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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, 09 Dec 2016 13:56:30 +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/2016/Dec/09/t1481288313a0yepw9g5207wr0.htm/, Retrieved Fri, 01 Nov 2024 03:48:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298516, Retrieved Fri, 01 Nov 2024 03:48:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsF1 competition
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Partial Autocorre...] [2016-12-09 12:56:30] [00d6a26c230b6c589ee3bbc701d55499] [Current]
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Dataseries X:
3840
3140
4580
4740
3920
4900
3400
3440
2600
2220
2190
2550
2720
3720
4710
5070
6030
5280
4420
3940
2750
2980
2690
2650
4000
4150
6050
6280
5520
4800
4610
3530
2790
2750
2470
2610
3680
3820
4460
4760
3290
3610
3650
3130
2850
2720
2740
2760
3330
3850
5430
5180
4770
5360
4950
3720
3330
3000
2760
3040
3260
3780
4670
4320
4080
4210
3350
3390
2630
2350
2330
2230
2830
3230
4240
3750
4160
3960
3000
2890
2300
2320
2270
1970
2920
3310
4370
3990
3970
3850
3510
2840
2130
2280
1960
1740
2370
1980
2680
3510
3350
3290
3150
2490
2490
2930
3590
2040
2480
2760
3400
3470
3130
3670
3080
2430




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298516&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]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298516&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298516&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0676370.72530.234863
20.1363771.46250.073168
30.0984961.05630.146534
4-0.320766-3.43980.000406
5-0.236922-2.54070.006198
6-0.410349-4.40051.2e-05
7-0.311628-3.34180.000562
8-0.160694-1.72330.043765
90.0336610.3610.359392
100.1113841.19450.117378
110.3191853.42290.00043
120.4871765.22440
130.1342531.43970.076334
140.1804481.93510.027718
15-0.019568-0.20980.417081
16-0.25428-2.72680.003698
17-0.167206-1.79310.037794
18-0.419927-4.50328e-06
19-0.214178-2.29680.01172
20-0.078982-0.8470.199381
21-0.046613-0.49990.30906
220.131951.4150.079885
230.2548892.73340.00363
240.3702623.97066.3e-05
250.1607521.72390.043709
260.141711.51970.065669
27-0.010064-0.10790.457124
28-0.118033-1.26580.104078
29-0.172262-1.84730.033637
30-0.350625-3.760.000134
31-0.161404-1.73090.043079
32-0.076596-0.82140.206558
33-0.084531-0.90650.183285
340.1896762.0340.022124
350.1366371.46530.072788
360.2895323.10490.001198
370.2222352.38320.009401
380.0694290.74450.229033
390.038460.41240.340394
40-0.083264-0.89290.186885
41-0.183941-1.97260.025473
42-0.326315-3.49930.000332
43-0.085599-0.9180.180283
44-0.171163-1.83550.034507
45-0.040257-0.43170.333382
460.1391121.49180.069244
470.0951471.02030.154854
480.2957253.17130.000973

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.067637 & 0.7253 & 0.234863 \tabularnewline
2 & 0.136377 & 1.4625 & 0.073168 \tabularnewline
3 & 0.098496 & 1.0563 & 0.146534 \tabularnewline
4 & -0.320766 & -3.4398 & 0.000406 \tabularnewline
5 & -0.236922 & -2.5407 & 0.006198 \tabularnewline
6 & -0.410349 & -4.4005 & 1.2e-05 \tabularnewline
7 & -0.311628 & -3.3418 & 0.000562 \tabularnewline
8 & -0.160694 & -1.7233 & 0.043765 \tabularnewline
9 & 0.033661 & 0.361 & 0.359392 \tabularnewline
10 & 0.111384 & 1.1945 & 0.117378 \tabularnewline
11 & 0.319185 & 3.4229 & 0.00043 \tabularnewline
12 & 0.487176 & 5.2244 & 0 \tabularnewline
13 & 0.134253 & 1.4397 & 0.076334 \tabularnewline
14 & 0.180448 & 1.9351 & 0.027718 \tabularnewline
15 & -0.019568 & -0.2098 & 0.417081 \tabularnewline
16 & -0.25428 & -2.7268 & 0.003698 \tabularnewline
17 & -0.167206 & -1.7931 & 0.037794 \tabularnewline
18 & -0.419927 & -4.5032 & 8e-06 \tabularnewline
19 & -0.214178 & -2.2968 & 0.01172 \tabularnewline
20 & -0.078982 & -0.847 & 0.199381 \tabularnewline
21 & -0.046613 & -0.4999 & 0.30906 \tabularnewline
22 & 0.13195 & 1.415 & 0.079885 \tabularnewline
23 & 0.254889 & 2.7334 & 0.00363 \tabularnewline
24 & 0.370262 & 3.9706 & 6.3e-05 \tabularnewline
25 & 0.160752 & 1.7239 & 0.043709 \tabularnewline
26 & 0.14171 & 1.5197 & 0.065669 \tabularnewline
27 & -0.010064 & -0.1079 & 0.457124 \tabularnewline
28 & -0.118033 & -1.2658 & 0.104078 \tabularnewline
29 & -0.172262 & -1.8473 & 0.033637 \tabularnewline
30 & -0.350625 & -3.76 & 0.000134 \tabularnewline
31 & -0.161404 & -1.7309 & 0.043079 \tabularnewline
32 & -0.076596 & -0.8214 & 0.206558 \tabularnewline
33 & -0.084531 & -0.9065 & 0.183285 \tabularnewline
34 & 0.189676 & 2.034 & 0.022124 \tabularnewline
35 & 0.136637 & 1.4653 & 0.072788 \tabularnewline
36 & 0.289532 & 3.1049 & 0.001198 \tabularnewline
37 & 0.222235 & 2.3832 & 0.009401 \tabularnewline
38 & 0.069429 & 0.7445 & 0.229033 \tabularnewline
39 & 0.03846 & 0.4124 & 0.340394 \tabularnewline
40 & -0.083264 & -0.8929 & 0.186885 \tabularnewline
41 & -0.183941 & -1.9726 & 0.025473 \tabularnewline
42 & -0.326315 & -3.4993 & 0.000332 \tabularnewline
43 & -0.085599 & -0.918 & 0.180283 \tabularnewline
44 & -0.171163 & -1.8355 & 0.034507 \tabularnewline
45 & -0.040257 & -0.4317 & 0.333382 \tabularnewline
46 & 0.139112 & 1.4918 & 0.069244 \tabularnewline
47 & 0.095147 & 1.0203 & 0.154854 \tabularnewline
48 & 0.295725 & 3.1713 & 0.000973 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298516&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]0.067637[/C][C]0.7253[/C][C]0.234863[/C][/ROW]
[ROW][C]2[/C][C]0.136377[/C][C]1.4625[/C][C]0.073168[/C][/ROW]
[ROW][C]3[/C][C]0.098496[/C][C]1.0563[/C][C]0.146534[/C][/ROW]
[ROW][C]4[/C][C]-0.320766[/C][C]-3.4398[/C][C]0.000406[/C][/ROW]
[ROW][C]5[/C][C]-0.236922[/C][C]-2.5407[/C][C]0.006198[/C][/ROW]
[ROW][C]6[/C][C]-0.410349[/C][C]-4.4005[/C][C]1.2e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.311628[/C][C]-3.3418[/C][C]0.000562[/C][/ROW]
[ROW][C]8[/C][C]-0.160694[/C][C]-1.7233[/C][C]0.043765[/C][/ROW]
[ROW][C]9[/C][C]0.033661[/C][C]0.361[/C][C]0.359392[/C][/ROW]
[ROW][C]10[/C][C]0.111384[/C][C]1.1945[/C][C]0.117378[/C][/ROW]
[ROW][C]11[/C][C]0.319185[/C][C]3.4229[/C][C]0.00043[/C][/ROW]
[ROW][C]12[/C][C]0.487176[/C][C]5.2244[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.134253[/C][C]1.4397[/C][C]0.076334[/C][/ROW]
[ROW][C]14[/C][C]0.180448[/C][C]1.9351[/C][C]0.027718[/C][/ROW]
[ROW][C]15[/C][C]-0.019568[/C][C]-0.2098[/C][C]0.417081[/C][/ROW]
[ROW][C]16[/C][C]-0.25428[/C][C]-2.7268[/C][C]0.003698[/C][/ROW]
[ROW][C]17[/C][C]-0.167206[/C][C]-1.7931[/C][C]0.037794[/C][/ROW]
[ROW][C]18[/C][C]-0.419927[/C][C]-4.5032[/C][C]8e-06[/C][/ROW]
[ROW][C]19[/C][C]-0.214178[/C][C]-2.2968[/C][C]0.01172[/C][/ROW]
[ROW][C]20[/C][C]-0.078982[/C][C]-0.847[/C][C]0.199381[/C][/ROW]
[ROW][C]21[/C][C]-0.046613[/C][C]-0.4999[/C][C]0.30906[/C][/ROW]
[ROW][C]22[/C][C]0.13195[/C][C]1.415[/C][C]0.079885[/C][/ROW]
[ROW][C]23[/C][C]0.254889[/C][C]2.7334[/C][C]0.00363[/C][/ROW]
[ROW][C]24[/C][C]0.370262[/C][C]3.9706[/C][C]6.3e-05[/C][/ROW]
[ROW][C]25[/C][C]0.160752[/C][C]1.7239[/C][C]0.043709[/C][/ROW]
[ROW][C]26[/C][C]0.14171[/C][C]1.5197[/C][C]0.065669[/C][/ROW]
[ROW][C]27[/C][C]-0.010064[/C][C]-0.1079[/C][C]0.457124[/C][/ROW]
[ROW][C]28[/C][C]-0.118033[/C][C]-1.2658[/C][C]0.104078[/C][/ROW]
[ROW][C]29[/C][C]-0.172262[/C][C]-1.8473[/C][C]0.033637[/C][/ROW]
[ROW][C]30[/C][C]-0.350625[/C][C]-3.76[/C][C]0.000134[/C][/ROW]
[ROW][C]31[/C][C]-0.161404[/C][C]-1.7309[/C][C]0.043079[/C][/ROW]
[ROW][C]32[/C][C]-0.076596[/C][C]-0.8214[/C][C]0.206558[/C][/ROW]
[ROW][C]33[/C][C]-0.084531[/C][C]-0.9065[/C][C]0.183285[/C][/ROW]
[ROW][C]34[/C][C]0.189676[/C][C]2.034[/C][C]0.022124[/C][/ROW]
[ROW][C]35[/C][C]0.136637[/C][C]1.4653[/C][C]0.072788[/C][/ROW]
[ROW][C]36[/C][C]0.289532[/C][C]3.1049[/C][C]0.001198[/C][/ROW]
[ROW][C]37[/C][C]0.222235[/C][C]2.3832[/C][C]0.009401[/C][/ROW]
[ROW][C]38[/C][C]0.069429[/C][C]0.7445[/C][C]0.229033[/C][/ROW]
[ROW][C]39[/C][C]0.03846[/C][C]0.4124[/C][C]0.340394[/C][/ROW]
[ROW][C]40[/C][C]-0.083264[/C][C]-0.8929[/C][C]0.186885[/C][/ROW]
[ROW][C]41[/C][C]-0.183941[/C][C]-1.9726[/C][C]0.025473[/C][/ROW]
[ROW][C]42[/C][C]-0.326315[/C][C]-3.4993[/C][C]0.000332[/C][/ROW]
[ROW][C]43[/C][C]-0.085599[/C][C]-0.918[/C][C]0.180283[/C][/ROW]
[ROW][C]44[/C][C]-0.171163[/C][C]-1.8355[/C][C]0.034507[/C][/ROW]
[ROW][C]45[/C][C]-0.040257[/C][C]-0.4317[/C][C]0.333382[/C][/ROW]
[ROW][C]46[/C][C]0.139112[/C][C]1.4918[/C][C]0.069244[/C][/ROW]
[ROW][C]47[/C][C]0.095147[/C][C]1.0203[/C][C]0.154854[/C][/ROW]
[ROW][C]48[/C][C]0.295725[/C][C]3.1713[/C][C]0.000973[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298516&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298516&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
10.0676370.72530.234863
20.1363771.46250.073168
30.0984961.05630.146534
4-0.320766-3.43980.000406
5-0.236922-2.54070.006198
6-0.410349-4.40051.2e-05
7-0.311628-3.34180.000562
8-0.160694-1.72330.043765
90.0336610.3610.359392
100.1113841.19450.117378
110.3191853.42290.00043
120.4871765.22440
130.1342531.43970.076334
140.1804481.93510.027718
15-0.019568-0.20980.417081
16-0.25428-2.72680.003698
17-0.167206-1.79310.037794
18-0.419927-4.50328e-06
19-0.214178-2.29680.01172
20-0.078982-0.8470.199381
21-0.046613-0.49990.30906
220.131951.4150.079885
230.2548892.73340.00363
240.3702623.97066.3e-05
250.1607521.72390.043709
260.141711.51970.065669
27-0.010064-0.10790.457124
28-0.118033-1.26580.104078
29-0.172262-1.84730.033637
30-0.350625-3.760.000134
31-0.161404-1.73090.043079
32-0.076596-0.82140.206558
33-0.084531-0.90650.183285
340.1896762.0340.022124
350.1366371.46530.072788
360.2895323.10490.001198
370.2222352.38320.009401
380.0694290.74450.229033
390.038460.41240.340394
40-0.083264-0.89290.186885
41-0.183941-1.97260.025473
42-0.326315-3.49930.000332
43-0.085599-0.9180.180283
44-0.171163-1.83550.034507
45-0.040257-0.43170.333382
460.1391121.49180.069244
470.0951471.02030.154854
480.2957253.17130.000973







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0676370.72530.234863
20.1324081.41990.079168
30.0833740.89410.186572
4-0.358831-3.8489.8e-05
5-0.258286-2.76980.003271
6-0.380733-4.08294.1e-05
7-0.280754-3.01070.001602
8-0.26996-2.8950.002269
9-0.085161-0.91320.181512
10-0.198694-2.13080.01762
11-0.046681-0.50060.308806
120.2376172.54820.006074
13-0.026144-0.28040.389851
14-0.044141-0.47340.318427
15-0.065699-0.70450.241261
16-0.080766-0.86610.194114
170.0543960.58330.280406
18-0.095427-1.02330.154148
19-0.028015-0.30040.382195
20-0.020195-0.21660.414464
21-0.078781-0.84480.19998
22-0.192245-2.06160.02075
23-0.186602-2.00110.023869
240.0059270.06360.474717
25-0.063894-0.68520.247302
26-0.089804-0.9630.168774
27-0.085751-0.91960.179858
280.0086850.09310.462977
29-0.003834-0.04110.483636
30-0.086681-0.92950.177276
31-0.093253-10.159698
320.0250210.26830.394468
33-0.043365-0.4650.321393
340.0735860.78910.215832
35-0.105499-1.13130.130131
36-0.010812-0.11590.453948
370.0509710.54660.292856
380.0306350.32850.371555
39-0.01749-0.18760.425778
400.0439880.47170.319013
410.0612870.65720.256175
42-0.070958-0.76090.224126
430.0718290.77030.221355
44-0.030493-0.3270.372131
450.0245370.26310.396459
460.0228190.24470.403559
470.0199560.2140.415463
480.0048070.05160.479487

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.067637 & 0.7253 & 0.234863 \tabularnewline
2 & 0.132408 & 1.4199 & 0.079168 \tabularnewline
3 & 0.083374 & 0.8941 & 0.186572 \tabularnewline
4 & -0.358831 & -3.848 & 9.8e-05 \tabularnewline
5 & -0.258286 & -2.7698 & 0.003271 \tabularnewline
6 & -0.380733 & -4.0829 & 4.1e-05 \tabularnewline
7 & -0.280754 & -3.0107 & 0.001602 \tabularnewline
8 & -0.26996 & -2.895 & 0.002269 \tabularnewline
9 & -0.085161 & -0.9132 & 0.181512 \tabularnewline
10 & -0.198694 & -2.1308 & 0.01762 \tabularnewline
11 & -0.046681 & -0.5006 & 0.308806 \tabularnewline
12 & 0.237617 & 2.5482 & 0.006074 \tabularnewline
13 & -0.026144 & -0.2804 & 0.389851 \tabularnewline
14 & -0.044141 & -0.4734 & 0.318427 \tabularnewline
15 & -0.065699 & -0.7045 & 0.241261 \tabularnewline
16 & -0.080766 & -0.8661 & 0.194114 \tabularnewline
17 & 0.054396 & 0.5833 & 0.280406 \tabularnewline
18 & -0.095427 & -1.0233 & 0.154148 \tabularnewline
19 & -0.028015 & -0.3004 & 0.382195 \tabularnewline
20 & -0.020195 & -0.2166 & 0.414464 \tabularnewline
21 & -0.078781 & -0.8448 & 0.19998 \tabularnewline
22 & -0.192245 & -2.0616 & 0.02075 \tabularnewline
23 & -0.186602 & -2.0011 & 0.023869 \tabularnewline
24 & 0.005927 & 0.0636 & 0.474717 \tabularnewline
25 & -0.063894 & -0.6852 & 0.247302 \tabularnewline
26 & -0.089804 & -0.963 & 0.168774 \tabularnewline
27 & -0.085751 & -0.9196 & 0.179858 \tabularnewline
28 & 0.008685 & 0.0931 & 0.462977 \tabularnewline
29 & -0.003834 & -0.0411 & 0.483636 \tabularnewline
30 & -0.086681 & -0.9295 & 0.177276 \tabularnewline
31 & -0.093253 & -1 & 0.159698 \tabularnewline
32 & 0.025021 & 0.2683 & 0.394468 \tabularnewline
33 & -0.043365 & -0.465 & 0.321393 \tabularnewline
34 & 0.073586 & 0.7891 & 0.215832 \tabularnewline
35 & -0.105499 & -1.1313 & 0.130131 \tabularnewline
36 & -0.010812 & -0.1159 & 0.453948 \tabularnewline
37 & 0.050971 & 0.5466 & 0.292856 \tabularnewline
38 & 0.030635 & 0.3285 & 0.371555 \tabularnewline
39 & -0.01749 & -0.1876 & 0.425778 \tabularnewline
40 & 0.043988 & 0.4717 & 0.319013 \tabularnewline
41 & 0.061287 & 0.6572 & 0.256175 \tabularnewline
42 & -0.070958 & -0.7609 & 0.224126 \tabularnewline
43 & 0.071829 & 0.7703 & 0.221355 \tabularnewline
44 & -0.030493 & -0.327 & 0.372131 \tabularnewline
45 & 0.024537 & 0.2631 & 0.396459 \tabularnewline
46 & 0.022819 & 0.2447 & 0.403559 \tabularnewline
47 & 0.019956 & 0.214 & 0.415463 \tabularnewline
48 & 0.004807 & 0.0516 & 0.479487 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298516&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]0.067637[/C][C]0.7253[/C][C]0.234863[/C][/ROW]
[ROW][C]2[/C][C]0.132408[/C][C]1.4199[/C][C]0.079168[/C][/ROW]
[ROW][C]3[/C][C]0.083374[/C][C]0.8941[/C][C]0.186572[/C][/ROW]
[ROW][C]4[/C][C]-0.358831[/C][C]-3.848[/C][C]9.8e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.258286[/C][C]-2.7698[/C][C]0.003271[/C][/ROW]
[ROW][C]6[/C][C]-0.380733[/C][C]-4.0829[/C][C]4.1e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.280754[/C][C]-3.0107[/C][C]0.001602[/C][/ROW]
[ROW][C]8[/C][C]-0.26996[/C][C]-2.895[/C][C]0.002269[/C][/ROW]
[ROW][C]9[/C][C]-0.085161[/C][C]-0.9132[/C][C]0.181512[/C][/ROW]
[ROW][C]10[/C][C]-0.198694[/C][C]-2.1308[/C][C]0.01762[/C][/ROW]
[ROW][C]11[/C][C]-0.046681[/C][C]-0.5006[/C][C]0.308806[/C][/ROW]
[ROW][C]12[/C][C]0.237617[/C][C]2.5482[/C][C]0.006074[/C][/ROW]
[ROW][C]13[/C][C]-0.026144[/C][C]-0.2804[/C][C]0.389851[/C][/ROW]
[ROW][C]14[/C][C]-0.044141[/C][C]-0.4734[/C][C]0.318427[/C][/ROW]
[ROW][C]15[/C][C]-0.065699[/C][C]-0.7045[/C][C]0.241261[/C][/ROW]
[ROW][C]16[/C][C]-0.080766[/C][C]-0.8661[/C][C]0.194114[/C][/ROW]
[ROW][C]17[/C][C]0.054396[/C][C]0.5833[/C][C]0.280406[/C][/ROW]
[ROW][C]18[/C][C]-0.095427[/C][C]-1.0233[/C][C]0.154148[/C][/ROW]
[ROW][C]19[/C][C]-0.028015[/C][C]-0.3004[/C][C]0.382195[/C][/ROW]
[ROW][C]20[/C][C]-0.020195[/C][C]-0.2166[/C][C]0.414464[/C][/ROW]
[ROW][C]21[/C][C]-0.078781[/C][C]-0.8448[/C][C]0.19998[/C][/ROW]
[ROW][C]22[/C][C]-0.192245[/C][C]-2.0616[/C][C]0.02075[/C][/ROW]
[ROW][C]23[/C][C]-0.186602[/C][C]-2.0011[/C][C]0.023869[/C][/ROW]
[ROW][C]24[/C][C]0.005927[/C][C]0.0636[/C][C]0.474717[/C][/ROW]
[ROW][C]25[/C][C]-0.063894[/C][C]-0.6852[/C][C]0.247302[/C][/ROW]
[ROW][C]26[/C][C]-0.089804[/C][C]-0.963[/C][C]0.168774[/C][/ROW]
[ROW][C]27[/C][C]-0.085751[/C][C]-0.9196[/C][C]0.179858[/C][/ROW]
[ROW][C]28[/C][C]0.008685[/C][C]0.0931[/C][C]0.462977[/C][/ROW]
[ROW][C]29[/C][C]-0.003834[/C][C]-0.0411[/C][C]0.483636[/C][/ROW]
[ROW][C]30[/C][C]-0.086681[/C][C]-0.9295[/C][C]0.177276[/C][/ROW]
[ROW][C]31[/C][C]-0.093253[/C][C]-1[/C][C]0.159698[/C][/ROW]
[ROW][C]32[/C][C]0.025021[/C][C]0.2683[/C][C]0.394468[/C][/ROW]
[ROW][C]33[/C][C]-0.043365[/C][C]-0.465[/C][C]0.321393[/C][/ROW]
[ROW][C]34[/C][C]0.073586[/C][C]0.7891[/C][C]0.215832[/C][/ROW]
[ROW][C]35[/C][C]-0.105499[/C][C]-1.1313[/C][C]0.130131[/C][/ROW]
[ROW][C]36[/C][C]-0.010812[/C][C]-0.1159[/C][C]0.453948[/C][/ROW]
[ROW][C]37[/C][C]0.050971[/C][C]0.5466[/C][C]0.292856[/C][/ROW]
[ROW][C]38[/C][C]0.030635[/C][C]0.3285[/C][C]0.371555[/C][/ROW]
[ROW][C]39[/C][C]-0.01749[/C][C]-0.1876[/C][C]0.425778[/C][/ROW]
[ROW][C]40[/C][C]0.043988[/C][C]0.4717[/C][C]0.319013[/C][/ROW]
[ROW][C]41[/C][C]0.061287[/C][C]0.6572[/C][C]0.256175[/C][/ROW]
[ROW][C]42[/C][C]-0.070958[/C][C]-0.7609[/C][C]0.224126[/C][/ROW]
[ROW][C]43[/C][C]0.071829[/C][C]0.7703[/C][C]0.221355[/C][/ROW]
[ROW][C]44[/C][C]-0.030493[/C][C]-0.327[/C][C]0.372131[/C][/ROW]
[ROW][C]45[/C][C]0.024537[/C][C]0.2631[/C][C]0.396459[/C][/ROW]
[ROW][C]46[/C][C]0.022819[/C][C]0.2447[/C][C]0.403559[/C][/ROW]
[ROW][C]47[/C][C]0.019956[/C][C]0.214[/C][C]0.415463[/C][/ROW]
[ROW][C]48[/C][C]0.004807[/C][C]0.0516[/C][C]0.479487[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298516&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298516&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
10.0676370.72530.234863
20.1324081.41990.079168
30.0833740.89410.186572
4-0.358831-3.8489.8e-05
5-0.258286-2.76980.003271
6-0.380733-4.08294.1e-05
7-0.280754-3.01070.001602
8-0.26996-2.8950.002269
9-0.085161-0.91320.181512
10-0.198694-2.13080.01762
11-0.046681-0.50060.308806
120.2376172.54820.006074
13-0.026144-0.28040.389851
14-0.044141-0.47340.318427
15-0.065699-0.70450.241261
16-0.080766-0.86610.194114
170.0543960.58330.280406
18-0.095427-1.02330.154148
19-0.028015-0.30040.382195
20-0.020195-0.21660.414464
21-0.078781-0.84480.19998
22-0.192245-2.06160.02075
23-0.186602-2.00110.023869
240.0059270.06360.474717
25-0.063894-0.68520.247302
26-0.089804-0.9630.168774
27-0.085751-0.91960.179858
280.0086850.09310.462977
29-0.003834-0.04110.483636
30-0.086681-0.92950.177276
31-0.093253-10.159698
320.0250210.26830.394468
33-0.043365-0.4650.321393
340.0735860.78910.215832
35-0.105499-1.13130.130131
36-0.010812-0.11590.453948
370.0509710.54660.292856
380.0306350.32850.371555
39-0.01749-0.18760.425778
400.0439880.47170.319013
410.0612870.65720.256175
42-0.070958-0.76090.224126
430.0718290.77030.221355
44-0.030493-0.3270.372131
450.0245370.26310.396459
460.0228190.24470.403559
470.0199560.2140.415463
480.0048070.05160.479487



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 (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')