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Author's title

Autocorrelation - Koers BEL 20 van Januari 2000 tot Januari 2009 - Claus We...

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 12 May 2009 07:45:35 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/May/12/t1242136024mua61axzqj0ag1j.htm/, Retrieved Mon, 29 Apr 2024 03:49:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=39747, Retrieved Mon, 29 Apr 2024 03:49:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelation -...] [2009-05-12 13:45:35] [fbcf875f1b36dfb87c2c6a55976f6e7b] [Current]
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Dataseries X:
3030,29
2803,47
2767,63
2882,6
2863,36
2897,06
3012,61
3142,95
3032,93
3045,78
3110,52
3013,24
2987,1
2995,55
2833,18
2848,96
2794,83
2845,26
2915,02
2892,63
2604,42
2641,65
2659,81
2638,53
2720,25
2745,88
2735,7
2811,7
2799,43
2555,28
2304,98
2214,95
2065,81
1940,49
2042
1995,37
1946,81
1765,9
1635,25
1833,42
1910,43
1959,67
1969,6
2061,41
2091,48
2120,88
2174,56
2196,72
2350,44
2440,25
2408,64
2472,81
2407,6
2452,62
2448,05
2497,84
2645,64
2756,76
2849,27
2921,44
2981,85
3080,58
3106,22
3119,31
3061,26
3097,31
3161,69
3257,16
3277,01
3295,32
3363,99
3494,17
3667,03
3813,06
3917,96
3895,51
3801,06
3570,12
3701,61
3862,27
3970,1
4138,52
4199,75
4290,89
4443,91
4502,64
4356,98
4591,27
4696,96
4621,4
4562,84
4202,52
4296,49
4435,23
4105,18
4116,68
3844,49
3720,98
3674,4
3857,62
3801,06
3504,37
3032,6
3047,03
2962,34
2197,82
2014,45
1862,83
1905,41




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=39747&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=39747&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=39747&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.97173610.14520
20.9323219.73370
30.8923719.31660
40.8482068.85550
50.8120868.47840
60.7706938.04630
70.7257227.57680
80.6871537.17410
90.6495116.78110
100.6083546.35140
110.5624645.87230
120.5111375.33640
130.4601714.80432e-06
140.4147134.32971.7e-05
150.3652243.81310.000114
160.3190923.33140.00059
170.2685382.80360.002992
180.2175752.27160.012539
190.1759831.83730.034444
200.1355291.4150.079965
210.0993381.03710.150987
220.0629720.65740.256139
230.0253120.26430.396038
24-0.004801-0.05010.480056
25-0.032588-0.34020.367169
26-0.062234-0.64970.258613
27-0.090216-0.94190.174168
28-0.117019-1.22170.112225
29-0.146452-1.5290.064581
30-0.176177-1.83930.034293
31-0.207366-2.1650.016286
32-0.238385-2.48880.007165
33-0.26398-2.7560.00343
34-0.284565-2.97090.001826
35-0.301183-3.14440.001072
36-0.314819-3.28680.000682
37-0.32934-3.43840.000415
38-0.344447-3.59610.000243
39-0.358627-3.74420.000145
40-0.373643-3.90098.3e-05
41-0.386768-4.0385e-05
42-0.397906-4.15433.3e-05
43-0.40805-4.26022.2e-05
44-0.414965-4.33241.6e-05
45-0.420775-4.3931.3e-05
46-0.422325-4.40921.2e-05
47-0.420312-4.38821.3e-05
48-0.415042-4.33321.6e-05

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.971736 & 10.1452 & 0 \tabularnewline
2 & 0.932321 & 9.7337 & 0 \tabularnewline
3 & 0.892371 & 9.3166 & 0 \tabularnewline
4 & 0.848206 & 8.8555 & 0 \tabularnewline
5 & 0.812086 & 8.4784 & 0 \tabularnewline
6 & 0.770693 & 8.0463 & 0 \tabularnewline
7 & 0.725722 & 7.5768 & 0 \tabularnewline
8 & 0.687153 & 7.1741 & 0 \tabularnewline
9 & 0.649511 & 6.7811 & 0 \tabularnewline
10 & 0.608354 & 6.3514 & 0 \tabularnewline
11 & 0.562464 & 5.8723 & 0 \tabularnewline
12 & 0.511137 & 5.3364 & 0 \tabularnewline
13 & 0.460171 & 4.8043 & 2e-06 \tabularnewline
14 & 0.414713 & 4.3297 & 1.7e-05 \tabularnewline
15 & 0.365224 & 3.8131 & 0.000114 \tabularnewline
16 & 0.319092 & 3.3314 & 0.00059 \tabularnewline
17 & 0.268538 & 2.8036 & 0.002992 \tabularnewline
18 & 0.217575 & 2.2716 & 0.012539 \tabularnewline
19 & 0.175983 & 1.8373 & 0.034444 \tabularnewline
20 & 0.135529 & 1.415 & 0.079965 \tabularnewline
21 & 0.099338 & 1.0371 & 0.150987 \tabularnewline
22 & 0.062972 & 0.6574 & 0.256139 \tabularnewline
23 & 0.025312 & 0.2643 & 0.396038 \tabularnewline
24 & -0.004801 & -0.0501 & 0.480056 \tabularnewline
25 & -0.032588 & -0.3402 & 0.367169 \tabularnewline
26 & -0.062234 & -0.6497 & 0.258613 \tabularnewline
27 & -0.090216 & -0.9419 & 0.174168 \tabularnewline
28 & -0.117019 & -1.2217 & 0.112225 \tabularnewline
29 & -0.146452 & -1.529 & 0.064581 \tabularnewline
30 & -0.176177 & -1.8393 & 0.034293 \tabularnewline
31 & -0.207366 & -2.165 & 0.016286 \tabularnewline
32 & -0.238385 & -2.4888 & 0.007165 \tabularnewline
33 & -0.26398 & -2.756 & 0.00343 \tabularnewline
34 & -0.284565 & -2.9709 & 0.001826 \tabularnewline
35 & -0.301183 & -3.1444 & 0.001072 \tabularnewline
36 & -0.314819 & -3.2868 & 0.000682 \tabularnewline
37 & -0.32934 & -3.4384 & 0.000415 \tabularnewline
38 & -0.344447 & -3.5961 & 0.000243 \tabularnewline
39 & -0.358627 & -3.7442 & 0.000145 \tabularnewline
40 & -0.373643 & -3.9009 & 8.3e-05 \tabularnewline
41 & -0.386768 & -4.038 & 5e-05 \tabularnewline
42 & -0.397906 & -4.1543 & 3.3e-05 \tabularnewline
43 & -0.40805 & -4.2602 & 2.2e-05 \tabularnewline
44 & -0.414965 & -4.3324 & 1.6e-05 \tabularnewline
45 & -0.420775 & -4.393 & 1.3e-05 \tabularnewline
46 & -0.422325 & -4.4092 & 1.2e-05 \tabularnewline
47 & -0.420312 & -4.3882 & 1.3e-05 \tabularnewline
48 & -0.415042 & -4.3332 & 1.6e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=39747&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]0.971736[/C][C]10.1452[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.932321[/C][C]9.7337[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.892371[/C][C]9.3166[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.848206[/C][C]8.8555[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.812086[/C][C]8.4784[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.770693[/C][C]8.0463[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.725722[/C][C]7.5768[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.687153[/C][C]7.1741[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.649511[/C][C]6.7811[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.608354[/C][C]6.3514[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.562464[/C][C]5.8723[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.511137[/C][C]5.3364[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.460171[/C][C]4.8043[/C][C]2e-06[/C][/ROW]
[ROW][C]14[/C][C]0.414713[/C][C]4.3297[/C][C]1.7e-05[/C][/ROW]
[ROW][C]15[/C][C]0.365224[/C][C]3.8131[/C][C]0.000114[/C][/ROW]
[ROW][C]16[/C][C]0.319092[/C][C]3.3314[/C][C]0.00059[/C][/ROW]
[ROW][C]17[/C][C]0.268538[/C][C]2.8036[/C][C]0.002992[/C][/ROW]
[ROW][C]18[/C][C]0.217575[/C][C]2.2716[/C][C]0.012539[/C][/ROW]
[ROW][C]19[/C][C]0.175983[/C][C]1.8373[/C][C]0.034444[/C][/ROW]
[ROW][C]20[/C][C]0.135529[/C][C]1.415[/C][C]0.079965[/C][/ROW]
[ROW][C]21[/C][C]0.099338[/C][C]1.0371[/C][C]0.150987[/C][/ROW]
[ROW][C]22[/C][C]0.062972[/C][C]0.6574[/C][C]0.256139[/C][/ROW]
[ROW][C]23[/C][C]0.025312[/C][C]0.2643[/C][C]0.396038[/C][/ROW]
[ROW][C]24[/C][C]-0.004801[/C][C]-0.0501[/C][C]0.480056[/C][/ROW]
[ROW][C]25[/C][C]-0.032588[/C][C]-0.3402[/C][C]0.367169[/C][/ROW]
[ROW][C]26[/C][C]-0.062234[/C][C]-0.6497[/C][C]0.258613[/C][/ROW]
[ROW][C]27[/C][C]-0.090216[/C][C]-0.9419[/C][C]0.174168[/C][/ROW]
[ROW][C]28[/C][C]-0.117019[/C][C]-1.2217[/C][C]0.112225[/C][/ROW]
[ROW][C]29[/C][C]-0.146452[/C][C]-1.529[/C][C]0.064581[/C][/ROW]
[ROW][C]30[/C][C]-0.176177[/C][C]-1.8393[/C][C]0.034293[/C][/ROW]
[ROW][C]31[/C][C]-0.207366[/C][C]-2.165[/C][C]0.016286[/C][/ROW]
[ROW][C]32[/C][C]-0.238385[/C][C]-2.4888[/C][C]0.007165[/C][/ROW]
[ROW][C]33[/C][C]-0.26398[/C][C]-2.756[/C][C]0.00343[/C][/ROW]
[ROW][C]34[/C][C]-0.284565[/C][C]-2.9709[/C][C]0.001826[/C][/ROW]
[ROW][C]35[/C][C]-0.301183[/C][C]-3.1444[/C][C]0.001072[/C][/ROW]
[ROW][C]36[/C][C]-0.314819[/C][C]-3.2868[/C][C]0.000682[/C][/ROW]
[ROW][C]37[/C][C]-0.32934[/C][C]-3.4384[/C][C]0.000415[/C][/ROW]
[ROW][C]38[/C][C]-0.344447[/C][C]-3.5961[/C][C]0.000243[/C][/ROW]
[ROW][C]39[/C][C]-0.358627[/C][C]-3.7442[/C][C]0.000145[/C][/ROW]
[ROW][C]40[/C][C]-0.373643[/C][C]-3.9009[/C][C]8.3e-05[/C][/ROW]
[ROW][C]41[/C][C]-0.386768[/C][C]-4.038[/C][C]5e-05[/C][/ROW]
[ROW][C]42[/C][C]-0.397906[/C][C]-4.1543[/C][C]3.3e-05[/C][/ROW]
[ROW][C]43[/C][C]-0.40805[/C][C]-4.2602[/C][C]2.2e-05[/C][/ROW]
[ROW][C]44[/C][C]-0.414965[/C][C]-4.3324[/C][C]1.6e-05[/C][/ROW]
[ROW][C]45[/C][C]-0.420775[/C][C]-4.393[/C][C]1.3e-05[/C][/ROW]
[ROW][C]46[/C][C]-0.422325[/C][C]-4.4092[/C][C]1.2e-05[/C][/ROW]
[ROW][C]47[/C][C]-0.420312[/C][C]-4.3882[/C][C]1.3e-05[/C][/ROW]
[ROW][C]48[/C][C]-0.415042[/C][C]-4.3332[/C][C]1.6e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=39747&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=39747&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
10.97173610.14520
20.9323219.73370
30.8923719.31660
40.8482068.85550
50.8120868.47840
60.7706938.04630
70.7257227.57680
80.6871537.17410
90.6495116.78110
100.6083546.35140
110.5624645.87230
120.5111375.33640
130.4601714.80432e-06
140.4147134.32971.7e-05
150.3652243.81310.000114
160.3190923.33140.00059
170.2685382.80360.002992
180.2175752.27160.012539
190.1759831.83730.034444
200.1355291.4150.079965
210.0993381.03710.150987
220.0629720.65740.256139
230.0253120.26430.396038
24-0.004801-0.05010.480056
25-0.032588-0.34020.367169
26-0.062234-0.64970.258613
27-0.090216-0.94190.174168
28-0.117019-1.22170.112225
29-0.146452-1.5290.064581
30-0.176177-1.83930.034293
31-0.207366-2.1650.016286
32-0.238385-2.48880.007165
33-0.26398-2.7560.00343
34-0.284565-2.97090.001826
35-0.301183-3.14440.001072
36-0.314819-3.28680.000682
37-0.32934-3.43840.000415
38-0.344447-3.59610.000243
39-0.358627-3.74420.000145
40-0.373643-3.90098.3e-05
41-0.386768-4.0385e-05
42-0.397906-4.15433.3e-05
43-0.40805-4.26022.2e-05
44-0.414965-4.33241.6e-05
45-0.420775-4.3931.3e-05
46-0.422325-4.40921.2e-05
47-0.420312-4.38821.3e-05
48-0.415042-4.33321.6e-05







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.97173610.14520
2-0.214411-2.23850.01361
30.0094610.09880.460748
4-0.104665-1.09270.13846
50.1610731.68160.04775
6-0.198436-2.07170.020325
7-0.010364-0.10820.457018
80.0719460.75110.227093
9-0.001356-0.01420.494366
10-0.138539-1.44640.075469
11-0.097761-1.02070.154838
12-0.053778-0.56150.287818
13-0.003631-0.03790.484916
140.0333760.34850.364085
15-0.14744-1.53930.063313
160.0950330.99220.161654
17-0.190709-1.99110.024488
180.0617580.64480.260214
190.0222970.23280.408183
200.0213950.22340.411832
210.0161970.16910.433015
22-0.083827-0.87520.191699
230.0201210.21010.417004
240.0455890.4760.317527
25-0.02413-0.25190.400788
26-0.081223-0.8480.19915
270.0461460.48180.315465
28-0.019705-0.20570.418694
29-0.109717-1.14550.127261
30-0.12817-1.33810.091819
310.0234770.24510.403415
32-0.009841-0.10270.459176
33-0.000321-0.00340.498666
340.0417450.43580.331909
35-0.027689-0.28910.386535
360.0292940.30580.380156
37-0.099562-1.03950.150446
38-0.020467-0.21370.415596
390.0168870.17630.430191
40-0.047445-0.49530.31068
410.005330.05560.477861
42-0.007856-0.0820.46739
43-0.001804-0.01880.492506
44-0.033684-0.35170.362881
45-0.039033-0.40750.342212
460.0844920.88210.189825
470.0106160.11080.455976
480.014640.15280.439403

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.971736 & 10.1452 & 0 \tabularnewline
2 & -0.214411 & -2.2385 & 0.01361 \tabularnewline
3 & 0.009461 & 0.0988 & 0.460748 \tabularnewline
4 & -0.104665 & -1.0927 & 0.13846 \tabularnewline
5 & 0.161073 & 1.6816 & 0.04775 \tabularnewline
6 & -0.198436 & -2.0717 & 0.020325 \tabularnewline
7 & -0.010364 & -0.1082 & 0.457018 \tabularnewline
8 & 0.071946 & 0.7511 & 0.227093 \tabularnewline
9 & -0.001356 & -0.0142 & 0.494366 \tabularnewline
10 & -0.138539 & -1.4464 & 0.075469 \tabularnewline
11 & -0.097761 & -1.0207 & 0.154838 \tabularnewline
12 & -0.053778 & -0.5615 & 0.287818 \tabularnewline
13 & -0.003631 & -0.0379 & 0.484916 \tabularnewline
14 & 0.033376 & 0.3485 & 0.364085 \tabularnewline
15 & -0.14744 & -1.5393 & 0.063313 \tabularnewline
16 & 0.095033 & 0.9922 & 0.161654 \tabularnewline
17 & -0.190709 & -1.9911 & 0.024488 \tabularnewline
18 & 0.061758 & 0.6448 & 0.260214 \tabularnewline
19 & 0.022297 & 0.2328 & 0.408183 \tabularnewline
20 & 0.021395 & 0.2234 & 0.411832 \tabularnewline
21 & 0.016197 & 0.1691 & 0.433015 \tabularnewline
22 & -0.083827 & -0.8752 & 0.191699 \tabularnewline
23 & 0.020121 & 0.2101 & 0.417004 \tabularnewline
24 & 0.045589 & 0.476 & 0.317527 \tabularnewline
25 & -0.02413 & -0.2519 & 0.400788 \tabularnewline
26 & -0.081223 & -0.848 & 0.19915 \tabularnewline
27 & 0.046146 & 0.4818 & 0.315465 \tabularnewline
28 & -0.019705 & -0.2057 & 0.418694 \tabularnewline
29 & -0.109717 & -1.1455 & 0.127261 \tabularnewline
30 & -0.12817 & -1.3381 & 0.091819 \tabularnewline
31 & 0.023477 & 0.2451 & 0.403415 \tabularnewline
32 & -0.009841 & -0.1027 & 0.459176 \tabularnewline
33 & -0.000321 & -0.0034 & 0.498666 \tabularnewline
34 & 0.041745 & 0.4358 & 0.331909 \tabularnewline
35 & -0.027689 & -0.2891 & 0.386535 \tabularnewline
36 & 0.029294 & 0.3058 & 0.380156 \tabularnewline
37 & -0.099562 & -1.0395 & 0.150446 \tabularnewline
38 & -0.020467 & -0.2137 & 0.415596 \tabularnewline
39 & 0.016887 & 0.1763 & 0.430191 \tabularnewline
40 & -0.047445 & -0.4953 & 0.31068 \tabularnewline
41 & 0.00533 & 0.0556 & 0.477861 \tabularnewline
42 & -0.007856 & -0.082 & 0.46739 \tabularnewline
43 & -0.001804 & -0.0188 & 0.492506 \tabularnewline
44 & -0.033684 & -0.3517 & 0.362881 \tabularnewline
45 & -0.039033 & -0.4075 & 0.342212 \tabularnewline
46 & 0.084492 & 0.8821 & 0.189825 \tabularnewline
47 & 0.010616 & 0.1108 & 0.455976 \tabularnewline
48 & 0.01464 & 0.1528 & 0.439403 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=39747&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]0.971736[/C][C]10.1452[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.214411[/C][C]-2.2385[/C][C]0.01361[/C][/ROW]
[ROW][C]3[/C][C]0.009461[/C][C]0.0988[/C][C]0.460748[/C][/ROW]
[ROW][C]4[/C][C]-0.104665[/C][C]-1.0927[/C][C]0.13846[/C][/ROW]
[ROW][C]5[/C][C]0.161073[/C][C]1.6816[/C][C]0.04775[/C][/ROW]
[ROW][C]6[/C][C]-0.198436[/C][C]-2.0717[/C][C]0.020325[/C][/ROW]
[ROW][C]7[/C][C]-0.010364[/C][C]-0.1082[/C][C]0.457018[/C][/ROW]
[ROW][C]8[/C][C]0.071946[/C][C]0.7511[/C][C]0.227093[/C][/ROW]
[ROW][C]9[/C][C]-0.001356[/C][C]-0.0142[/C][C]0.494366[/C][/ROW]
[ROW][C]10[/C][C]-0.138539[/C][C]-1.4464[/C][C]0.075469[/C][/ROW]
[ROW][C]11[/C][C]-0.097761[/C][C]-1.0207[/C][C]0.154838[/C][/ROW]
[ROW][C]12[/C][C]-0.053778[/C][C]-0.5615[/C][C]0.287818[/C][/ROW]
[ROW][C]13[/C][C]-0.003631[/C][C]-0.0379[/C][C]0.484916[/C][/ROW]
[ROW][C]14[/C][C]0.033376[/C][C]0.3485[/C][C]0.364085[/C][/ROW]
[ROW][C]15[/C][C]-0.14744[/C][C]-1.5393[/C][C]0.063313[/C][/ROW]
[ROW][C]16[/C][C]0.095033[/C][C]0.9922[/C][C]0.161654[/C][/ROW]
[ROW][C]17[/C][C]-0.190709[/C][C]-1.9911[/C][C]0.024488[/C][/ROW]
[ROW][C]18[/C][C]0.061758[/C][C]0.6448[/C][C]0.260214[/C][/ROW]
[ROW][C]19[/C][C]0.022297[/C][C]0.2328[/C][C]0.408183[/C][/ROW]
[ROW][C]20[/C][C]0.021395[/C][C]0.2234[/C][C]0.411832[/C][/ROW]
[ROW][C]21[/C][C]0.016197[/C][C]0.1691[/C][C]0.433015[/C][/ROW]
[ROW][C]22[/C][C]-0.083827[/C][C]-0.8752[/C][C]0.191699[/C][/ROW]
[ROW][C]23[/C][C]0.020121[/C][C]0.2101[/C][C]0.417004[/C][/ROW]
[ROW][C]24[/C][C]0.045589[/C][C]0.476[/C][C]0.317527[/C][/ROW]
[ROW][C]25[/C][C]-0.02413[/C][C]-0.2519[/C][C]0.400788[/C][/ROW]
[ROW][C]26[/C][C]-0.081223[/C][C]-0.848[/C][C]0.19915[/C][/ROW]
[ROW][C]27[/C][C]0.046146[/C][C]0.4818[/C][C]0.315465[/C][/ROW]
[ROW][C]28[/C][C]-0.019705[/C][C]-0.2057[/C][C]0.418694[/C][/ROW]
[ROW][C]29[/C][C]-0.109717[/C][C]-1.1455[/C][C]0.127261[/C][/ROW]
[ROW][C]30[/C][C]-0.12817[/C][C]-1.3381[/C][C]0.091819[/C][/ROW]
[ROW][C]31[/C][C]0.023477[/C][C]0.2451[/C][C]0.403415[/C][/ROW]
[ROW][C]32[/C][C]-0.009841[/C][C]-0.1027[/C][C]0.459176[/C][/ROW]
[ROW][C]33[/C][C]-0.000321[/C][C]-0.0034[/C][C]0.498666[/C][/ROW]
[ROW][C]34[/C][C]0.041745[/C][C]0.4358[/C][C]0.331909[/C][/ROW]
[ROW][C]35[/C][C]-0.027689[/C][C]-0.2891[/C][C]0.386535[/C][/ROW]
[ROW][C]36[/C][C]0.029294[/C][C]0.3058[/C][C]0.380156[/C][/ROW]
[ROW][C]37[/C][C]-0.099562[/C][C]-1.0395[/C][C]0.150446[/C][/ROW]
[ROW][C]38[/C][C]-0.020467[/C][C]-0.2137[/C][C]0.415596[/C][/ROW]
[ROW][C]39[/C][C]0.016887[/C][C]0.1763[/C][C]0.430191[/C][/ROW]
[ROW][C]40[/C][C]-0.047445[/C][C]-0.4953[/C][C]0.31068[/C][/ROW]
[ROW][C]41[/C][C]0.00533[/C][C]0.0556[/C][C]0.477861[/C][/ROW]
[ROW][C]42[/C][C]-0.007856[/C][C]-0.082[/C][C]0.46739[/C][/ROW]
[ROW][C]43[/C][C]-0.001804[/C][C]-0.0188[/C][C]0.492506[/C][/ROW]
[ROW][C]44[/C][C]-0.033684[/C][C]-0.3517[/C][C]0.362881[/C][/ROW]
[ROW][C]45[/C][C]-0.039033[/C][C]-0.4075[/C][C]0.342212[/C][/ROW]
[ROW][C]46[/C][C]0.084492[/C][C]0.8821[/C][C]0.189825[/C][/ROW]
[ROW][C]47[/C][C]0.010616[/C][C]0.1108[/C][C]0.455976[/C][/ROW]
[ROW][C]48[/C][C]0.01464[/C][C]0.1528[/C][C]0.439403[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=39747&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=39747&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
10.97173610.14520
2-0.214411-2.23850.01361
30.0094610.09880.460748
4-0.104665-1.09270.13846
50.1610731.68160.04775
6-0.198436-2.07170.020325
7-0.010364-0.10820.457018
80.0719460.75110.227093
9-0.001356-0.01420.494366
10-0.138539-1.44640.075469
11-0.097761-1.02070.154838
12-0.053778-0.56150.287818
13-0.003631-0.03790.484916
140.0333760.34850.364085
15-0.14744-1.53930.063313
160.0950330.99220.161654
17-0.190709-1.99110.024488
180.0617580.64480.260214
190.0222970.23280.408183
200.0213950.22340.411832
210.0161970.16910.433015
22-0.083827-0.87520.191699
230.0201210.21010.417004
240.0455890.4760.317527
25-0.02413-0.25190.400788
26-0.081223-0.8480.19915
270.0461460.48180.315465
28-0.019705-0.20570.418694
29-0.109717-1.14550.127261
30-0.12817-1.33810.091819
310.0234770.24510.403415
32-0.009841-0.10270.459176
33-0.000321-0.00340.498666
340.0417450.43580.331909
35-0.027689-0.28910.386535
360.0292940.30580.380156
37-0.099562-1.03950.150446
38-0.020467-0.21370.415596
390.0168870.17630.430191
40-0.047445-0.49530.31068
410.005330.05560.477861
42-0.007856-0.0820.46739
43-0.001804-0.01880.492506
44-0.033684-0.35170.362881
45-0.039033-0.40750.342212
460.0844920.88210.189825
470.0106160.11080.455976
480.014640.15280.439403



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')