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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 03 May 2010 14:24:41 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/03/t1272896773m2mmzi83kcyh79t.htm/, Retrieved Thu, 25 Apr 2024 14:41:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75209, Retrieved Thu, 25 Apr 2024 14:41:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact157
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2010-05-03 14:24:41] [a1c0563c4f28de3d0d1958a3be552dbb] [Current]
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Dataseries X:
66857.2
64722.8
68489.6
71342.9
63542.5
69425.0
58927.9
61009.0
66837.0
66147.6
65982.3
65527.5
65914.6
59189.9
66211.4
66400.8
60167.7
64547.9
57706.2
58642.6
60082.1
63414.8
66044.0
57628.5
62838.8
55758.6
61004.5
66173.4
57489.0
59552.2
57061.8
55895.3
56314.7
61232.8
60014.1
57685.4
60403.1
52349.7
55693.3
65676.1
54898.8
55518.2
53779.1
52340.9
55704.4
60330.3
52837.4
55388.1
60383.4
52070.3
54077.0
62887.8
49212.8
57722.0
53936.8
46991.0
54984.2
56485.1
51277.8
53596.4
54252.5
49413.0
53213.2
58695.3
48723.5
54510.0
49454.1
46136.6
54622.5
50583.0
53224.3
53056.4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75209&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75209&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75209&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5399254.58149e-06
20.5504614.67087e-06
30.6468285.48850
40.3855323.27140.000822
50.5281014.48111.4e-05
60.5874784.98492e-06
70.435443.69480.000213
80.3479122.95210.002129
90.4857234.12155e-05
100.3231022.74160.003853
110.3035952.57610.006022
120.566024.80284e-06
130.2244651.90470.03041
140.2591142.19870.015558
150.2830932.40210.009441
160.0733140.62210.267924
170.231641.96550.026605
180.2253711.91230.029906
190.1431561.21470.114221
200.0654910.55570.290066
210.1270741.07830.14226
220.0635580.53930.295669
230.0350060.2970.383647
240.2038561.72980.043978
250.0062240.05280.479012
26-0.009223-0.07830.46892
270.0213770.18140.428287
28-0.125393-1.0640.145443
29-0.031362-0.26610.395455
30-0.046505-0.39460.347148
31-0.085963-0.72940.234055
32-0.152371-1.29290.100088
33-0.123199-1.04540.149672
34-0.120598-1.02330.154793
35-0.190214-1.6140.055449
36-0.05983-0.50770.306616
37-0.173893-1.47550.072215
38-0.223494-1.89640.030959
39-0.153335-1.30110.098688
40-0.265788-2.25530.013578
41-0.231233-1.96210.026809
42-0.211802-1.79720.038249
43-0.229401-1.94650.027747
44-0.278466-2.36290.010419
45-0.243716-2.0680.021117
46-0.223187-1.89380.031134
47-0.303016-2.57120.006101
48-0.173088-1.46870.073135

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.539925 & 4.5814 & 9e-06 \tabularnewline
2 & 0.550461 & 4.6708 & 7e-06 \tabularnewline
3 & 0.646828 & 5.4885 & 0 \tabularnewline
4 & 0.385532 & 3.2714 & 0.000822 \tabularnewline
5 & 0.528101 & 4.4811 & 1.4e-05 \tabularnewline
6 & 0.587478 & 4.9849 & 2e-06 \tabularnewline
7 & 0.43544 & 3.6948 & 0.000213 \tabularnewline
8 & 0.347912 & 2.9521 & 0.002129 \tabularnewline
9 & 0.485723 & 4.1215 & 5e-05 \tabularnewline
10 & 0.323102 & 2.7416 & 0.003853 \tabularnewline
11 & 0.303595 & 2.5761 & 0.006022 \tabularnewline
12 & 0.56602 & 4.8028 & 4e-06 \tabularnewline
13 & 0.224465 & 1.9047 & 0.03041 \tabularnewline
14 & 0.259114 & 2.1987 & 0.015558 \tabularnewline
15 & 0.283093 & 2.4021 & 0.009441 \tabularnewline
16 & 0.073314 & 0.6221 & 0.267924 \tabularnewline
17 & 0.23164 & 1.9655 & 0.026605 \tabularnewline
18 & 0.225371 & 1.9123 & 0.029906 \tabularnewline
19 & 0.143156 & 1.2147 & 0.114221 \tabularnewline
20 & 0.065491 & 0.5557 & 0.290066 \tabularnewline
21 & 0.127074 & 1.0783 & 0.14226 \tabularnewline
22 & 0.063558 & 0.5393 & 0.295669 \tabularnewline
23 & 0.035006 & 0.297 & 0.383647 \tabularnewline
24 & 0.203856 & 1.7298 & 0.043978 \tabularnewline
25 & 0.006224 & 0.0528 & 0.479012 \tabularnewline
26 & -0.009223 & -0.0783 & 0.46892 \tabularnewline
27 & 0.021377 & 0.1814 & 0.428287 \tabularnewline
28 & -0.125393 & -1.064 & 0.145443 \tabularnewline
29 & -0.031362 & -0.2661 & 0.395455 \tabularnewline
30 & -0.046505 & -0.3946 & 0.347148 \tabularnewline
31 & -0.085963 & -0.7294 & 0.234055 \tabularnewline
32 & -0.152371 & -1.2929 & 0.100088 \tabularnewline
33 & -0.123199 & -1.0454 & 0.149672 \tabularnewline
34 & -0.120598 & -1.0233 & 0.154793 \tabularnewline
35 & -0.190214 & -1.614 & 0.055449 \tabularnewline
36 & -0.05983 & -0.5077 & 0.306616 \tabularnewline
37 & -0.173893 & -1.4755 & 0.072215 \tabularnewline
38 & -0.223494 & -1.8964 & 0.030959 \tabularnewline
39 & -0.153335 & -1.3011 & 0.098688 \tabularnewline
40 & -0.265788 & -2.2553 & 0.013578 \tabularnewline
41 & -0.231233 & -1.9621 & 0.026809 \tabularnewline
42 & -0.211802 & -1.7972 & 0.038249 \tabularnewline
43 & -0.229401 & -1.9465 & 0.027747 \tabularnewline
44 & -0.278466 & -2.3629 & 0.010419 \tabularnewline
45 & -0.243716 & -2.068 & 0.021117 \tabularnewline
46 & -0.223187 & -1.8938 & 0.031134 \tabularnewline
47 & -0.303016 & -2.5712 & 0.006101 \tabularnewline
48 & -0.173088 & -1.4687 & 0.073135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75209&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]0.539925[/C][C]4.5814[/C][C]9e-06[/C][/ROW]
[ROW][C]2[/C][C]0.550461[/C][C]4.6708[/C][C]7e-06[/C][/ROW]
[ROW][C]3[/C][C]0.646828[/C][C]5.4885[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.385532[/C][C]3.2714[/C][C]0.000822[/C][/ROW]
[ROW][C]5[/C][C]0.528101[/C][C]4.4811[/C][C]1.4e-05[/C][/ROW]
[ROW][C]6[/C][C]0.587478[/C][C]4.9849[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]0.43544[/C][C]3.6948[/C][C]0.000213[/C][/ROW]
[ROW][C]8[/C][C]0.347912[/C][C]2.9521[/C][C]0.002129[/C][/ROW]
[ROW][C]9[/C][C]0.485723[/C][C]4.1215[/C][C]5e-05[/C][/ROW]
[ROW][C]10[/C][C]0.323102[/C][C]2.7416[/C][C]0.003853[/C][/ROW]
[ROW][C]11[/C][C]0.303595[/C][C]2.5761[/C][C]0.006022[/C][/ROW]
[ROW][C]12[/C][C]0.56602[/C][C]4.8028[/C][C]4e-06[/C][/ROW]
[ROW][C]13[/C][C]0.224465[/C][C]1.9047[/C][C]0.03041[/C][/ROW]
[ROW][C]14[/C][C]0.259114[/C][C]2.1987[/C][C]0.015558[/C][/ROW]
[ROW][C]15[/C][C]0.283093[/C][C]2.4021[/C][C]0.009441[/C][/ROW]
[ROW][C]16[/C][C]0.073314[/C][C]0.6221[/C][C]0.267924[/C][/ROW]
[ROW][C]17[/C][C]0.23164[/C][C]1.9655[/C][C]0.026605[/C][/ROW]
[ROW][C]18[/C][C]0.225371[/C][C]1.9123[/C][C]0.029906[/C][/ROW]
[ROW][C]19[/C][C]0.143156[/C][C]1.2147[/C][C]0.114221[/C][/ROW]
[ROW][C]20[/C][C]0.065491[/C][C]0.5557[/C][C]0.290066[/C][/ROW]
[ROW][C]21[/C][C]0.127074[/C][C]1.0783[/C][C]0.14226[/C][/ROW]
[ROW][C]22[/C][C]0.063558[/C][C]0.5393[/C][C]0.295669[/C][/ROW]
[ROW][C]23[/C][C]0.035006[/C][C]0.297[/C][C]0.383647[/C][/ROW]
[ROW][C]24[/C][C]0.203856[/C][C]1.7298[/C][C]0.043978[/C][/ROW]
[ROW][C]25[/C][C]0.006224[/C][C]0.0528[/C][C]0.479012[/C][/ROW]
[ROW][C]26[/C][C]-0.009223[/C][C]-0.0783[/C][C]0.46892[/C][/ROW]
[ROW][C]27[/C][C]0.021377[/C][C]0.1814[/C][C]0.428287[/C][/ROW]
[ROW][C]28[/C][C]-0.125393[/C][C]-1.064[/C][C]0.145443[/C][/ROW]
[ROW][C]29[/C][C]-0.031362[/C][C]-0.2661[/C][C]0.395455[/C][/ROW]
[ROW][C]30[/C][C]-0.046505[/C][C]-0.3946[/C][C]0.347148[/C][/ROW]
[ROW][C]31[/C][C]-0.085963[/C][C]-0.7294[/C][C]0.234055[/C][/ROW]
[ROW][C]32[/C][C]-0.152371[/C][C]-1.2929[/C][C]0.100088[/C][/ROW]
[ROW][C]33[/C][C]-0.123199[/C][C]-1.0454[/C][C]0.149672[/C][/ROW]
[ROW][C]34[/C][C]-0.120598[/C][C]-1.0233[/C][C]0.154793[/C][/ROW]
[ROW][C]35[/C][C]-0.190214[/C][C]-1.614[/C][C]0.055449[/C][/ROW]
[ROW][C]36[/C][C]-0.05983[/C][C]-0.5077[/C][C]0.306616[/C][/ROW]
[ROW][C]37[/C][C]-0.173893[/C][C]-1.4755[/C][C]0.072215[/C][/ROW]
[ROW][C]38[/C][C]-0.223494[/C][C]-1.8964[/C][C]0.030959[/C][/ROW]
[ROW][C]39[/C][C]-0.153335[/C][C]-1.3011[/C][C]0.098688[/C][/ROW]
[ROW][C]40[/C][C]-0.265788[/C][C]-2.2553[/C][C]0.013578[/C][/ROW]
[ROW][C]41[/C][C]-0.231233[/C][C]-1.9621[/C][C]0.026809[/C][/ROW]
[ROW][C]42[/C][C]-0.211802[/C][C]-1.7972[/C][C]0.038249[/C][/ROW]
[ROW][C]43[/C][C]-0.229401[/C][C]-1.9465[/C][C]0.027747[/C][/ROW]
[ROW][C]44[/C][C]-0.278466[/C][C]-2.3629[/C][C]0.010419[/C][/ROW]
[ROW][C]45[/C][C]-0.243716[/C][C]-2.068[/C][C]0.021117[/C][/ROW]
[ROW][C]46[/C][C]-0.223187[/C][C]-1.8938[/C][C]0.031134[/C][/ROW]
[ROW][C]47[/C][C]-0.303016[/C][C]-2.5712[/C][C]0.006101[/C][/ROW]
[ROW][C]48[/C][C]-0.173088[/C][C]-1.4687[/C][C]0.073135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75209&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75209&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
10.5399254.58149e-06
20.5504614.67087e-06
30.6468285.48850
40.3855323.27140.000822
50.5281014.48111.4e-05
60.5874784.98492e-06
70.435443.69480.000213
80.3479122.95210.002129
90.4857234.12155e-05
100.3231022.74160.003853
110.3035952.57610.006022
120.566024.80284e-06
130.2244651.90470.03041
140.2591142.19870.015558
150.2830932.40210.009441
160.0733140.62210.267924
170.231641.96550.026605
180.2253711.91230.029906
190.1431561.21470.114221
200.0654910.55570.290066
210.1270741.07830.14226
220.0635580.53930.295669
230.0350060.2970.383647
240.2038561.72980.043978
250.0062240.05280.479012
26-0.009223-0.07830.46892
270.0213770.18140.428287
28-0.125393-1.0640.145443
29-0.031362-0.26610.395455
30-0.046505-0.39460.347148
31-0.085963-0.72940.234055
32-0.152371-1.29290.100088
33-0.123199-1.04540.149672
34-0.120598-1.02330.154793
35-0.190214-1.6140.055449
36-0.05983-0.50770.306616
37-0.173893-1.47550.072215
38-0.223494-1.89640.030959
39-0.153335-1.30110.098688
40-0.265788-2.25530.013578
41-0.231233-1.96210.026809
42-0.211802-1.79720.038249
43-0.229401-1.94650.027747
44-0.278466-2.36290.010419
45-0.243716-2.0680.021117
46-0.223187-1.89380.031134
47-0.303016-2.57120.006101
48-0.173088-1.46870.073135







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5399254.58149e-06
20.3654893.10130.001375
30.4250453.60660.000284
4-0.171198-1.45270.07533
50.2091571.77480.040083
60.255452.16760.01675
70.0517060.43870.331081
8-0.400811-3.4010.000549
90.2435322.06640.021192
100.0220180.18680.426161
11-0.103082-0.87470.192329
120.280942.38390.009885
13-0.203978-1.73080.043885
14-0.161087-1.36690.087959
15-0.254913-2.1630.016931
160.0996850.84590.200217
170.1156250.98110.164913
18-0.11516-0.97720.16588
190.0498660.42310.336732
20-0.060776-0.51570.303822
210.005710.04850.480745
220.0972620.82530.205966
230.0004250.00360.498566
24-0.040736-0.34570.365305
250.0453960.38520.350614
26-0.135161-1.14690.127613
27-0.023644-0.20060.420778
28-0.070821-0.60090.274884
29-0.007897-0.0670.473379
30-0.112251-0.95250.172019
31-0.062324-0.52880.299272
320.077850.66060.255495
330.0182290.15470.438754
340.0140930.11960.452573
35-0.072883-0.61840.269121
36-0.012982-0.11020.456297
370.0230640.19570.422696
38-0.016018-0.13590.446133
390.0111650.09470.462394
40-0.041701-0.35380.362245
41-0.113097-0.95970.170219
42-0.022469-0.19070.424667
430.0534780.45380.325676
440.006470.05490.478185
45-0.019949-0.16930.433027
46-0.047511-0.40310.344017
470.0050360.04270.483015
480.0130650.11090.456017

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.539925 & 4.5814 & 9e-06 \tabularnewline
2 & 0.365489 & 3.1013 & 0.001375 \tabularnewline
3 & 0.425045 & 3.6066 & 0.000284 \tabularnewline
4 & -0.171198 & -1.4527 & 0.07533 \tabularnewline
5 & 0.209157 & 1.7748 & 0.040083 \tabularnewline
6 & 0.25545 & 2.1676 & 0.01675 \tabularnewline
7 & 0.051706 & 0.4387 & 0.331081 \tabularnewline
8 & -0.400811 & -3.401 & 0.000549 \tabularnewline
9 & 0.243532 & 2.0664 & 0.021192 \tabularnewline
10 & 0.022018 & 0.1868 & 0.426161 \tabularnewline
11 & -0.103082 & -0.8747 & 0.192329 \tabularnewline
12 & 0.28094 & 2.3839 & 0.009885 \tabularnewline
13 & -0.203978 & -1.7308 & 0.043885 \tabularnewline
14 & -0.161087 & -1.3669 & 0.087959 \tabularnewline
15 & -0.254913 & -2.163 & 0.016931 \tabularnewline
16 & 0.099685 & 0.8459 & 0.200217 \tabularnewline
17 & 0.115625 & 0.9811 & 0.164913 \tabularnewline
18 & -0.11516 & -0.9772 & 0.16588 \tabularnewline
19 & 0.049866 & 0.4231 & 0.336732 \tabularnewline
20 & -0.060776 & -0.5157 & 0.303822 \tabularnewline
21 & 0.00571 & 0.0485 & 0.480745 \tabularnewline
22 & 0.097262 & 0.8253 & 0.205966 \tabularnewline
23 & 0.000425 & 0.0036 & 0.498566 \tabularnewline
24 & -0.040736 & -0.3457 & 0.365305 \tabularnewline
25 & 0.045396 & 0.3852 & 0.350614 \tabularnewline
26 & -0.135161 & -1.1469 & 0.127613 \tabularnewline
27 & -0.023644 & -0.2006 & 0.420778 \tabularnewline
28 & -0.070821 & -0.6009 & 0.274884 \tabularnewline
29 & -0.007897 & -0.067 & 0.473379 \tabularnewline
30 & -0.112251 & -0.9525 & 0.172019 \tabularnewline
31 & -0.062324 & -0.5288 & 0.299272 \tabularnewline
32 & 0.07785 & 0.6606 & 0.255495 \tabularnewline
33 & 0.018229 & 0.1547 & 0.438754 \tabularnewline
34 & 0.014093 & 0.1196 & 0.452573 \tabularnewline
35 & -0.072883 & -0.6184 & 0.269121 \tabularnewline
36 & -0.012982 & -0.1102 & 0.456297 \tabularnewline
37 & 0.023064 & 0.1957 & 0.422696 \tabularnewline
38 & -0.016018 & -0.1359 & 0.446133 \tabularnewline
39 & 0.011165 & 0.0947 & 0.462394 \tabularnewline
40 & -0.041701 & -0.3538 & 0.362245 \tabularnewline
41 & -0.113097 & -0.9597 & 0.170219 \tabularnewline
42 & -0.022469 & -0.1907 & 0.424667 \tabularnewline
43 & 0.053478 & 0.4538 & 0.325676 \tabularnewline
44 & 0.00647 & 0.0549 & 0.478185 \tabularnewline
45 & -0.019949 & -0.1693 & 0.433027 \tabularnewline
46 & -0.047511 & -0.4031 & 0.344017 \tabularnewline
47 & 0.005036 & 0.0427 & 0.483015 \tabularnewline
48 & 0.013065 & 0.1109 & 0.456017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75209&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]0.539925[/C][C]4.5814[/C][C]9e-06[/C][/ROW]
[ROW][C]2[/C][C]0.365489[/C][C]3.1013[/C][C]0.001375[/C][/ROW]
[ROW][C]3[/C][C]0.425045[/C][C]3.6066[/C][C]0.000284[/C][/ROW]
[ROW][C]4[/C][C]-0.171198[/C][C]-1.4527[/C][C]0.07533[/C][/ROW]
[ROW][C]5[/C][C]0.209157[/C][C]1.7748[/C][C]0.040083[/C][/ROW]
[ROW][C]6[/C][C]0.25545[/C][C]2.1676[/C][C]0.01675[/C][/ROW]
[ROW][C]7[/C][C]0.051706[/C][C]0.4387[/C][C]0.331081[/C][/ROW]
[ROW][C]8[/C][C]-0.400811[/C][C]-3.401[/C][C]0.000549[/C][/ROW]
[ROW][C]9[/C][C]0.243532[/C][C]2.0664[/C][C]0.021192[/C][/ROW]
[ROW][C]10[/C][C]0.022018[/C][C]0.1868[/C][C]0.426161[/C][/ROW]
[ROW][C]11[/C][C]-0.103082[/C][C]-0.8747[/C][C]0.192329[/C][/ROW]
[ROW][C]12[/C][C]0.28094[/C][C]2.3839[/C][C]0.009885[/C][/ROW]
[ROW][C]13[/C][C]-0.203978[/C][C]-1.7308[/C][C]0.043885[/C][/ROW]
[ROW][C]14[/C][C]-0.161087[/C][C]-1.3669[/C][C]0.087959[/C][/ROW]
[ROW][C]15[/C][C]-0.254913[/C][C]-2.163[/C][C]0.016931[/C][/ROW]
[ROW][C]16[/C][C]0.099685[/C][C]0.8459[/C][C]0.200217[/C][/ROW]
[ROW][C]17[/C][C]0.115625[/C][C]0.9811[/C][C]0.164913[/C][/ROW]
[ROW][C]18[/C][C]-0.11516[/C][C]-0.9772[/C][C]0.16588[/C][/ROW]
[ROW][C]19[/C][C]0.049866[/C][C]0.4231[/C][C]0.336732[/C][/ROW]
[ROW][C]20[/C][C]-0.060776[/C][C]-0.5157[/C][C]0.303822[/C][/ROW]
[ROW][C]21[/C][C]0.00571[/C][C]0.0485[/C][C]0.480745[/C][/ROW]
[ROW][C]22[/C][C]0.097262[/C][C]0.8253[/C][C]0.205966[/C][/ROW]
[ROW][C]23[/C][C]0.000425[/C][C]0.0036[/C][C]0.498566[/C][/ROW]
[ROW][C]24[/C][C]-0.040736[/C][C]-0.3457[/C][C]0.365305[/C][/ROW]
[ROW][C]25[/C][C]0.045396[/C][C]0.3852[/C][C]0.350614[/C][/ROW]
[ROW][C]26[/C][C]-0.135161[/C][C]-1.1469[/C][C]0.127613[/C][/ROW]
[ROW][C]27[/C][C]-0.023644[/C][C]-0.2006[/C][C]0.420778[/C][/ROW]
[ROW][C]28[/C][C]-0.070821[/C][C]-0.6009[/C][C]0.274884[/C][/ROW]
[ROW][C]29[/C][C]-0.007897[/C][C]-0.067[/C][C]0.473379[/C][/ROW]
[ROW][C]30[/C][C]-0.112251[/C][C]-0.9525[/C][C]0.172019[/C][/ROW]
[ROW][C]31[/C][C]-0.062324[/C][C]-0.5288[/C][C]0.299272[/C][/ROW]
[ROW][C]32[/C][C]0.07785[/C][C]0.6606[/C][C]0.255495[/C][/ROW]
[ROW][C]33[/C][C]0.018229[/C][C]0.1547[/C][C]0.438754[/C][/ROW]
[ROW][C]34[/C][C]0.014093[/C][C]0.1196[/C][C]0.452573[/C][/ROW]
[ROW][C]35[/C][C]-0.072883[/C][C]-0.6184[/C][C]0.269121[/C][/ROW]
[ROW][C]36[/C][C]-0.012982[/C][C]-0.1102[/C][C]0.456297[/C][/ROW]
[ROW][C]37[/C][C]0.023064[/C][C]0.1957[/C][C]0.422696[/C][/ROW]
[ROW][C]38[/C][C]-0.016018[/C][C]-0.1359[/C][C]0.446133[/C][/ROW]
[ROW][C]39[/C][C]0.011165[/C][C]0.0947[/C][C]0.462394[/C][/ROW]
[ROW][C]40[/C][C]-0.041701[/C][C]-0.3538[/C][C]0.362245[/C][/ROW]
[ROW][C]41[/C][C]-0.113097[/C][C]-0.9597[/C][C]0.170219[/C][/ROW]
[ROW][C]42[/C][C]-0.022469[/C][C]-0.1907[/C][C]0.424667[/C][/ROW]
[ROW][C]43[/C][C]0.053478[/C][C]0.4538[/C][C]0.325676[/C][/ROW]
[ROW][C]44[/C][C]0.00647[/C][C]0.0549[/C][C]0.478185[/C][/ROW]
[ROW][C]45[/C][C]-0.019949[/C][C]-0.1693[/C][C]0.433027[/C][/ROW]
[ROW][C]46[/C][C]-0.047511[/C][C]-0.4031[/C][C]0.344017[/C][/ROW]
[ROW][C]47[/C][C]0.005036[/C][C]0.0427[/C][C]0.483015[/C][/ROW]
[ROW][C]48[/C][C]0.013065[/C][C]0.1109[/C][C]0.456017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75209&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75209&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
10.5399254.58149e-06
20.3654893.10130.001375
30.4250453.60660.000284
4-0.171198-1.45270.07533
50.2091571.77480.040083
60.255452.16760.01675
70.0517060.43870.331081
8-0.400811-3.4010.000549
90.2435322.06640.021192
100.0220180.18680.426161
11-0.103082-0.87470.192329
120.280942.38390.009885
13-0.203978-1.73080.043885
14-0.161087-1.36690.087959
15-0.254913-2.1630.016931
160.0996850.84590.200217
170.1156250.98110.164913
18-0.11516-0.97720.16588
190.0498660.42310.336732
20-0.060776-0.51570.303822
210.005710.04850.480745
220.0972620.82530.205966
230.0004250.00360.498566
24-0.040736-0.34570.365305
250.0453960.38520.350614
26-0.135161-1.14690.127613
27-0.023644-0.20060.420778
28-0.070821-0.60090.274884
29-0.007897-0.0670.473379
30-0.112251-0.95250.172019
31-0.062324-0.52880.299272
320.077850.66060.255495
330.0182290.15470.438754
340.0140930.11960.452573
35-0.072883-0.61840.269121
36-0.012982-0.11020.456297
370.0230640.19570.422696
38-0.016018-0.13590.446133
390.0111650.09470.462394
40-0.041701-0.35380.362245
41-0.113097-0.95970.170219
42-0.022469-0.19070.424667
430.0534780.45380.325676
440.006470.05490.478185
45-0.019949-0.16930.433027
46-0.047511-0.40310.344017
470.0050360.04270.483015
480.0130650.11090.456017



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')