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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 21 Nov 2010 09:29:07 +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/Nov/21/t1290331761q8bjrwp5rujybe7.htm/, Retrieved Thu, 02 May 2024 03:44:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=98327, Retrieved Thu, 02 May 2024 03:44:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact209
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelatie we...] [2010-11-21 09:29:07] [3ed99328c0a6512dc7383724785cc652] [Current]
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Dataseries X:
180144
173666
165688
161570
156145
153730
182698
200765
176512
166618
158644
159585
163095
159044
155511
153745
150569
150605
179612
194690
189917
184128
175335
179566
181140
177876
175041
169292
166070
166972
206348
215706
202108
195411
193111
195198
198770
194163
190420
189733
186029
191531
232571
243477
227247
217859
208679
213188
216234
213586
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171297
169701
164182
161914
159612
151001
158114
186530
187069
174330
169362
166827
178037
186413
189226
191563
188906
186005
195309
223532
226899
214126
206903
204442
220375
214320
212588
205816
202196
195722
198563
229139
229527
211868




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98327&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98327&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98327&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.89399210.15380
20.7363978.36390
30.642597.29840
40.6123466.95490
50.6112666.94260
60.5929056.73410
70.5568476.32460
80.5036255.72010
90.4761615.40820
100.5007235.68710
110.5869346.66630
120.6198757.04040
130.4839455.49660
140.3067983.48460.000337
150.1901982.16020.016302
160.1350681.53410.063729
170.1099131.24840.107079
180.0728670.82760.20471
190.0219630.24940.401706
20-0.037195-0.42250.336697
21-0.065324-0.74190.229737
22-0.041935-0.47630.317338
230.0380490.43220.333176
240.0655710.74470.228892
25-0.058923-0.66920.252269
26-0.211619-2.40350.00883
27-0.298807-3.39380.000458
28-0.330456-3.75330.000131
29-0.334504-3.79920.000111
30-0.349104-3.96516e-05
31-0.367934-4.17892.7e-05
32-0.392037-4.45279e-06
33-0.38965-4.42561e-05
34-0.342007-3.88458.2e-05
35-0.245028-2.7830.003098
36-0.200515-2.27740.012204
37-0.292188-3.31860.000588
38-0.404391-4.5935e-06
39-0.45814-5.20350
40-0.461314-5.23950
41-0.439522-4.9921e-06
42-0.428788-4.87012e-06
43-0.423163-4.80622e-06
44-0.423854-4.81412e-06
45-0.402613-4.57286e-06
46-0.341441-3.8788.3e-05
47-0.243838-2.76950.003222
48-0.190688-2.16580.016083

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.893992 & 10.1538 & 0 \tabularnewline
2 & 0.736397 & 8.3639 & 0 \tabularnewline
3 & 0.64259 & 7.2984 & 0 \tabularnewline
4 & 0.612346 & 6.9549 & 0 \tabularnewline
5 & 0.611266 & 6.9426 & 0 \tabularnewline
6 & 0.592905 & 6.7341 & 0 \tabularnewline
7 & 0.556847 & 6.3246 & 0 \tabularnewline
8 & 0.503625 & 5.7201 & 0 \tabularnewline
9 & 0.476161 & 5.4082 & 0 \tabularnewline
10 & 0.500723 & 5.6871 & 0 \tabularnewline
11 & 0.586934 & 6.6663 & 0 \tabularnewline
12 & 0.619875 & 7.0404 & 0 \tabularnewline
13 & 0.483945 & 5.4966 & 0 \tabularnewline
14 & 0.306798 & 3.4846 & 0.000337 \tabularnewline
15 & 0.190198 & 2.1602 & 0.016302 \tabularnewline
16 & 0.135068 & 1.5341 & 0.063729 \tabularnewline
17 & 0.109913 & 1.2484 & 0.107079 \tabularnewline
18 & 0.072867 & 0.8276 & 0.20471 \tabularnewline
19 & 0.021963 & 0.2494 & 0.401706 \tabularnewline
20 & -0.037195 & -0.4225 & 0.336697 \tabularnewline
21 & -0.065324 & -0.7419 & 0.229737 \tabularnewline
22 & -0.041935 & -0.4763 & 0.317338 \tabularnewline
23 & 0.038049 & 0.4322 & 0.333176 \tabularnewline
24 & 0.065571 & 0.7447 & 0.228892 \tabularnewline
25 & -0.058923 & -0.6692 & 0.252269 \tabularnewline
26 & -0.211619 & -2.4035 & 0.00883 \tabularnewline
27 & -0.298807 & -3.3938 & 0.000458 \tabularnewline
28 & -0.330456 & -3.7533 & 0.000131 \tabularnewline
29 & -0.334504 & -3.7992 & 0.000111 \tabularnewline
30 & -0.349104 & -3.9651 & 6e-05 \tabularnewline
31 & -0.367934 & -4.1789 & 2.7e-05 \tabularnewline
32 & -0.392037 & -4.4527 & 9e-06 \tabularnewline
33 & -0.38965 & -4.4256 & 1e-05 \tabularnewline
34 & -0.342007 & -3.8845 & 8.2e-05 \tabularnewline
35 & -0.245028 & -2.783 & 0.003098 \tabularnewline
36 & -0.200515 & -2.2774 & 0.012204 \tabularnewline
37 & -0.292188 & -3.3186 & 0.000588 \tabularnewline
38 & -0.404391 & -4.593 & 5e-06 \tabularnewline
39 & -0.45814 & -5.2035 & 0 \tabularnewline
40 & -0.461314 & -5.2395 & 0 \tabularnewline
41 & -0.439522 & -4.992 & 1e-06 \tabularnewline
42 & -0.428788 & -4.8701 & 2e-06 \tabularnewline
43 & -0.423163 & -4.8062 & 2e-06 \tabularnewline
44 & -0.423854 & -4.8141 & 2e-06 \tabularnewline
45 & -0.402613 & -4.5728 & 6e-06 \tabularnewline
46 & -0.341441 & -3.878 & 8.3e-05 \tabularnewline
47 & -0.243838 & -2.7695 & 0.003222 \tabularnewline
48 & -0.190688 & -2.1658 & 0.016083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98327&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]0.893992[/C][C]10.1538[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.736397[/C][C]8.3639[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.64259[/C][C]7.2984[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.612346[/C][C]6.9549[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.611266[/C][C]6.9426[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.592905[/C][C]6.7341[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.556847[/C][C]6.3246[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.503625[/C][C]5.7201[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.476161[/C][C]5.4082[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.500723[/C][C]5.6871[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.586934[/C][C]6.6663[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.619875[/C][C]7.0404[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.483945[/C][C]5.4966[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.306798[/C][C]3.4846[/C][C]0.000337[/C][/ROW]
[ROW][C]15[/C][C]0.190198[/C][C]2.1602[/C][C]0.016302[/C][/ROW]
[ROW][C]16[/C][C]0.135068[/C][C]1.5341[/C][C]0.063729[/C][/ROW]
[ROW][C]17[/C][C]0.109913[/C][C]1.2484[/C][C]0.107079[/C][/ROW]
[ROW][C]18[/C][C]0.072867[/C][C]0.8276[/C][C]0.20471[/C][/ROW]
[ROW][C]19[/C][C]0.021963[/C][C]0.2494[/C][C]0.401706[/C][/ROW]
[ROW][C]20[/C][C]-0.037195[/C][C]-0.4225[/C][C]0.336697[/C][/ROW]
[ROW][C]21[/C][C]-0.065324[/C][C]-0.7419[/C][C]0.229737[/C][/ROW]
[ROW][C]22[/C][C]-0.041935[/C][C]-0.4763[/C][C]0.317338[/C][/ROW]
[ROW][C]23[/C][C]0.038049[/C][C]0.4322[/C][C]0.333176[/C][/ROW]
[ROW][C]24[/C][C]0.065571[/C][C]0.7447[/C][C]0.228892[/C][/ROW]
[ROW][C]25[/C][C]-0.058923[/C][C]-0.6692[/C][C]0.252269[/C][/ROW]
[ROW][C]26[/C][C]-0.211619[/C][C]-2.4035[/C][C]0.00883[/C][/ROW]
[ROW][C]27[/C][C]-0.298807[/C][C]-3.3938[/C][C]0.000458[/C][/ROW]
[ROW][C]28[/C][C]-0.330456[/C][C]-3.7533[/C][C]0.000131[/C][/ROW]
[ROW][C]29[/C][C]-0.334504[/C][C]-3.7992[/C][C]0.000111[/C][/ROW]
[ROW][C]30[/C][C]-0.349104[/C][C]-3.9651[/C][C]6e-05[/C][/ROW]
[ROW][C]31[/C][C]-0.367934[/C][C]-4.1789[/C][C]2.7e-05[/C][/ROW]
[ROW][C]32[/C][C]-0.392037[/C][C]-4.4527[/C][C]9e-06[/C][/ROW]
[ROW][C]33[/C][C]-0.38965[/C][C]-4.4256[/C][C]1e-05[/C][/ROW]
[ROW][C]34[/C][C]-0.342007[/C][C]-3.8845[/C][C]8.2e-05[/C][/ROW]
[ROW][C]35[/C][C]-0.245028[/C][C]-2.783[/C][C]0.003098[/C][/ROW]
[ROW][C]36[/C][C]-0.200515[/C][C]-2.2774[/C][C]0.012204[/C][/ROW]
[ROW][C]37[/C][C]-0.292188[/C][C]-3.3186[/C][C]0.000588[/C][/ROW]
[ROW][C]38[/C][C]-0.404391[/C][C]-4.593[/C][C]5e-06[/C][/ROW]
[ROW][C]39[/C][C]-0.45814[/C][C]-5.2035[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]-0.461314[/C][C]-5.2395[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]-0.439522[/C][C]-4.992[/C][C]1e-06[/C][/ROW]
[ROW][C]42[/C][C]-0.428788[/C][C]-4.8701[/C][C]2e-06[/C][/ROW]
[ROW][C]43[/C][C]-0.423163[/C][C]-4.8062[/C][C]2e-06[/C][/ROW]
[ROW][C]44[/C][C]-0.423854[/C][C]-4.8141[/C][C]2e-06[/C][/ROW]
[ROW][C]45[/C][C]-0.402613[/C][C]-4.5728[/C][C]6e-06[/C][/ROW]
[ROW][C]46[/C][C]-0.341441[/C][C]-3.878[/C][C]8.3e-05[/C][/ROW]
[ROW][C]47[/C][C]-0.243838[/C][C]-2.7695[/C][C]0.003222[/C][/ROW]
[ROW][C]48[/C][C]-0.190688[/C][C]-2.1658[/C][C]0.016083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98327&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98327&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
10.89399210.15380
20.7363978.36390
30.642597.29840
40.6123466.95490
50.6112666.94260
60.5929056.73410
70.5568476.32460
80.5036255.72010
90.4761615.40820
100.5007235.68710
110.5869346.66630
120.6198757.04040
130.4839455.49660
140.3067983.48460.000337
150.1901982.16020.016302
160.1350681.53410.063729
170.1099131.24840.107079
180.0728670.82760.20471
190.0219630.24940.401706
20-0.037195-0.42250.336697
21-0.065324-0.74190.229737
22-0.041935-0.47630.317338
230.0380490.43220.333176
240.0655710.74470.228892
25-0.058923-0.66920.252269
26-0.211619-2.40350.00883
27-0.298807-3.39380.000458
28-0.330456-3.75330.000131
29-0.334504-3.79920.000111
30-0.349104-3.96516e-05
31-0.367934-4.17892.7e-05
32-0.392037-4.45279e-06
33-0.38965-4.42561e-05
34-0.342007-3.88458.2e-05
35-0.245028-2.7830.003098
36-0.200515-2.27740.012204
37-0.292188-3.31860.000588
38-0.404391-4.5935e-06
39-0.45814-5.20350
40-0.461314-5.23950
41-0.439522-4.9921e-06
42-0.428788-4.87012e-06
43-0.423163-4.80622e-06
44-0.423854-4.81412e-06
45-0.402613-4.57286e-06
46-0.341441-3.8788.3e-05
47-0.243838-2.76950.003222
48-0.190688-2.16580.016083







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.89399210.15380
2-0.312908-3.5540.000265
30.3202133.63690.000199
40.0901881.02430.153795
50.1222561.38860.08368
6-0.044753-0.50830.306055
70.0604020.6860.246962
8-0.099471-1.12980.130334
90.1842792.0930.019154
100.1373751.56030.060572
110.3758054.26831.9e-05
12-0.365391-4.153e-05
13-0.645221-7.32830
14-0.001319-0.0150.494036
15-0.069367-0.78790.216112
16-0.181792-2.06480.020475
17-0.002476-0.02810.488805
18-0.056297-0.63940.261843
190.0158270.17980.42881
200.0165350.18780.425666
210.1480591.68160.04753
220.040540.46050.322984
230.0862710.97990.164497
240.0020620.02340.490674
25-0.183276-2.08160.019677
260.069430.78860.215905
270.0688620.78210.217787
28-0.18232-2.07080.020188
290.0265240.30130.381854
30-0.045552-0.51740.30289
310.1190051.35160.089428
32-0.09991-1.13480.12929
330.0312520.3550.361601
34-0.047011-0.53390.297149
350.0050780.05770.47705
36-0.041384-0.470.319562
370.0123130.13990.444498
38-0.080285-0.91190.18177
39-0.014806-0.16820.433357
40-0.087307-0.99160.16162
410.0884841.0050.158392
42-0.119647-1.35890.088269
430.0419990.4770.317078
44-0.13-1.47650.071121
450.0338310.38420.350714
46-0.066473-0.7550.225816
47-0.040608-0.46120.32271
480.0909811.03330.151688

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.893992 & 10.1538 & 0 \tabularnewline
2 & -0.312908 & -3.554 & 0.000265 \tabularnewline
3 & 0.320213 & 3.6369 & 0.000199 \tabularnewline
4 & 0.090188 & 1.0243 & 0.153795 \tabularnewline
5 & 0.122256 & 1.3886 & 0.08368 \tabularnewline
6 & -0.044753 & -0.5083 & 0.306055 \tabularnewline
7 & 0.060402 & 0.686 & 0.246962 \tabularnewline
8 & -0.099471 & -1.1298 & 0.130334 \tabularnewline
9 & 0.184279 & 2.093 & 0.019154 \tabularnewline
10 & 0.137375 & 1.5603 & 0.060572 \tabularnewline
11 & 0.375805 & 4.2683 & 1.9e-05 \tabularnewline
12 & -0.365391 & -4.15 & 3e-05 \tabularnewline
13 & -0.645221 & -7.3283 & 0 \tabularnewline
14 & -0.001319 & -0.015 & 0.494036 \tabularnewline
15 & -0.069367 & -0.7879 & 0.216112 \tabularnewline
16 & -0.181792 & -2.0648 & 0.020475 \tabularnewline
17 & -0.002476 & -0.0281 & 0.488805 \tabularnewline
18 & -0.056297 & -0.6394 & 0.261843 \tabularnewline
19 & 0.015827 & 0.1798 & 0.42881 \tabularnewline
20 & 0.016535 & 0.1878 & 0.425666 \tabularnewline
21 & 0.148059 & 1.6816 & 0.04753 \tabularnewline
22 & 0.04054 & 0.4605 & 0.322984 \tabularnewline
23 & 0.086271 & 0.9799 & 0.164497 \tabularnewline
24 & 0.002062 & 0.0234 & 0.490674 \tabularnewline
25 & -0.183276 & -2.0816 & 0.019677 \tabularnewline
26 & 0.06943 & 0.7886 & 0.215905 \tabularnewline
27 & 0.068862 & 0.7821 & 0.217787 \tabularnewline
28 & -0.18232 & -2.0708 & 0.020188 \tabularnewline
29 & 0.026524 & 0.3013 & 0.381854 \tabularnewline
30 & -0.045552 & -0.5174 & 0.30289 \tabularnewline
31 & 0.119005 & 1.3516 & 0.089428 \tabularnewline
32 & -0.09991 & -1.1348 & 0.12929 \tabularnewline
33 & 0.031252 & 0.355 & 0.361601 \tabularnewline
34 & -0.047011 & -0.5339 & 0.297149 \tabularnewline
35 & 0.005078 & 0.0577 & 0.47705 \tabularnewline
36 & -0.041384 & -0.47 & 0.319562 \tabularnewline
37 & 0.012313 & 0.1399 & 0.444498 \tabularnewline
38 & -0.080285 & -0.9119 & 0.18177 \tabularnewline
39 & -0.014806 & -0.1682 & 0.433357 \tabularnewline
40 & -0.087307 & -0.9916 & 0.16162 \tabularnewline
41 & 0.088484 & 1.005 & 0.158392 \tabularnewline
42 & -0.119647 & -1.3589 & 0.088269 \tabularnewline
43 & 0.041999 & 0.477 & 0.317078 \tabularnewline
44 & -0.13 & -1.4765 & 0.071121 \tabularnewline
45 & 0.033831 & 0.3842 & 0.350714 \tabularnewline
46 & -0.066473 & -0.755 & 0.225816 \tabularnewline
47 & -0.040608 & -0.4612 & 0.32271 \tabularnewline
48 & 0.090981 & 1.0333 & 0.151688 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98327&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]0.893992[/C][C]10.1538[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.312908[/C][C]-3.554[/C][C]0.000265[/C][/ROW]
[ROW][C]3[/C][C]0.320213[/C][C]3.6369[/C][C]0.000199[/C][/ROW]
[ROW][C]4[/C][C]0.090188[/C][C]1.0243[/C][C]0.153795[/C][/ROW]
[ROW][C]5[/C][C]0.122256[/C][C]1.3886[/C][C]0.08368[/C][/ROW]
[ROW][C]6[/C][C]-0.044753[/C][C]-0.5083[/C][C]0.306055[/C][/ROW]
[ROW][C]7[/C][C]0.060402[/C][C]0.686[/C][C]0.246962[/C][/ROW]
[ROW][C]8[/C][C]-0.099471[/C][C]-1.1298[/C][C]0.130334[/C][/ROW]
[ROW][C]9[/C][C]0.184279[/C][C]2.093[/C][C]0.019154[/C][/ROW]
[ROW][C]10[/C][C]0.137375[/C][C]1.5603[/C][C]0.060572[/C][/ROW]
[ROW][C]11[/C][C]0.375805[/C][C]4.2683[/C][C]1.9e-05[/C][/ROW]
[ROW][C]12[/C][C]-0.365391[/C][C]-4.15[/C][C]3e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.645221[/C][C]-7.3283[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]-0.001319[/C][C]-0.015[/C][C]0.494036[/C][/ROW]
[ROW][C]15[/C][C]-0.069367[/C][C]-0.7879[/C][C]0.216112[/C][/ROW]
[ROW][C]16[/C][C]-0.181792[/C][C]-2.0648[/C][C]0.020475[/C][/ROW]
[ROW][C]17[/C][C]-0.002476[/C][C]-0.0281[/C][C]0.488805[/C][/ROW]
[ROW][C]18[/C][C]-0.056297[/C][C]-0.6394[/C][C]0.261843[/C][/ROW]
[ROW][C]19[/C][C]0.015827[/C][C]0.1798[/C][C]0.42881[/C][/ROW]
[ROW][C]20[/C][C]0.016535[/C][C]0.1878[/C][C]0.425666[/C][/ROW]
[ROW][C]21[/C][C]0.148059[/C][C]1.6816[/C][C]0.04753[/C][/ROW]
[ROW][C]22[/C][C]0.04054[/C][C]0.4605[/C][C]0.322984[/C][/ROW]
[ROW][C]23[/C][C]0.086271[/C][C]0.9799[/C][C]0.164497[/C][/ROW]
[ROW][C]24[/C][C]0.002062[/C][C]0.0234[/C][C]0.490674[/C][/ROW]
[ROW][C]25[/C][C]-0.183276[/C][C]-2.0816[/C][C]0.019677[/C][/ROW]
[ROW][C]26[/C][C]0.06943[/C][C]0.7886[/C][C]0.215905[/C][/ROW]
[ROW][C]27[/C][C]0.068862[/C][C]0.7821[/C][C]0.217787[/C][/ROW]
[ROW][C]28[/C][C]-0.18232[/C][C]-2.0708[/C][C]0.020188[/C][/ROW]
[ROW][C]29[/C][C]0.026524[/C][C]0.3013[/C][C]0.381854[/C][/ROW]
[ROW][C]30[/C][C]-0.045552[/C][C]-0.5174[/C][C]0.30289[/C][/ROW]
[ROW][C]31[/C][C]0.119005[/C][C]1.3516[/C][C]0.089428[/C][/ROW]
[ROW][C]32[/C][C]-0.09991[/C][C]-1.1348[/C][C]0.12929[/C][/ROW]
[ROW][C]33[/C][C]0.031252[/C][C]0.355[/C][C]0.361601[/C][/ROW]
[ROW][C]34[/C][C]-0.047011[/C][C]-0.5339[/C][C]0.297149[/C][/ROW]
[ROW][C]35[/C][C]0.005078[/C][C]0.0577[/C][C]0.47705[/C][/ROW]
[ROW][C]36[/C][C]-0.041384[/C][C]-0.47[/C][C]0.319562[/C][/ROW]
[ROW][C]37[/C][C]0.012313[/C][C]0.1399[/C][C]0.444498[/C][/ROW]
[ROW][C]38[/C][C]-0.080285[/C][C]-0.9119[/C][C]0.18177[/C][/ROW]
[ROW][C]39[/C][C]-0.014806[/C][C]-0.1682[/C][C]0.433357[/C][/ROW]
[ROW][C]40[/C][C]-0.087307[/C][C]-0.9916[/C][C]0.16162[/C][/ROW]
[ROW][C]41[/C][C]0.088484[/C][C]1.005[/C][C]0.158392[/C][/ROW]
[ROW][C]42[/C][C]-0.119647[/C][C]-1.3589[/C][C]0.088269[/C][/ROW]
[ROW][C]43[/C][C]0.041999[/C][C]0.477[/C][C]0.317078[/C][/ROW]
[ROW][C]44[/C][C]-0.13[/C][C]-1.4765[/C][C]0.071121[/C][/ROW]
[ROW][C]45[/C][C]0.033831[/C][C]0.3842[/C][C]0.350714[/C][/ROW]
[ROW][C]46[/C][C]-0.066473[/C][C]-0.755[/C][C]0.225816[/C][/ROW]
[ROW][C]47[/C][C]-0.040608[/C][C]-0.4612[/C][C]0.32271[/C][/ROW]
[ROW][C]48[/C][C]0.090981[/C][C]1.0333[/C][C]0.151688[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98327&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98327&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
10.89399210.15380
2-0.312908-3.5540.000265
30.3202133.63690.000199
40.0901881.02430.153795
50.1222561.38860.08368
6-0.044753-0.50830.306055
70.0604020.6860.246962
8-0.099471-1.12980.130334
90.1842792.0930.019154
100.1373751.56030.060572
110.3758054.26831.9e-05
12-0.365391-4.153e-05
13-0.645221-7.32830
14-0.001319-0.0150.494036
15-0.069367-0.78790.216112
16-0.181792-2.06480.020475
17-0.002476-0.02810.488805
18-0.056297-0.63940.261843
190.0158270.17980.42881
200.0165350.18780.425666
210.1480591.68160.04753
220.040540.46050.322984
230.0862710.97990.164497
240.0020620.02340.490674
25-0.183276-2.08160.019677
260.069430.78860.215905
270.0688620.78210.217787
28-0.18232-2.07080.020188
290.0265240.30130.381854
30-0.045552-0.51740.30289
310.1190051.35160.089428
32-0.09991-1.13480.12929
330.0312520.3550.361601
34-0.047011-0.53390.297149
350.0050780.05770.47705
36-0.041384-0.470.319562
370.0123130.13990.444498
38-0.080285-0.91190.18177
39-0.014806-0.16820.433357
40-0.087307-0.99160.16162
410.0884841.0050.158392
42-0.119647-1.35890.088269
430.0419990.4770.317078
44-0.13-1.47650.071121
450.0338310.38420.350714
46-0.066473-0.7550.225816
47-0.040608-0.46120.32271
480.0909811.03330.151688



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')