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Description of Statistical Computation

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 computationSat, 23 Dec 2017 18:42:48 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/23/t1514051013bevhbfdiy4lzr7g.htm/, Retrieved Wed, 15 May 2024 05:36:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310874, Retrieved Wed, 15 May 2024 05:36:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [autocorrelation d...] [2017-12-23 17:42:48] [2c7049bbcc29bc93573a73f5c62450a0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
56,5
69,4
81
68
69,1
66,3
46,4
71,6
75,8
78,7
73,2
53,3
60,3
71,4
73,1
73,4
66,4
69,9
53,9
72,7
77,3
78,6
73,4
63,7
73,8
81,5
93,7
92,9
79,4
81,8
69,3
82,9
90,1
95
83,3
64,6
64,7
85,5
88,5
84,8
81,2
74,3
68,1
82,3
91,6
95,2
76,5
64
62,2
70
93,3
91,1
73,9
90,9
70,7
85,5
91,3
88,3
79,8
68,5
64,8
72,5
84,1
89,1
82,9
100,1
63,8
87,6
96,5
121,3
121,8
111,5
81,9
85,7
106,8
94,7
104,8
110,5
82
102,7
103,8
111,1
100,4
92,5
88,9
97,3
116,2
105,9
107,1
115,4
90,9
123,6
103,5
111
106,9
83,5
113,8
104,2
126,9
125,8
112,9
119,9
105,1
123,4
113,3
114,4
93
73,9
64,9
83,5
90,5
92,1
85,8
99,1
76,7
92,5
106,8
108,5
95,3
67,2
59,4
74,3
111,2
112,4
102,6
127,5
88,4
118,5
112,9
111,1
111
70,6
84,9
102,4
115,6
105,3
118
111,5
72,8
118,7
112,9
107,4
105,2
85,7
88,2
78,8
111,5
99,4
108,7
112,4
79,1
94,7
99,3
111,6
96,1
67,2
66,8
78,9
87,8
97
103,5
103
85
91,7
96,6
105,8
87,5
74
80,7
82,2
92,8
97,1
90,4
90,3
78,1
84,5
95,8
101,4
82,1
72
99
86,6
114,9
101,2
104
119,4
106,2
106,8
113,4
110,8
97,9
83,4
85
89
117,9
112,5
100,3
111,5
66,3
120,4
131,3
118,6
120
100,1
83
99,2
123,7
104
113,9
122,2
98,7
114,8

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310874&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=310874&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310874&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.374173-5.27840
2-0.059371-0.83750.20165
30.0608630.85860.195804
4-0.104387-1.47260.071224
5-0.028768-0.40580.342654
60.0790221.11470.133152
70.0358020.50510.30704
8-0.067831-0.95690.169897
90.0202090.28510.387936
10-0.006833-0.09640.461652
110.1596682.25240.012694
12-0.35391-4.99251e-06
130.086851.22520.110979
140.0638650.90090.184357
15-0.018875-0.26630.395157
16-0.043533-0.61410.269924
170.0690450.9740.16562
18-0.024054-0.33930.367361
19-0.087597-1.23570.109011
200.1649462.32690.01049
210.02510.35410.361826
22-0.160762-2.26780.012207
230.0943671.33120.092321
24-0.117142-1.65250.050006
250.0282790.39890.345189
260.0618280.87220.192079
270.0729931.02970.152202
28-0.002358-0.03330.48675
29-0.059974-0.8460.199275
30-0.04491-0.63350.263557
310.0236920.33420.369282
320.0245930.34690.364508
33-0.029573-0.41720.338497
340.0352820.49770.309618
35-0.032134-0.45330.32541
36-0.034556-0.48750.313229
370.0714581.0080.157329
380.0144150.20330.419537
39-0.134631-1.89920.029492
400.0746691.05330.146732
41-0.001415-0.020.49205
42-0.027625-0.38970.348587
430.0665690.93910.174417
44-0.036579-0.5160.303209
45-0.081153-1.14480.126833
460.1370461.93330.027311
470.0096720.13640.445806
480.0272840.38490.350365

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.374173 & -5.2784 & 0 \tabularnewline
2 & -0.059371 & -0.8375 & 0.20165 \tabularnewline
3 & 0.060863 & 0.8586 & 0.195804 \tabularnewline
4 & -0.104387 & -1.4726 & 0.071224 \tabularnewline
5 & -0.028768 & -0.4058 & 0.342654 \tabularnewline
6 & 0.079022 & 1.1147 & 0.133152 \tabularnewline
7 & 0.035802 & 0.5051 & 0.30704 \tabularnewline
8 & -0.067831 & -0.9569 & 0.169897 \tabularnewline
9 & 0.020209 & 0.2851 & 0.387936 \tabularnewline
10 & -0.006833 & -0.0964 & 0.461652 \tabularnewline
11 & 0.159668 & 2.2524 & 0.012694 \tabularnewline
12 & -0.35391 & -4.9925 & 1e-06 \tabularnewline
13 & 0.08685 & 1.2252 & 0.110979 \tabularnewline
14 & 0.063865 & 0.9009 & 0.184357 \tabularnewline
15 & -0.018875 & -0.2663 & 0.395157 \tabularnewline
16 & -0.043533 & -0.6141 & 0.269924 \tabularnewline
17 & 0.069045 & 0.974 & 0.16562 \tabularnewline
18 & -0.024054 & -0.3393 & 0.367361 \tabularnewline
19 & -0.087597 & -1.2357 & 0.109011 \tabularnewline
20 & 0.164946 & 2.3269 & 0.01049 \tabularnewline
21 & 0.0251 & 0.3541 & 0.361826 \tabularnewline
22 & -0.160762 & -2.2678 & 0.012207 \tabularnewline
23 & 0.094367 & 1.3312 & 0.092321 \tabularnewline
24 & -0.117142 & -1.6525 & 0.050006 \tabularnewline
25 & 0.028279 & 0.3989 & 0.345189 \tabularnewline
26 & 0.061828 & 0.8722 & 0.192079 \tabularnewline
27 & 0.072993 & 1.0297 & 0.152202 \tabularnewline
28 & -0.002358 & -0.0333 & 0.48675 \tabularnewline
29 & -0.059974 & -0.846 & 0.199275 \tabularnewline
30 & -0.04491 & -0.6335 & 0.263557 \tabularnewline
31 & 0.023692 & 0.3342 & 0.369282 \tabularnewline
32 & 0.024593 & 0.3469 & 0.364508 \tabularnewline
33 & -0.029573 & -0.4172 & 0.338497 \tabularnewline
34 & 0.035282 & 0.4977 & 0.309618 \tabularnewline
35 & -0.032134 & -0.4533 & 0.32541 \tabularnewline
36 & -0.034556 & -0.4875 & 0.313229 \tabularnewline
37 & 0.071458 & 1.008 & 0.157329 \tabularnewline
38 & 0.014415 & 0.2033 & 0.419537 \tabularnewline
39 & -0.134631 & -1.8992 & 0.029492 \tabularnewline
40 & 0.074669 & 1.0533 & 0.146732 \tabularnewline
41 & -0.001415 & -0.02 & 0.49205 \tabularnewline
42 & -0.027625 & -0.3897 & 0.348587 \tabularnewline
43 & 0.066569 & 0.9391 & 0.174417 \tabularnewline
44 & -0.036579 & -0.516 & 0.303209 \tabularnewline
45 & -0.081153 & -1.1448 & 0.126833 \tabularnewline
46 & 0.137046 & 1.9333 & 0.027311 \tabularnewline
47 & 0.009672 & 0.1364 & 0.445806 \tabularnewline
48 & 0.027284 & 0.3849 & 0.350365 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310874&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]-0.374173[/C][C]-5.2784[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.059371[/C][C]-0.8375[/C][C]0.20165[/C][/ROW]
[ROW][C]3[/C][C]0.060863[/C][C]0.8586[/C][C]0.195804[/C][/ROW]
[ROW][C]4[/C][C]-0.104387[/C][C]-1.4726[/C][C]0.071224[/C][/ROW]
[ROW][C]5[/C][C]-0.028768[/C][C]-0.4058[/C][C]0.342654[/C][/ROW]
[ROW][C]6[/C][C]0.079022[/C][C]1.1147[/C][C]0.133152[/C][/ROW]
[ROW][C]7[/C][C]0.035802[/C][C]0.5051[/C][C]0.30704[/C][/ROW]
[ROW][C]8[/C][C]-0.067831[/C][C]-0.9569[/C][C]0.169897[/C][/ROW]
[ROW][C]9[/C][C]0.020209[/C][C]0.2851[/C][C]0.387936[/C][/ROW]
[ROW][C]10[/C][C]-0.006833[/C][C]-0.0964[/C][C]0.461652[/C][/ROW]
[ROW][C]11[/C][C]0.159668[/C][C]2.2524[/C][C]0.012694[/C][/ROW]
[ROW][C]12[/C][C]-0.35391[/C][C]-4.9925[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]0.08685[/C][C]1.2252[/C][C]0.110979[/C][/ROW]
[ROW][C]14[/C][C]0.063865[/C][C]0.9009[/C][C]0.184357[/C][/ROW]
[ROW][C]15[/C][C]-0.018875[/C][C]-0.2663[/C][C]0.395157[/C][/ROW]
[ROW][C]16[/C][C]-0.043533[/C][C]-0.6141[/C][C]0.269924[/C][/ROW]
[ROW][C]17[/C][C]0.069045[/C][C]0.974[/C][C]0.16562[/C][/ROW]
[ROW][C]18[/C][C]-0.024054[/C][C]-0.3393[/C][C]0.367361[/C][/ROW]
[ROW][C]19[/C][C]-0.087597[/C][C]-1.2357[/C][C]0.109011[/C][/ROW]
[ROW][C]20[/C][C]0.164946[/C][C]2.3269[/C][C]0.01049[/C][/ROW]
[ROW][C]21[/C][C]0.0251[/C][C]0.3541[/C][C]0.361826[/C][/ROW]
[ROW][C]22[/C][C]-0.160762[/C][C]-2.2678[/C][C]0.012207[/C][/ROW]
[ROW][C]23[/C][C]0.094367[/C][C]1.3312[/C][C]0.092321[/C][/ROW]
[ROW][C]24[/C][C]-0.117142[/C][C]-1.6525[/C][C]0.050006[/C][/ROW]
[ROW][C]25[/C][C]0.028279[/C][C]0.3989[/C][C]0.345189[/C][/ROW]
[ROW][C]26[/C][C]0.061828[/C][C]0.8722[/C][C]0.192079[/C][/ROW]
[ROW][C]27[/C][C]0.072993[/C][C]1.0297[/C][C]0.152202[/C][/ROW]
[ROW][C]28[/C][C]-0.002358[/C][C]-0.0333[/C][C]0.48675[/C][/ROW]
[ROW][C]29[/C][C]-0.059974[/C][C]-0.846[/C][C]0.199275[/C][/ROW]
[ROW][C]30[/C][C]-0.04491[/C][C]-0.6335[/C][C]0.263557[/C][/ROW]
[ROW][C]31[/C][C]0.023692[/C][C]0.3342[/C][C]0.369282[/C][/ROW]
[ROW][C]32[/C][C]0.024593[/C][C]0.3469[/C][C]0.364508[/C][/ROW]
[ROW][C]33[/C][C]-0.029573[/C][C]-0.4172[/C][C]0.338497[/C][/ROW]
[ROW][C]34[/C][C]0.035282[/C][C]0.4977[/C][C]0.309618[/C][/ROW]
[ROW][C]35[/C][C]-0.032134[/C][C]-0.4533[/C][C]0.32541[/C][/ROW]
[ROW][C]36[/C][C]-0.034556[/C][C]-0.4875[/C][C]0.313229[/C][/ROW]
[ROW][C]37[/C][C]0.071458[/C][C]1.008[/C][C]0.157329[/C][/ROW]
[ROW][C]38[/C][C]0.014415[/C][C]0.2033[/C][C]0.419537[/C][/ROW]
[ROW][C]39[/C][C]-0.134631[/C][C]-1.8992[/C][C]0.029492[/C][/ROW]
[ROW][C]40[/C][C]0.074669[/C][C]1.0533[/C][C]0.146732[/C][/ROW]
[ROW][C]41[/C][C]-0.001415[/C][C]-0.02[/C][C]0.49205[/C][/ROW]
[ROW][C]42[/C][C]-0.027625[/C][C]-0.3897[/C][C]0.348587[/C][/ROW]
[ROW][C]43[/C][C]0.066569[/C][C]0.9391[/C][C]0.174417[/C][/ROW]
[ROW][C]44[/C][C]-0.036579[/C][C]-0.516[/C][C]0.303209[/C][/ROW]
[ROW][C]45[/C][C]-0.081153[/C][C]-1.1448[/C][C]0.126833[/C][/ROW]
[ROW][C]46[/C][C]0.137046[/C][C]1.9333[/C][C]0.027311[/C][/ROW]
[ROW][C]47[/C][C]0.009672[/C][C]0.1364[/C][C]0.445806[/C][/ROW]
[ROW][C]48[/C][C]0.027284[/C][C]0.3849[/C][C]0.350365[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310874&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310874&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.374173-5.27840
2-0.059371-0.83750.20165
30.0608630.85860.195804
4-0.104387-1.47260.071224
5-0.028768-0.40580.342654
60.0790221.11470.133152
70.0358020.50510.30704
8-0.067831-0.95690.169897
90.0202090.28510.387936
10-0.006833-0.09640.461652
110.1596682.25240.012694
12-0.35391-4.99251e-06
130.086851.22520.110979
140.0638650.90090.184357
15-0.018875-0.26630.395157
16-0.043533-0.61410.269924
170.0690450.9740.16562
18-0.024054-0.33930.367361
19-0.087597-1.23570.109011
200.1649462.32690.01049
210.02510.35410.361826
22-0.160762-2.26780.012207
230.0943671.33120.092321
24-0.117142-1.65250.050006
250.0282790.39890.345189
260.0618280.87220.192079
270.0729931.02970.152202
28-0.002358-0.03330.48675
29-0.059974-0.8460.199275
30-0.04491-0.63350.263557
310.0236920.33420.369282
320.0245930.34690.364508
33-0.029573-0.41720.338497
340.0352820.49770.309618
35-0.032134-0.45330.32541
36-0.034556-0.48750.313229
370.0714581.0080.157329
380.0144150.20330.419537
39-0.134631-1.89920.029492
400.0746691.05330.146732
41-0.001415-0.020.49205
42-0.027625-0.38970.348587
430.0665690.93910.174417
44-0.036579-0.5160.303209
45-0.081153-1.14480.126833
460.1370461.93330.027311
470.0096720.13640.445806
480.0272840.38490.350365






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.374173-5.27840
2-0.231834-3.27040.000633
3-0.065434-0.92310.178545
4-0.14248-2.00990.022895
5-0.154245-2.17590.015371
6-0.036988-0.52180.301203
70.0482340.68040.248514
8-0.032904-0.46420.321518
9-0.0276-0.38930.34872
10-0.020254-0.28570.387698
110.2165783.05520.001279
12-0.268627-3.78941e-04
13-0.197065-2.780.002979
14-0.082754-1.16740.122224
150.0186710.26340.396264
16-0.162195-2.2880.011593
17-0.116645-1.64550.050724
18-0.015444-0.21790.413878
19-0.046599-0.65740.255854
200.0469070.66170.254463
210.1269951.79150.037367
22-0.081864-1.15480.124773
230.1162471.63990.051306
24-0.254434-3.58920.000209
25-0.158954-2.24230.013022
26-0.083883-1.18330.119048
270.1284721.81230.035722
280.0145310.2050.418897
29-0.042447-0.59880.274999
30-0.06596-0.93050.176625
31-0.017811-0.25130.400937
320.0654070.92270.178647
330.1000381.41120.079873
34-0.125213-1.76630.039435
350.00850.11990.452341
36-0.241465-3.40630.000398
37-0.051033-0.71990.236213
38-0.024801-0.34990.363406
390.0064820.09140.46362
40-0.031732-0.44760.327454
41-0.083177-1.17340.121028
42-0.093308-1.31630.094797
430.0338170.47710.316924
440.0466540.65810.255607
45-0.014575-0.20560.418655
46-0.083461-1.17740.120228
470.0569690.80360.21128
48-0.052098-0.73490.231623

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.374173 & -5.2784 & 0 \tabularnewline
2 & -0.231834 & -3.2704 & 0.000633 \tabularnewline
3 & -0.065434 & -0.9231 & 0.178545 \tabularnewline
4 & -0.14248 & -2.0099 & 0.022895 \tabularnewline
5 & -0.154245 & -2.1759 & 0.015371 \tabularnewline
6 & -0.036988 & -0.5218 & 0.301203 \tabularnewline
7 & 0.048234 & 0.6804 & 0.248514 \tabularnewline
8 & -0.032904 & -0.4642 & 0.321518 \tabularnewline
9 & -0.0276 & -0.3893 & 0.34872 \tabularnewline
10 & -0.020254 & -0.2857 & 0.387698 \tabularnewline
11 & 0.216578 & 3.0552 & 0.001279 \tabularnewline
12 & -0.268627 & -3.7894 & 1e-04 \tabularnewline
13 & -0.197065 & -2.78 & 0.002979 \tabularnewline
14 & -0.082754 & -1.1674 & 0.122224 \tabularnewline
15 & 0.018671 & 0.2634 & 0.396264 \tabularnewline
16 & -0.162195 & -2.288 & 0.011593 \tabularnewline
17 & -0.116645 & -1.6455 & 0.050724 \tabularnewline
18 & -0.015444 & -0.2179 & 0.413878 \tabularnewline
19 & -0.046599 & -0.6574 & 0.255854 \tabularnewline
20 & 0.046907 & 0.6617 & 0.254463 \tabularnewline
21 & 0.126995 & 1.7915 & 0.037367 \tabularnewline
22 & -0.081864 & -1.1548 & 0.124773 \tabularnewline
23 & 0.116247 & 1.6399 & 0.051306 \tabularnewline
24 & -0.254434 & -3.5892 & 0.000209 \tabularnewline
25 & -0.158954 & -2.2423 & 0.013022 \tabularnewline
26 & -0.083883 & -1.1833 & 0.119048 \tabularnewline
27 & 0.128472 & 1.8123 & 0.035722 \tabularnewline
28 & 0.014531 & 0.205 & 0.418897 \tabularnewline
29 & -0.042447 & -0.5988 & 0.274999 \tabularnewline
30 & -0.06596 & -0.9305 & 0.176625 \tabularnewline
31 & -0.017811 & -0.2513 & 0.400937 \tabularnewline
32 & 0.065407 & 0.9227 & 0.178647 \tabularnewline
33 & 0.100038 & 1.4112 & 0.079873 \tabularnewline
34 & -0.125213 & -1.7663 & 0.039435 \tabularnewline
35 & 0.0085 & 0.1199 & 0.452341 \tabularnewline
36 & -0.241465 & -3.4063 & 0.000398 \tabularnewline
37 & -0.051033 & -0.7199 & 0.236213 \tabularnewline
38 & -0.024801 & -0.3499 & 0.363406 \tabularnewline
39 & 0.006482 & 0.0914 & 0.46362 \tabularnewline
40 & -0.031732 & -0.4476 & 0.327454 \tabularnewline
41 & -0.083177 & -1.1734 & 0.121028 \tabularnewline
42 & -0.093308 & -1.3163 & 0.094797 \tabularnewline
43 & 0.033817 & 0.4771 & 0.316924 \tabularnewline
44 & 0.046654 & 0.6581 & 0.255607 \tabularnewline
45 & -0.014575 & -0.2056 & 0.418655 \tabularnewline
46 & -0.083461 & -1.1774 & 0.120228 \tabularnewline
47 & 0.056969 & 0.8036 & 0.21128 \tabularnewline
48 & -0.052098 & -0.7349 & 0.231623 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310874&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]-0.374173[/C][C]-5.2784[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.231834[/C][C]-3.2704[/C][C]0.000633[/C][/ROW]
[ROW][C]3[/C][C]-0.065434[/C][C]-0.9231[/C][C]0.178545[/C][/ROW]
[ROW][C]4[/C][C]-0.14248[/C][C]-2.0099[/C][C]0.022895[/C][/ROW]
[ROW][C]5[/C][C]-0.154245[/C][C]-2.1759[/C][C]0.015371[/C][/ROW]
[ROW][C]6[/C][C]-0.036988[/C][C]-0.5218[/C][C]0.301203[/C][/ROW]
[ROW][C]7[/C][C]0.048234[/C][C]0.6804[/C][C]0.248514[/C][/ROW]
[ROW][C]8[/C][C]-0.032904[/C][C]-0.4642[/C][C]0.321518[/C][/ROW]
[ROW][C]9[/C][C]-0.0276[/C][C]-0.3893[/C][C]0.34872[/C][/ROW]
[ROW][C]10[/C][C]-0.020254[/C][C]-0.2857[/C][C]0.387698[/C][/ROW]
[ROW][C]11[/C][C]0.216578[/C][C]3.0552[/C][C]0.001279[/C][/ROW]
[ROW][C]12[/C][C]-0.268627[/C][C]-3.7894[/C][C]1e-04[/C][/ROW]
[ROW][C]13[/C][C]-0.197065[/C][C]-2.78[/C][C]0.002979[/C][/ROW]
[ROW][C]14[/C][C]-0.082754[/C][C]-1.1674[/C][C]0.122224[/C][/ROW]
[ROW][C]15[/C][C]0.018671[/C][C]0.2634[/C][C]0.396264[/C][/ROW]
[ROW][C]16[/C][C]-0.162195[/C][C]-2.288[/C][C]0.011593[/C][/ROW]
[ROW][C]17[/C][C]-0.116645[/C][C]-1.6455[/C][C]0.050724[/C][/ROW]
[ROW][C]18[/C][C]-0.015444[/C][C]-0.2179[/C][C]0.413878[/C][/ROW]
[ROW][C]19[/C][C]-0.046599[/C][C]-0.6574[/C][C]0.255854[/C][/ROW]
[ROW][C]20[/C][C]0.046907[/C][C]0.6617[/C][C]0.254463[/C][/ROW]
[ROW][C]21[/C][C]0.126995[/C][C]1.7915[/C][C]0.037367[/C][/ROW]
[ROW][C]22[/C][C]-0.081864[/C][C]-1.1548[/C][C]0.124773[/C][/ROW]
[ROW][C]23[/C][C]0.116247[/C][C]1.6399[/C][C]0.051306[/C][/ROW]
[ROW][C]24[/C][C]-0.254434[/C][C]-3.5892[/C][C]0.000209[/C][/ROW]
[ROW][C]25[/C][C]-0.158954[/C][C]-2.2423[/C][C]0.013022[/C][/ROW]
[ROW][C]26[/C][C]-0.083883[/C][C]-1.1833[/C][C]0.119048[/C][/ROW]
[ROW][C]27[/C][C]0.128472[/C][C]1.8123[/C][C]0.035722[/C][/ROW]
[ROW][C]28[/C][C]0.014531[/C][C]0.205[/C][C]0.418897[/C][/ROW]
[ROW][C]29[/C][C]-0.042447[/C][C]-0.5988[/C][C]0.274999[/C][/ROW]
[ROW][C]30[/C][C]-0.06596[/C][C]-0.9305[/C][C]0.176625[/C][/ROW]
[ROW][C]31[/C][C]-0.017811[/C][C]-0.2513[/C][C]0.400937[/C][/ROW]
[ROW][C]32[/C][C]0.065407[/C][C]0.9227[/C][C]0.178647[/C][/ROW]
[ROW][C]33[/C][C]0.100038[/C][C]1.4112[/C][C]0.079873[/C][/ROW]
[ROW][C]34[/C][C]-0.125213[/C][C]-1.7663[/C][C]0.039435[/C][/ROW]
[ROW][C]35[/C][C]0.0085[/C][C]0.1199[/C][C]0.452341[/C][/ROW]
[ROW][C]36[/C][C]-0.241465[/C][C]-3.4063[/C][C]0.000398[/C][/ROW]
[ROW][C]37[/C][C]-0.051033[/C][C]-0.7199[/C][C]0.236213[/C][/ROW]
[ROW][C]38[/C][C]-0.024801[/C][C]-0.3499[/C][C]0.363406[/C][/ROW]
[ROW][C]39[/C][C]0.006482[/C][C]0.0914[/C][C]0.46362[/C][/ROW]
[ROW][C]40[/C][C]-0.031732[/C][C]-0.4476[/C][C]0.327454[/C][/ROW]
[ROW][C]41[/C][C]-0.083177[/C][C]-1.1734[/C][C]0.121028[/C][/ROW]
[ROW][C]42[/C][C]-0.093308[/C][C]-1.3163[/C][C]0.094797[/C][/ROW]
[ROW][C]43[/C][C]0.033817[/C][C]0.4771[/C][C]0.316924[/C][/ROW]
[ROW][C]44[/C][C]0.046654[/C][C]0.6581[/C][C]0.255607[/C][/ROW]
[ROW][C]45[/C][C]-0.014575[/C][C]-0.2056[/C][C]0.418655[/C][/ROW]
[ROW][C]46[/C][C]-0.083461[/C][C]-1.1774[/C][C]0.120228[/C][/ROW]
[ROW][C]47[/C][C]0.056969[/C][C]0.8036[/C][C]0.21128[/C][/ROW]
[ROW][C]48[/C][C]-0.052098[/C][C]-0.7349[/C][C]0.231623[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310874&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310874&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.374173-5.27840
2-0.231834-3.27040.000633
3-0.065434-0.92310.178545
4-0.14248-2.00990.022895
5-0.154245-2.17590.015371
6-0.036988-0.52180.301203
70.0482340.68040.248514
8-0.032904-0.46420.321518
9-0.0276-0.38930.34872
10-0.020254-0.28570.387698
110.2165783.05520.001279
12-0.268627-3.78941e-04
13-0.197065-2.780.002979
14-0.082754-1.16740.122224
150.0186710.26340.396264
16-0.162195-2.2880.011593
17-0.116645-1.64550.050724
18-0.015444-0.21790.413878
19-0.046599-0.65740.255854
200.0469070.66170.254463
210.1269951.79150.037367
22-0.081864-1.15480.124773
230.1162471.63990.051306
24-0.254434-3.58920.000209
25-0.158954-2.24230.013022
26-0.083883-1.18330.119048
270.1284721.81230.035722
280.0145310.2050.418897
29-0.042447-0.59880.274999
30-0.06596-0.93050.176625
31-0.017811-0.25130.400937
320.0654070.92270.178647
330.1000381.41120.079873
34-0.125213-1.76630.039435
350.00850.11990.452341
36-0.241465-3.40630.000398
37-0.051033-0.71990.236213
38-0.024801-0.34990.363406
390.0064820.09140.46362
40-0.031732-0.44760.327454
41-0.083177-1.17340.121028
42-0.093308-1.31630.094797
430.0338170.47710.316924
440.0466540.65810.255607
45-0.014575-0.20560.418655
46-0.083461-1.17740.120228
470.0569690.80360.21128
48-0.052098-0.73490.231623


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ; par6 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = -0.3 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
x <- na.omit(x)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,'ACF(k)',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,'PACF(k)',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')