-0.023262[/C][C]-0.1756[/C][C]0.430607[/C][/ROW]
[ROW][C]36[/C][C]-0.065183[/C][C]-0.4921[/C][C]0.312263[/C][/ROW]
[ROW][C]37[/C][C]-0.068865[/C][C]-0.5199[/C][C]0.302567[/C][/ROW]
[ROW][C]38[/C][C]-0.098824[/C][C]-0.7461[/C][C]0.229335[/C][/ROW]
[ROW][C]39[/C][C]0.050518[/C][C]0.3814[/C][C]0.352161[/C][/ROW]
[ROW][C]40[/C][C]0.045342[/C][C]0.3423[/C][C]0.366682[/C][/ROW]
[ROW][C]41[/C][C]-0.043489[/C][C]-0.3283[/C][C]0.37193[/C][/ROW]
[ROW][C]42[/C][C]-0.019035[/C][C]-0.1437[/C][C]0.443117[/C][/ROW]
[ROW][C]43[/C][C]-0.013831[/C][C]-0.1044[/C][C]0.458601[/C][/ROW]
[ROW][C]44[/C][C]-0.007519[/C][C]-0.0568[/C][C]0.477466[/C][/ROW]
[ROW][C]45[/C][C]0.038045[/C][C]0.2872[/C][C]0.387489[/C][/ROW]
[ROW][C]46[/C][C]0.031992[/C][C]0.2415[/C][C]0.405005[/C][/ROW]
[ROW][C]47[/C][C]0.092322[/C][C]0.697[/C][C]0.244313[/C][/ROW]
[ROW][C]48[/C][C]0.013359[/C][C]0.1009[/C][C]0.460009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111478&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111478&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
1-0.085651-0.64660.260228
2-0.046009-0.34740.364801
3-0.075952-0.57340.284307
4-0.163313-1.2330.111321
50.0393580.29710.383716
6-0.25321-1.91170.030473
70.110310.83280.204211
8-0.29866-2.25480.014001
9-0.01619-0.12220.451573
10-0.26968-2.0360.023202
110.0184270.13910.444922
120.5055643.81690.000168
130.1639141.23750.110483
14-0.161131-1.21650.114402
150.0188030.1420.443808
16-0.344694-2.60240.005889
170.1477341.11540.134687
180.026790.20230.420217
19-0.021734-0.16410.435122
200.0597740.45130.326749
210.0573450.43290.333344
220.0544040.41070.341402
23-0.068656-0.51830.303114
24-0.160069-1.20850.115923
250.0103310.0780.469051
260.0638950.48240.315686
27-0.060369-0.45580.325142
280.1833641.38440.085821
29-0.006615-0.04990.480172
30-0.089796-0.67790.250275
31-0.066809-0.50440.307962
32-0.05904-0.44570.328736
33-0.058932-0.44490.32903
34-0.108014-0.81550.209095
35-0.023262-0.17560.430607
36-0.065183-0.49210.312263
37-0.068865-0.51990.302567
38-0.098824-0.74610.229335
390.0505180.38140.352161
400.0453420.34230.366682
41-0.043489-0.32830.37193
42-0.019035-0.14370.443117
43-0.013831-0.10440.458601
44-0.007519-0.05680.477466
450.0380450.28720.387489
460.0319920.24150.405005
470.0923220.6970.244313
480.0133590.10090.460009



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')