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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, 30 Nov 2012 05:31:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/30/t1354271859s8u1ijfcgn2wywi.htm/, Retrieved Sat, 04 May 2024 00:31:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194904, Retrieved Sat, 04 May 2024 00:31:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65
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 09:09:37] [b98453cac15ba1066b407e146608df68]
- R  D    [(Partial) Autocorrelation Function] [Aantal werklozen ...] [2012-11-30 10:24:51] [3e2c7966ca4198d187b4c59e4eb5d004]
-   P         [(Partial) Autocorrelation Function] [Aantal werklozen ...] [2012-11-30 10:31:59] [7ac586d7aaad1f98cbd1d1bd98b37cf0] [Current]
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Dataseries X:
116
111
104
100
93
91
119
139
134
124
113
109
109
106
101
98
93
91
122
139
140
132
117
114
113
110
107
103
98
98
137
148
147
139
130
128
127
123
118
114
108
111
151
159
158
148
138
137
136
133
126
120
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107
99
103
131
137
135
124
118
121
121
118
113
107
100
102
130
136
133
120
112
109
110
106
102
98
92
92
120
127
124
114
108
106
111
110
104
100
96
98
122
134
133




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194904&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194904&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194904&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'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0438350.51870.302406
20.0971051.1490.126266
30.0545650.64560.259791
40.1002811.18650.118709
5-0.00956-0.11310.455051
60.0936421.1080.134884
70.1166991.38080.08477
80.0189960.22480.411247
90.1307791.54740.062012
10-0.018738-0.22170.412432
110.0741780.87770.19081
12-0.095324-1.12790.130649
13-0.055221-0.65340.257291
140.0181510.21480.415132
15-0.024154-0.28580.38773
16-0.144751-1.71270.044489
17-0.047721-0.56460.286608
18-0.121649-1.43940.076139
19-0.117107-1.38560.084032
20-0.050613-0.59890.275118
21-0.075195-0.88970.18757
22-0.047436-0.56130.287755
23-0.1278-1.51210.066375
24-0.15685-1.85590.032787
25-0.107724-1.27460.102279
26-0.026712-0.31610.376216
27-0.129587-1.53330.063729
28-0.010633-0.12580.450031
290.0484550.57330.28367
30-0.174211-2.06130.020563
310.0234770.27780.390794
320.068370.8090.209953
330.0298280.35290.362338
34-0.011331-0.13410.446771
350.1418031.67780.047805
36-0.044744-0.52940.298677
37-0.002349-0.02780.488935
380.0058670.06940.472378
390.0240160.28420.388353
400.0601220.71140.239018
410.0323360.38260.351298
420.0907191.07340.142469
430.1150691.36150.087769
44-0.039796-0.47090.31923
450.0085350.1010.45985
460.0325330.38490.350434
47-0.064965-0.76870.221692
480.038560.45630.324457

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.043835 & 0.5187 & 0.302406 \tabularnewline
2 & 0.097105 & 1.149 & 0.126266 \tabularnewline
3 & 0.054565 & 0.6456 & 0.259791 \tabularnewline
4 & 0.100281 & 1.1865 & 0.118709 \tabularnewline
5 & -0.00956 & -0.1131 & 0.455051 \tabularnewline
6 & 0.093642 & 1.108 & 0.134884 \tabularnewline
7 & 0.116699 & 1.3808 & 0.08477 \tabularnewline
8 & 0.018996 & 0.2248 & 0.411247 \tabularnewline
9 & 0.130779 & 1.5474 & 0.062012 \tabularnewline
10 & -0.018738 & -0.2217 & 0.412432 \tabularnewline
11 & 0.074178 & 0.8777 & 0.19081 \tabularnewline
12 & -0.095324 & -1.1279 & 0.130649 \tabularnewline
13 & -0.055221 & -0.6534 & 0.257291 \tabularnewline
14 & 0.018151 & 0.2148 & 0.415132 \tabularnewline
15 & -0.024154 & -0.2858 & 0.38773 \tabularnewline
16 & -0.144751 & -1.7127 & 0.044489 \tabularnewline
17 & -0.047721 & -0.5646 & 0.286608 \tabularnewline
18 & -0.121649 & -1.4394 & 0.076139 \tabularnewline
19 & -0.117107 & -1.3856 & 0.084032 \tabularnewline
20 & -0.050613 & -0.5989 & 0.275118 \tabularnewline
21 & -0.075195 & -0.8897 & 0.18757 \tabularnewline
22 & -0.047436 & -0.5613 & 0.287755 \tabularnewline
23 & -0.1278 & -1.5121 & 0.066375 \tabularnewline
24 & -0.15685 & -1.8559 & 0.032787 \tabularnewline
25 & -0.107724 & -1.2746 & 0.102279 \tabularnewline
26 & -0.026712 & -0.3161 & 0.376216 \tabularnewline
27 & -0.129587 & -1.5333 & 0.063729 \tabularnewline
28 & -0.010633 & -0.1258 & 0.450031 \tabularnewline
29 & 0.048455 & 0.5733 & 0.28367 \tabularnewline
30 & -0.174211 & -2.0613 & 0.020563 \tabularnewline
31 & 0.023477 & 0.2778 & 0.390794 \tabularnewline
32 & 0.06837 & 0.809 & 0.209953 \tabularnewline
33 & 0.029828 & 0.3529 & 0.362338 \tabularnewline
34 & -0.011331 & -0.1341 & 0.446771 \tabularnewline
35 & 0.141803 & 1.6778 & 0.047805 \tabularnewline
36 & -0.044744 & -0.5294 & 0.298677 \tabularnewline
37 & -0.002349 & -0.0278 & 0.488935 \tabularnewline
38 & 0.005867 & 0.0694 & 0.472378 \tabularnewline
39 & 0.024016 & 0.2842 & 0.388353 \tabularnewline
40 & 0.060122 & 0.7114 & 0.239018 \tabularnewline
41 & 0.032336 & 0.3826 & 0.351298 \tabularnewline
42 & 0.090719 & 1.0734 & 0.142469 \tabularnewline
43 & 0.115069 & 1.3615 & 0.087769 \tabularnewline
44 & -0.039796 & -0.4709 & 0.31923 \tabularnewline
45 & 0.008535 & 0.101 & 0.45985 \tabularnewline
46 & 0.032533 & 0.3849 & 0.350434 \tabularnewline
47 & -0.064965 & -0.7687 & 0.221692 \tabularnewline
48 & 0.03856 & 0.4563 & 0.324457 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194904&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]0.043835[/C][C]0.5187[/C][C]0.302406[/C][/ROW]
[ROW][C]2[/C][C]0.097105[/C][C]1.149[/C][C]0.126266[/C][/ROW]
[ROW][C]3[/C][C]0.054565[/C][C]0.6456[/C][C]0.259791[/C][/ROW]
[ROW][C]4[/C][C]0.100281[/C][C]1.1865[/C][C]0.118709[/C][/ROW]
[ROW][C]5[/C][C]-0.00956[/C][C]-0.1131[/C][C]0.455051[/C][/ROW]
[ROW][C]6[/C][C]0.093642[/C][C]1.108[/C][C]0.134884[/C][/ROW]
[ROW][C]7[/C][C]0.116699[/C][C]1.3808[/C][C]0.08477[/C][/ROW]
[ROW][C]8[/C][C]0.018996[/C][C]0.2248[/C][C]0.411247[/C][/ROW]
[ROW][C]9[/C][C]0.130779[/C][C]1.5474[/C][C]0.062012[/C][/ROW]
[ROW][C]10[/C][C]-0.018738[/C][C]-0.2217[/C][C]0.412432[/C][/ROW]
[ROW][C]11[/C][C]0.074178[/C][C]0.8777[/C][C]0.19081[/C][/ROW]
[ROW][C]12[/C][C]-0.095324[/C][C]-1.1279[/C][C]0.130649[/C][/ROW]
[ROW][C]13[/C][C]-0.055221[/C][C]-0.6534[/C][C]0.257291[/C][/ROW]
[ROW][C]14[/C][C]0.018151[/C][C]0.2148[/C][C]0.415132[/C][/ROW]
[ROW][C]15[/C][C]-0.024154[/C][C]-0.2858[/C][C]0.38773[/C][/ROW]
[ROW][C]16[/C][C]-0.144751[/C][C]-1.7127[/C][C]0.044489[/C][/ROW]
[ROW][C]17[/C][C]-0.047721[/C][C]-0.5646[/C][C]0.286608[/C][/ROW]
[ROW][C]18[/C][C]-0.121649[/C][C]-1.4394[/C][C]0.076139[/C][/ROW]
[ROW][C]19[/C][C]-0.117107[/C][C]-1.3856[/C][C]0.084032[/C][/ROW]
[ROW][C]20[/C][C]-0.050613[/C][C]-0.5989[/C][C]0.275118[/C][/ROW]
[ROW][C]21[/C][C]-0.075195[/C][C]-0.8897[/C][C]0.18757[/C][/ROW]
[ROW][C]22[/C][C]-0.047436[/C][C]-0.5613[/C][C]0.287755[/C][/ROW]
[ROW][C]23[/C][C]-0.1278[/C][C]-1.5121[/C][C]0.066375[/C][/ROW]
[ROW][C]24[/C][C]-0.15685[/C][C]-1.8559[/C][C]0.032787[/C][/ROW]
[ROW][C]25[/C][C]-0.107724[/C][C]-1.2746[/C][C]0.102279[/C][/ROW]
[ROW][C]26[/C][C]-0.026712[/C][C]-0.3161[/C][C]0.376216[/C][/ROW]
[ROW][C]27[/C][C]-0.129587[/C][C]-1.5333[/C][C]0.063729[/C][/ROW]
[ROW][C]28[/C][C]-0.010633[/C][C]-0.1258[/C][C]0.450031[/C][/ROW]
[ROW][C]29[/C][C]0.048455[/C][C]0.5733[/C][C]0.28367[/C][/ROW]
[ROW][C]30[/C][C]-0.174211[/C][C]-2.0613[/C][C]0.020563[/C][/ROW]
[ROW][C]31[/C][C]0.023477[/C][C]0.2778[/C][C]0.390794[/C][/ROW]
[ROW][C]32[/C][C]0.06837[/C][C]0.809[/C][C]0.209953[/C][/ROW]
[ROW][C]33[/C][C]0.029828[/C][C]0.3529[/C][C]0.362338[/C][/ROW]
[ROW][C]34[/C][C]-0.011331[/C][C]-0.1341[/C][C]0.446771[/C][/ROW]
[ROW][C]35[/C][C]0.141803[/C][C]1.6778[/C][C]0.047805[/C][/ROW]
[ROW][C]36[/C][C]-0.044744[/C][C]-0.5294[/C][C]0.298677[/C][/ROW]
[ROW][C]37[/C][C]-0.002349[/C][C]-0.0278[/C][C]0.488935[/C][/ROW]
[ROW][C]38[/C][C]0.005867[/C][C]0.0694[/C][C]0.472378[/C][/ROW]
[ROW][C]39[/C][C]0.024016[/C][C]0.2842[/C][C]0.388353[/C][/ROW]
[ROW][C]40[/C][C]0.060122[/C][C]0.7114[/C][C]0.239018[/C][/ROW]
[ROW][C]41[/C][C]0.032336[/C][C]0.3826[/C][C]0.351298[/C][/ROW]
[ROW][C]42[/C][C]0.090719[/C][C]1.0734[/C][C]0.142469[/C][/ROW]
[ROW][C]43[/C][C]0.115069[/C][C]1.3615[/C][C]0.087769[/C][/ROW]
[ROW][C]44[/C][C]-0.039796[/C][C]-0.4709[/C][C]0.31923[/C][/ROW]
[ROW][C]45[/C][C]0.008535[/C][C]0.101[/C][C]0.45985[/C][/ROW]
[ROW][C]46[/C][C]0.032533[/C][C]0.3849[/C][C]0.350434[/C][/ROW]
[ROW][C]47[/C][C]-0.064965[/C][C]-0.7687[/C][C]0.221692[/C][/ROW]
[ROW][C]48[/C][C]0.03856[/C][C]0.4563[/C][C]0.324457[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194904&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194904&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
10.0438350.51870.302406
20.0971051.1490.126266
30.0545650.64560.259791
40.1002811.18650.118709
5-0.00956-0.11310.455051
60.0936421.1080.134884
70.1166991.38080.08477
80.0189960.22480.411247
90.1307791.54740.062012
10-0.018738-0.22170.412432
110.0741780.87770.19081
12-0.095324-1.12790.130649
13-0.055221-0.65340.257291
140.0181510.21480.415132
15-0.024154-0.28580.38773
16-0.144751-1.71270.044489
17-0.047721-0.56460.286608
18-0.121649-1.43940.076139
19-0.117107-1.38560.084032
20-0.050613-0.59890.275118
21-0.075195-0.88970.18757
22-0.047436-0.56130.287755
23-0.1278-1.51210.066375
24-0.15685-1.85590.032787
25-0.107724-1.27460.102279
26-0.026712-0.31610.376216
27-0.129587-1.53330.063729
28-0.010633-0.12580.450031
290.0484550.57330.28367
30-0.174211-2.06130.020563
310.0234770.27780.390794
320.068370.8090.209953
330.0298280.35290.362338
34-0.011331-0.13410.446771
350.1418031.67780.047805
36-0.044744-0.52940.298677
37-0.002349-0.02780.488935
380.0058670.06940.472378
390.0240160.28420.388353
400.0601220.71140.239018
410.0323360.38260.351298
420.0907191.07340.142469
430.1150691.36150.087769
44-0.039796-0.47090.31923
450.0085350.1010.45985
460.0325330.38490.350434
47-0.064965-0.76870.221692
480.038560.45630.324457







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0438350.51870.302406
20.0953661.12840.130542
30.0470510.55670.289304
40.0883861.04580.148728
5-0.026005-0.30770.379384
60.0769170.91010.18217
70.1077241.27460.10228
8-0.009552-0.1130.455086
90.1120871.32620.093462
10-0.053853-0.63720.26252
110.04430.52420.300495
12-0.110426-1.30660.096749
13-0.098265-1.16270.123468
140.0374850.44350.329033
15-0.045402-0.53720.29599
16-0.148288-1.75460.040761
17-0.036248-0.42890.334331
18-0.129489-1.53210.063872
19-0.052598-0.62230.267363
20-0.013475-0.15940.436778
21-0.036287-0.42940.334164
220.0248820.29440.384441
23-0.086292-1.0210.154502
24-0.123546-1.46180.073016
25-0.029119-0.34450.365476
260.0251680.29780.38315
27-0.0423-0.50050.308754
280.0135170.15990.436582
290.0795710.94150.174037
30-0.151669-1.79460.03744
310.0508250.60140.274283
320.1128751.33560.091931
330.0518350.61330.27033
340.0163270.19320.42355
350.0938181.11010.134435
36-0.096338-1.13990.12814
37-0.048511-0.5740.283449
38-0.028019-0.33150.370371
39-0.022838-0.27020.393694
40-0.010383-0.12290.451201
41-0.023039-0.27260.392779
42-0.0229-0.2710.393413
430.0420140.49710.309943
44-0.089537-1.05940.145616
450.0201560.23850.405924
46-0.044315-0.52430.300435
47-0.081255-0.96140.168997
480.0195120.23090.408875

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.043835 & 0.5187 & 0.302406 \tabularnewline
2 & 0.095366 & 1.1284 & 0.130542 \tabularnewline
3 & 0.047051 & 0.5567 & 0.289304 \tabularnewline
4 & 0.088386 & 1.0458 & 0.148728 \tabularnewline
5 & -0.026005 & -0.3077 & 0.379384 \tabularnewline
6 & 0.076917 & 0.9101 & 0.18217 \tabularnewline
7 & 0.107724 & 1.2746 & 0.10228 \tabularnewline
8 & -0.009552 & -0.113 & 0.455086 \tabularnewline
9 & 0.112087 & 1.3262 & 0.093462 \tabularnewline
10 & -0.053853 & -0.6372 & 0.26252 \tabularnewline
11 & 0.0443 & 0.5242 & 0.300495 \tabularnewline
12 & -0.110426 & -1.3066 & 0.096749 \tabularnewline
13 & -0.098265 & -1.1627 & 0.123468 \tabularnewline
14 & 0.037485 & 0.4435 & 0.329033 \tabularnewline
15 & -0.045402 & -0.5372 & 0.29599 \tabularnewline
16 & -0.148288 & -1.7546 & 0.040761 \tabularnewline
17 & -0.036248 & -0.4289 & 0.334331 \tabularnewline
18 & -0.129489 & -1.5321 & 0.063872 \tabularnewline
19 & -0.052598 & -0.6223 & 0.267363 \tabularnewline
20 & -0.013475 & -0.1594 & 0.436778 \tabularnewline
21 & -0.036287 & -0.4294 & 0.334164 \tabularnewline
22 & 0.024882 & 0.2944 & 0.384441 \tabularnewline
23 & -0.086292 & -1.021 & 0.154502 \tabularnewline
24 & -0.123546 & -1.4618 & 0.073016 \tabularnewline
25 & -0.029119 & -0.3445 & 0.365476 \tabularnewline
26 & 0.025168 & 0.2978 & 0.38315 \tabularnewline
27 & -0.0423 & -0.5005 & 0.308754 \tabularnewline
28 & 0.013517 & 0.1599 & 0.436582 \tabularnewline
29 & 0.079571 & 0.9415 & 0.174037 \tabularnewline
30 & -0.151669 & -1.7946 & 0.03744 \tabularnewline
31 & 0.050825 & 0.6014 & 0.274283 \tabularnewline
32 & 0.112875 & 1.3356 & 0.091931 \tabularnewline
33 & 0.051835 & 0.6133 & 0.27033 \tabularnewline
34 & 0.016327 & 0.1932 & 0.42355 \tabularnewline
35 & 0.093818 & 1.1101 & 0.134435 \tabularnewline
36 & -0.096338 & -1.1399 & 0.12814 \tabularnewline
37 & -0.048511 & -0.574 & 0.283449 \tabularnewline
38 & -0.028019 & -0.3315 & 0.370371 \tabularnewline
39 & -0.022838 & -0.2702 & 0.393694 \tabularnewline
40 & -0.010383 & -0.1229 & 0.451201 \tabularnewline
41 & -0.023039 & -0.2726 & 0.392779 \tabularnewline
42 & -0.0229 & -0.271 & 0.393413 \tabularnewline
43 & 0.042014 & 0.4971 & 0.309943 \tabularnewline
44 & -0.089537 & -1.0594 & 0.145616 \tabularnewline
45 & 0.020156 & 0.2385 & 0.405924 \tabularnewline
46 & -0.044315 & -0.5243 & 0.300435 \tabularnewline
47 & -0.081255 & -0.9614 & 0.168997 \tabularnewline
48 & 0.019512 & 0.2309 & 0.408875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194904&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]0.043835[/C][C]0.5187[/C][C]0.302406[/C][/ROW]
[ROW][C]2[/C][C]0.095366[/C][C]1.1284[/C][C]0.130542[/C][/ROW]
[ROW][C]3[/C][C]0.047051[/C][C]0.5567[/C][C]0.289304[/C][/ROW]
[ROW][C]4[/C][C]0.088386[/C][C]1.0458[/C][C]0.148728[/C][/ROW]
[ROW][C]5[/C][C]-0.026005[/C][C]-0.3077[/C][C]0.379384[/C][/ROW]
[ROW][C]6[/C][C]0.076917[/C][C]0.9101[/C][C]0.18217[/C][/ROW]
[ROW][C]7[/C][C]0.107724[/C][C]1.2746[/C][C]0.10228[/C][/ROW]
[ROW][C]8[/C][C]-0.009552[/C][C]-0.113[/C][C]0.455086[/C][/ROW]
[ROW][C]9[/C][C]0.112087[/C][C]1.3262[/C][C]0.093462[/C][/ROW]
[ROW][C]10[/C][C]-0.053853[/C][C]-0.6372[/C][C]0.26252[/C][/ROW]
[ROW][C]11[/C][C]0.0443[/C][C]0.5242[/C][C]0.300495[/C][/ROW]
[ROW][C]12[/C][C]-0.110426[/C][C]-1.3066[/C][C]0.096749[/C][/ROW]
[ROW][C]13[/C][C]-0.098265[/C][C]-1.1627[/C][C]0.123468[/C][/ROW]
[ROW][C]14[/C][C]0.037485[/C][C]0.4435[/C][C]0.329033[/C][/ROW]
[ROW][C]15[/C][C]-0.045402[/C][C]-0.5372[/C][C]0.29599[/C][/ROW]
[ROW][C]16[/C][C]-0.148288[/C][C]-1.7546[/C][C]0.040761[/C][/ROW]
[ROW][C]17[/C][C]-0.036248[/C][C]-0.4289[/C][C]0.334331[/C][/ROW]
[ROW][C]18[/C][C]-0.129489[/C][C]-1.5321[/C][C]0.063872[/C][/ROW]
[ROW][C]19[/C][C]-0.052598[/C][C]-0.6223[/C][C]0.267363[/C][/ROW]
[ROW][C]20[/C][C]-0.013475[/C][C]-0.1594[/C][C]0.436778[/C][/ROW]
[ROW][C]21[/C][C]-0.036287[/C][C]-0.4294[/C][C]0.334164[/C][/ROW]
[ROW][C]22[/C][C]0.024882[/C][C]0.2944[/C][C]0.384441[/C][/ROW]
[ROW][C]23[/C][C]-0.086292[/C][C]-1.021[/C][C]0.154502[/C][/ROW]
[ROW][C]24[/C][C]-0.123546[/C][C]-1.4618[/C][C]0.073016[/C][/ROW]
[ROW][C]25[/C][C]-0.029119[/C][C]-0.3445[/C][C]0.365476[/C][/ROW]
[ROW][C]26[/C][C]0.025168[/C][C]0.2978[/C][C]0.38315[/C][/ROW]
[ROW][C]27[/C][C]-0.0423[/C][C]-0.5005[/C][C]0.308754[/C][/ROW]
[ROW][C]28[/C][C]0.013517[/C][C]0.1599[/C][C]0.436582[/C][/ROW]
[ROW][C]29[/C][C]0.079571[/C][C]0.9415[/C][C]0.174037[/C][/ROW]
[ROW][C]30[/C][C]-0.151669[/C][C]-1.7946[/C][C]0.03744[/C][/ROW]
[ROW][C]31[/C][C]0.050825[/C][C]0.6014[/C][C]0.274283[/C][/ROW]
[ROW][C]32[/C][C]0.112875[/C][C]1.3356[/C][C]0.091931[/C][/ROW]
[ROW][C]33[/C][C]0.051835[/C][C]0.6133[/C][C]0.27033[/C][/ROW]
[ROW][C]34[/C][C]0.016327[/C][C]0.1932[/C][C]0.42355[/C][/ROW]
[ROW][C]35[/C][C]0.093818[/C][C]1.1101[/C][C]0.134435[/C][/ROW]
[ROW][C]36[/C][C]-0.096338[/C][C]-1.1399[/C][C]0.12814[/C][/ROW]
[ROW][C]37[/C][C]-0.048511[/C][C]-0.574[/C][C]0.283449[/C][/ROW]
[ROW][C]38[/C][C]-0.028019[/C][C]-0.3315[/C][C]0.370371[/C][/ROW]
[ROW][C]39[/C][C]-0.022838[/C][C]-0.2702[/C][C]0.393694[/C][/ROW]
[ROW][C]40[/C][C]-0.010383[/C][C]-0.1229[/C][C]0.451201[/C][/ROW]
[ROW][C]41[/C][C]-0.023039[/C][C]-0.2726[/C][C]0.392779[/C][/ROW]
[ROW][C]42[/C][C]-0.0229[/C][C]-0.271[/C][C]0.393413[/C][/ROW]
[ROW][C]43[/C][C]0.042014[/C][C]0.4971[/C][C]0.309943[/C][/ROW]
[ROW][C]44[/C][C]-0.089537[/C][C]-1.0594[/C][C]0.145616[/C][/ROW]
[ROW][C]45[/C][C]0.020156[/C][C]0.2385[/C][C]0.405924[/C][/ROW]
[ROW][C]46[/C][C]-0.044315[/C][C]-0.5243[/C][C]0.300435[/C][/ROW]
[ROW][C]47[/C][C]-0.081255[/C][C]-0.9614[/C][C]0.168997[/C][/ROW]
[ROW][C]48[/C][C]0.019512[/C][C]0.2309[/C][C]0.408875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194904&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194904&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
10.0438350.51870.302406
20.0953661.12840.130542
30.0470510.55670.289304
40.0883861.04580.148728
5-0.026005-0.30770.379384
60.0769170.91010.18217
70.1077241.27460.10228
8-0.009552-0.1130.455086
90.1120871.32620.093462
10-0.053853-0.63720.26252
110.04430.52420.300495
12-0.110426-1.30660.096749
13-0.098265-1.16270.123468
140.0374850.44350.329033
15-0.045402-0.53720.29599
16-0.148288-1.75460.040761
17-0.036248-0.42890.334331
18-0.129489-1.53210.063872
19-0.052598-0.62230.267363
20-0.013475-0.15940.436778
21-0.036287-0.42940.334164
220.0248820.29440.384441
23-0.086292-1.0210.154502
24-0.123546-1.46180.073016
25-0.029119-0.34450.365476
260.0251680.29780.38315
27-0.0423-0.50050.308754
280.0135170.15990.436582
290.0795710.94150.174037
30-0.151669-1.79460.03744
310.0508250.60140.274283
320.1128751.33560.091931
330.0518350.61330.27033
340.0163270.19320.42355
350.0938181.11010.134435
36-0.096338-1.13990.12814
37-0.048511-0.5740.283449
38-0.028019-0.33150.370371
39-0.022838-0.27020.393694
40-0.010383-0.12290.451201
41-0.023039-0.27260.392779
42-0.0229-0.2710.393413
430.0420140.49710.309943
44-0.089537-1.05940.145616
450.0201560.23850.405924
46-0.044315-0.52430.300435
47-0.081255-0.96140.168997
480.0195120.23090.408875



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