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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 01 May 2010 10:49:04 +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/01/t12727110132hdcq8qvp35vgu4.htm/, Retrieved Sun, 28 Apr 2024 17:47:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75107, Retrieved Sun, 28 Apr 2024 17:47:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact169
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Katleen van den A...] [2010-04-23 13:13:26] [b39c10f74e49ba87352399c34734b08b]
-    D  [Mean Plot] [Katleen van den A...] [2010-04-26 14:36:04] [b39c10f74e49ba87352399c34734b08b]
- RMPD    [(Partial) Autocorrelation Function] [Katleen van den A...] [2010-05-01 10:30:39] [b39c10f74e49ba87352399c34734b08b]
-    D        [(Partial) Autocorrelation Function] [Katleen van den A...] [2010-05-01 10:49:04] [8b7f9564fd63910ef0a86e3a376c4af8] [Current]
-   P           [(Partial) Autocorrelation Function] [Katleen van den A...] [2010-05-07 10:03:46] [b39c10f74e49ba87352399c34734b08b]
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Dataseries X:
285708
905858
225733
405481
845758
805651
395747
695853
175625
405534
965639
575634
576023
566089
336141
26271
586226
376484
176583
287042
997142
207694
418003
838258
848182
658215
208304
398599
438399
578393
988390
958304
318251
78307
408520
748640
258520
518618
388588
238842
328957
499266
109011
168896
798921
878732
897576
518317
228370
758167
658491
518170
398212
498286
78136
647990
357927
698061
407932
637934
397784
217980
47737
467672
67651
167524
687406
367345
157553
887453
227566
817279
697059
997185
847075
547122
996977
346998
967154
547097
586853
46728
236883
36784
277085
446998
586725
496845
86765
146966
197113
657096
337200
17273
457284
507696
547628
157435
67793
267631
518397
918560
918895
429509
289569
9010172
1810617
7111400
1611919
9712714
2913310
1013816
6714518
2414721
9114534
8214993
6215159
515612
9415340
3715267




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75107&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75107&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75107&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4047324.43361e-05
20.5799356.35290
30.4582665.02011e-06
40.5119075.60770
50.3877474.24762.1e-05
60.3366743.68810.00017
70.3720924.07614.1e-05
80.1834222.00930.023375
90.397694.35651.4e-05
100.1915392.09820.018992
110.1990772.18080.015575
120.030020.32890.371419
130.1534881.68140.047645
140.0379630.41590.339125
15-0.022924-0.25110.401075
16-0.028274-0.30970.378652
17-0.03392-0.37160.355434
18-0.022545-0.2470.402679
19-0.034011-0.37260.355062
20-0.034335-0.37610.353748
21-0.03979-0.43590.331854
22-0.039918-0.43730.331346
23-0.032584-0.35690.360884
24-0.042925-0.47020.319524
25-0.041138-0.45060.326529
26-0.051519-0.56440.286782
27-0.023202-0.25420.399901
28-0.037812-0.41420.33973
29-0.017416-0.19080.424509
30-0.035966-0.3940.347146
31-0.021054-0.23060.408996
32-0.024128-0.26430.396
33-0.020191-0.22120.412662
34-0.012057-0.13210.44757
35-0.029347-0.32150.374202
360.0066680.0730.470946
37-0.031014-0.33970.367322
38-0.004634-0.05080.479798
39-0.015503-0.16980.432714
40-0.004164-0.04560.481848
41-0.019942-0.21850.413723
42-0.017567-0.19240.423864
43-0.019482-0.21340.415683
44-0.038958-0.42680.33516
45-0.03427-0.37540.354009
46-0.030153-0.33030.370872
47-0.043544-0.4770.317115
48-0.04744-0.51970.302122

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.404732 & 4.4336 & 1e-05 \tabularnewline
2 & 0.579935 & 6.3529 & 0 \tabularnewline
3 & 0.458266 & 5.0201 & 1e-06 \tabularnewline
4 & 0.511907 & 5.6077 & 0 \tabularnewline
5 & 0.387747 & 4.2476 & 2.1e-05 \tabularnewline
6 & 0.336674 & 3.6881 & 0.00017 \tabularnewline
7 & 0.372092 & 4.0761 & 4.1e-05 \tabularnewline
8 & 0.183422 & 2.0093 & 0.023375 \tabularnewline
9 & 0.39769 & 4.3565 & 1.4e-05 \tabularnewline
10 & 0.191539 & 2.0982 & 0.018992 \tabularnewline
11 & 0.199077 & 2.1808 & 0.015575 \tabularnewline
12 & 0.03002 & 0.3289 & 0.371419 \tabularnewline
13 & 0.153488 & 1.6814 & 0.047645 \tabularnewline
14 & 0.037963 & 0.4159 & 0.339125 \tabularnewline
15 & -0.022924 & -0.2511 & 0.401075 \tabularnewline
16 & -0.028274 & -0.3097 & 0.378652 \tabularnewline
17 & -0.03392 & -0.3716 & 0.355434 \tabularnewline
18 & -0.022545 & -0.247 & 0.402679 \tabularnewline
19 & -0.034011 & -0.3726 & 0.355062 \tabularnewline
20 & -0.034335 & -0.3761 & 0.353748 \tabularnewline
21 & -0.03979 & -0.4359 & 0.331854 \tabularnewline
22 & -0.039918 & -0.4373 & 0.331346 \tabularnewline
23 & -0.032584 & -0.3569 & 0.360884 \tabularnewline
24 & -0.042925 & -0.4702 & 0.319524 \tabularnewline
25 & -0.041138 & -0.4506 & 0.326529 \tabularnewline
26 & -0.051519 & -0.5644 & 0.286782 \tabularnewline
27 & -0.023202 & -0.2542 & 0.399901 \tabularnewline
28 & -0.037812 & -0.4142 & 0.33973 \tabularnewline
29 & -0.017416 & -0.1908 & 0.424509 \tabularnewline
30 & -0.035966 & -0.394 & 0.347146 \tabularnewline
31 & -0.021054 & -0.2306 & 0.408996 \tabularnewline
32 & -0.024128 & -0.2643 & 0.396 \tabularnewline
33 & -0.020191 & -0.2212 & 0.412662 \tabularnewline
34 & -0.012057 & -0.1321 & 0.44757 \tabularnewline
35 & -0.029347 & -0.3215 & 0.374202 \tabularnewline
36 & 0.006668 & 0.073 & 0.470946 \tabularnewline
37 & -0.031014 & -0.3397 & 0.367322 \tabularnewline
38 & -0.004634 & -0.0508 & 0.479798 \tabularnewline
39 & -0.015503 & -0.1698 & 0.432714 \tabularnewline
40 & -0.004164 & -0.0456 & 0.481848 \tabularnewline
41 & -0.019942 & -0.2185 & 0.413723 \tabularnewline
42 & -0.017567 & -0.1924 & 0.423864 \tabularnewline
43 & -0.019482 & -0.2134 & 0.415683 \tabularnewline
44 & -0.038958 & -0.4268 & 0.33516 \tabularnewline
45 & -0.03427 & -0.3754 & 0.354009 \tabularnewline
46 & -0.030153 & -0.3303 & 0.370872 \tabularnewline
47 & -0.043544 & -0.477 & 0.317115 \tabularnewline
48 & -0.04744 & -0.5197 & 0.302122 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75107&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]0.404732[/C][C]4.4336[/C][C]1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.579935[/C][C]6.3529[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.458266[/C][C]5.0201[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.511907[/C][C]5.6077[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.387747[/C][C]4.2476[/C][C]2.1e-05[/C][/ROW]
[ROW][C]6[/C][C]0.336674[/C][C]3.6881[/C][C]0.00017[/C][/ROW]
[ROW][C]7[/C][C]0.372092[/C][C]4.0761[/C][C]4.1e-05[/C][/ROW]
[ROW][C]8[/C][C]0.183422[/C][C]2.0093[/C][C]0.023375[/C][/ROW]
[ROW][C]9[/C][C]0.39769[/C][C]4.3565[/C][C]1.4e-05[/C][/ROW]
[ROW][C]10[/C][C]0.191539[/C][C]2.0982[/C][C]0.018992[/C][/ROW]
[ROW][C]11[/C][C]0.199077[/C][C]2.1808[/C][C]0.015575[/C][/ROW]
[ROW][C]12[/C][C]0.03002[/C][C]0.3289[/C][C]0.371419[/C][/ROW]
[ROW][C]13[/C][C]0.153488[/C][C]1.6814[/C][C]0.047645[/C][/ROW]
[ROW][C]14[/C][C]0.037963[/C][C]0.4159[/C][C]0.339125[/C][/ROW]
[ROW][C]15[/C][C]-0.022924[/C][C]-0.2511[/C][C]0.401075[/C][/ROW]
[ROW][C]16[/C][C]-0.028274[/C][C]-0.3097[/C][C]0.378652[/C][/ROW]
[ROW][C]17[/C][C]-0.03392[/C][C]-0.3716[/C][C]0.355434[/C][/ROW]
[ROW][C]18[/C][C]-0.022545[/C][C]-0.247[/C][C]0.402679[/C][/ROW]
[ROW][C]19[/C][C]-0.034011[/C][C]-0.3726[/C][C]0.355062[/C][/ROW]
[ROW][C]20[/C][C]-0.034335[/C][C]-0.3761[/C][C]0.353748[/C][/ROW]
[ROW][C]21[/C][C]-0.03979[/C][C]-0.4359[/C][C]0.331854[/C][/ROW]
[ROW][C]22[/C][C]-0.039918[/C][C]-0.4373[/C][C]0.331346[/C][/ROW]
[ROW][C]23[/C][C]-0.032584[/C][C]-0.3569[/C][C]0.360884[/C][/ROW]
[ROW][C]24[/C][C]-0.042925[/C][C]-0.4702[/C][C]0.319524[/C][/ROW]
[ROW][C]25[/C][C]-0.041138[/C][C]-0.4506[/C][C]0.326529[/C][/ROW]
[ROW][C]26[/C][C]-0.051519[/C][C]-0.5644[/C][C]0.286782[/C][/ROW]
[ROW][C]27[/C][C]-0.023202[/C][C]-0.2542[/C][C]0.399901[/C][/ROW]
[ROW][C]28[/C][C]-0.037812[/C][C]-0.4142[/C][C]0.33973[/C][/ROW]
[ROW][C]29[/C][C]-0.017416[/C][C]-0.1908[/C][C]0.424509[/C][/ROW]
[ROW][C]30[/C][C]-0.035966[/C][C]-0.394[/C][C]0.347146[/C][/ROW]
[ROW][C]31[/C][C]-0.021054[/C][C]-0.2306[/C][C]0.408996[/C][/ROW]
[ROW][C]32[/C][C]-0.024128[/C][C]-0.2643[/C][C]0.396[/C][/ROW]
[ROW][C]33[/C][C]-0.020191[/C][C]-0.2212[/C][C]0.412662[/C][/ROW]
[ROW][C]34[/C][C]-0.012057[/C][C]-0.1321[/C][C]0.44757[/C][/ROW]
[ROW][C]35[/C][C]-0.029347[/C][C]-0.3215[/C][C]0.374202[/C][/ROW]
[ROW][C]36[/C][C]0.006668[/C][C]0.073[/C][C]0.470946[/C][/ROW]
[ROW][C]37[/C][C]-0.031014[/C][C]-0.3397[/C][C]0.367322[/C][/ROW]
[ROW][C]38[/C][C]-0.004634[/C][C]-0.0508[/C][C]0.479798[/C][/ROW]
[ROW][C]39[/C][C]-0.015503[/C][C]-0.1698[/C][C]0.432714[/C][/ROW]
[ROW][C]40[/C][C]-0.004164[/C][C]-0.0456[/C][C]0.481848[/C][/ROW]
[ROW][C]41[/C][C]-0.019942[/C][C]-0.2185[/C][C]0.413723[/C][/ROW]
[ROW][C]42[/C][C]-0.017567[/C][C]-0.1924[/C][C]0.423864[/C][/ROW]
[ROW][C]43[/C][C]-0.019482[/C][C]-0.2134[/C][C]0.415683[/C][/ROW]
[ROW][C]44[/C][C]-0.038958[/C][C]-0.4268[/C][C]0.33516[/C][/ROW]
[ROW][C]45[/C][C]-0.03427[/C][C]-0.3754[/C][C]0.354009[/C][/ROW]
[ROW][C]46[/C][C]-0.030153[/C][C]-0.3303[/C][C]0.370872[/C][/ROW]
[ROW][C]47[/C][C]-0.043544[/C][C]-0.477[/C][C]0.317115[/C][/ROW]
[ROW][C]48[/C][C]-0.04744[/C][C]-0.5197[/C][C]0.302122[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75107&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75107&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
10.4047324.43361e-05
20.5799356.35290
30.4582665.02011e-06
40.5119075.60770
50.3877474.24762.1e-05
60.3366743.68810.00017
70.3720924.07614.1e-05
80.1834222.00930.023375
90.397694.35651.4e-05
100.1915392.09820.018992
110.1990772.18080.015575
120.030020.32890.371419
130.1534881.68140.047645
140.0379630.41590.339125
15-0.022924-0.25110.401075
16-0.028274-0.30970.378652
17-0.03392-0.37160.355434
18-0.022545-0.2470.402679
19-0.034011-0.37260.355062
20-0.034335-0.37610.353748
21-0.03979-0.43590.331854
22-0.039918-0.43730.331346
23-0.032584-0.35690.360884
24-0.042925-0.47020.319524
25-0.041138-0.45060.326529
26-0.051519-0.56440.286782
27-0.023202-0.25420.399901
28-0.037812-0.41420.33973
29-0.017416-0.19080.424509
30-0.035966-0.3940.347146
31-0.021054-0.23060.408996
32-0.024128-0.26430.396
33-0.020191-0.22120.412662
34-0.012057-0.13210.44757
35-0.029347-0.32150.374202
360.0066680.0730.470946
37-0.031014-0.33970.367322
38-0.004634-0.05080.479798
39-0.015503-0.16980.432714
40-0.004164-0.04560.481848
41-0.019942-0.21850.413723
42-0.017567-0.19240.423864
43-0.019482-0.21340.415683
44-0.038958-0.42680.33516
45-0.03427-0.37540.354009
46-0.030153-0.33030.370872
47-0.043544-0.4770.317115
48-0.04744-0.51970.302122







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4047324.43361e-05
20.4976465.45140
30.2208542.41930.008525
40.1957672.14450.017004
5-0.002617-0.02870.488587
6-0.131119-1.43630.076754
70.0441980.48420.314574
8-0.191238-2.09490.019141
90.2335382.55830.005882
100.0298990.32750.371919
11-0.150776-1.65170.050608
12-0.274757-3.00980.001593
13-0.039552-0.43330.3328
140.0307330.33670.368481
15-0.008615-0.09440.462487
16-0.035938-0.39370.347257
170.0962831.05470.146834
180.0072260.07920.468519
190.0651040.71320.238559
20-0.00867-0.0950.462245
210.1402111.53590.063594
22-0.003393-0.03720.485208
23-0.068694-0.75250.226612
24-0.040893-0.4480.327494
250.0627270.68710.246661
26-0.046022-0.50410.307541
27-0.025542-0.27980.390055
28-0.077197-0.84560.199716
290.0462540.50670.306652
30-0.075358-0.82550.20536
31-0.016845-0.18450.426955
320.0098260.10760.45723
330.0763390.83630.202338
34-0.003814-0.04180.483372
35-0.001123-0.01230.495101
360.049930.5470.292714
370.0329260.36070.359484
38-0.072295-0.79190.214977
390.0209690.22970.409357
400.0105190.11520.454226
410.0176790.19370.423382
42-0.083027-0.90950.182449
43-0.043139-0.47260.318691
44-0.02617-0.28670.387425
45-0.03586-0.39280.347571
46-0.01174-0.12860.448944
470.0330010.36150.359177
480.0112080.12280.451244

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.404732 & 4.4336 & 1e-05 \tabularnewline
2 & 0.497646 & 5.4514 & 0 \tabularnewline
3 & 0.220854 & 2.4193 & 0.008525 \tabularnewline
4 & 0.195767 & 2.1445 & 0.017004 \tabularnewline
5 & -0.002617 & -0.0287 & 0.488587 \tabularnewline
6 & -0.131119 & -1.4363 & 0.076754 \tabularnewline
7 & 0.044198 & 0.4842 & 0.314574 \tabularnewline
8 & -0.191238 & -2.0949 & 0.019141 \tabularnewline
9 & 0.233538 & 2.5583 & 0.005882 \tabularnewline
10 & 0.029899 & 0.3275 & 0.371919 \tabularnewline
11 & -0.150776 & -1.6517 & 0.050608 \tabularnewline
12 & -0.274757 & -3.0098 & 0.001593 \tabularnewline
13 & -0.039552 & -0.4333 & 0.3328 \tabularnewline
14 & 0.030733 & 0.3367 & 0.368481 \tabularnewline
15 & -0.008615 & -0.0944 & 0.462487 \tabularnewline
16 & -0.035938 & -0.3937 & 0.347257 \tabularnewline
17 & 0.096283 & 1.0547 & 0.146834 \tabularnewline
18 & 0.007226 & 0.0792 & 0.468519 \tabularnewline
19 & 0.065104 & 0.7132 & 0.238559 \tabularnewline
20 & -0.00867 & -0.095 & 0.462245 \tabularnewline
21 & 0.140211 & 1.5359 & 0.063594 \tabularnewline
22 & -0.003393 & -0.0372 & 0.485208 \tabularnewline
23 & -0.068694 & -0.7525 & 0.226612 \tabularnewline
24 & -0.040893 & -0.448 & 0.327494 \tabularnewline
25 & 0.062727 & 0.6871 & 0.246661 \tabularnewline
26 & -0.046022 & -0.5041 & 0.307541 \tabularnewline
27 & -0.025542 & -0.2798 & 0.390055 \tabularnewline
28 & -0.077197 & -0.8456 & 0.199716 \tabularnewline
29 & 0.046254 & 0.5067 & 0.306652 \tabularnewline
30 & -0.075358 & -0.8255 & 0.20536 \tabularnewline
31 & -0.016845 & -0.1845 & 0.426955 \tabularnewline
32 & 0.009826 & 0.1076 & 0.45723 \tabularnewline
33 & 0.076339 & 0.8363 & 0.202338 \tabularnewline
34 & -0.003814 & -0.0418 & 0.483372 \tabularnewline
35 & -0.001123 & -0.0123 & 0.495101 \tabularnewline
36 & 0.04993 & 0.547 & 0.292714 \tabularnewline
37 & 0.032926 & 0.3607 & 0.359484 \tabularnewline
38 & -0.072295 & -0.7919 & 0.214977 \tabularnewline
39 & 0.020969 & 0.2297 & 0.409357 \tabularnewline
40 & 0.010519 & 0.1152 & 0.454226 \tabularnewline
41 & 0.017679 & 0.1937 & 0.423382 \tabularnewline
42 & -0.083027 & -0.9095 & 0.182449 \tabularnewline
43 & -0.043139 & -0.4726 & 0.318691 \tabularnewline
44 & -0.02617 & -0.2867 & 0.387425 \tabularnewline
45 & -0.03586 & -0.3928 & 0.347571 \tabularnewline
46 & -0.01174 & -0.1286 & 0.448944 \tabularnewline
47 & 0.033001 & 0.3615 & 0.359177 \tabularnewline
48 & 0.011208 & 0.1228 & 0.451244 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75107&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]0.404732[/C][C]4.4336[/C][C]1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.497646[/C][C]5.4514[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.220854[/C][C]2.4193[/C][C]0.008525[/C][/ROW]
[ROW][C]4[/C][C]0.195767[/C][C]2.1445[/C][C]0.017004[/C][/ROW]
[ROW][C]5[/C][C]-0.002617[/C][C]-0.0287[/C][C]0.488587[/C][/ROW]
[ROW][C]6[/C][C]-0.131119[/C][C]-1.4363[/C][C]0.076754[/C][/ROW]
[ROW][C]7[/C][C]0.044198[/C][C]0.4842[/C][C]0.314574[/C][/ROW]
[ROW][C]8[/C][C]-0.191238[/C][C]-2.0949[/C][C]0.019141[/C][/ROW]
[ROW][C]9[/C][C]0.233538[/C][C]2.5583[/C][C]0.005882[/C][/ROW]
[ROW][C]10[/C][C]0.029899[/C][C]0.3275[/C][C]0.371919[/C][/ROW]
[ROW][C]11[/C][C]-0.150776[/C][C]-1.6517[/C][C]0.050608[/C][/ROW]
[ROW][C]12[/C][C]-0.274757[/C][C]-3.0098[/C][C]0.001593[/C][/ROW]
[ROW][C]13[/C][C]-0.039552[/C][C]-0.4333[/C][C]0.3328[/C][/ROW]
[ROW][C]14[/C][C]0.030733[/C][C]0.3367[/C][C]0.368481[/C][/ROW]
[ROW][C]15[/C][C]-0.008615[/C][C]-0.0944[/C][C]0.462487[/C][/ROW]
[ROW][C]16[/C][C]-0.035938[/C][C]-0.3937[/C][C]0.347257[/C][/ROW]
[ROW][C]17[/C][C]0.096283[/C][C]1.0547[/C][C]0.146834[/C][/ROW]
[ROW][C]18[/C][C]0.007226[/C][C]0.0792[/C][C]0.468519[/C][/ROW]
[ROW][C]19[/C][C]0.065104[/C][C]0.7132[/C][C]0.238559[/C][/ROW]
[ROW][C]20[/C][C]-0.00867[/C][C]-0.095[/C][C]0.462245[/C][/ROW]
[ROW][C]21[/C][C]0.140211[/C][C]1.5359[/C][C]0.063594[/C][/ROW]
[ROW][C]22[/C][C]-0.003393[/C][C]-0.0372[/C][C]0.485208[/C][/ROW]
[ROW][C]23[/C][C]-0.068694[/C][C]-0.7525[/C][C]0.226612[/C][/ROW]
[ROW][C]24[/C][C]-0.040893[/C][C]-0.448[/C][C]0.327494[/C][/ROW]
[ROW][C]25[/C][C]0.062727[/C][C]0.6871[/C][C]0.246661[/C][/ROW]
[ROW][C]26[/C][C]-0.046022[/C][C]-0.5041[/C][C]0.307541[/C][/ROW]
[ROW][C]27[/C][C]-0.025542[/C][C]-0.2798[/C][C]0.390055[/C][/ROW]
[ROW][C]28[/C][C]-0.077197[/C][C]-0.8456[/C][C]0.199716[/C][/ROW]
[ROW][C]29[/C][C]0.046254[/C][C]0.5067[/C][C]0.306652[/C][/ROW]
[ROW][C]30[/C][C]-0.075358[/C][C]-0.8255[/C][C]0.20536[/C][/ROW]
[ROW][C]31[/C][C]-0.016845[/C][C]-0.1845[/C][C]0.426955[/C][/ROW]
[ROW][C]32[/C][C]0.009826[/C][C]0.1076[/C][C]0.45723[/C][/ROW]
[ROW][C]33[/C][C]0.076339[/C][C]0.8363[/C][C]0.202338[/C][/ROW]
[ROW][C]34[/C][C]-0.003814[/C][C]-0.0418[/C][C]0.483372[/C][/ROW]
[ROW][C]35[/C][C]-0.001123[/C][C]-0.0123[/C][C]0.495101[/C][/ROW]
[ROW][C]36[/C][C]0.04993[/C][C]0.547[/C][C]0.292714[/C][/ROW]
[ROW][C]37[/C][C]0.032926[/C][C]0.3607[/C][C]0.359484[/C][/ROW]
[ROW][C]38[/C][C]-0.072295[/C][C]-0.7919[/C][C]0.214977[/C][/ROW]
[ROW][C]39[/C][C]0.020969[/C][C]0.2297[/C][C]0.409357[/C][/ROW]
[ROW][C]40[/C][C]0.010519[/C][C]0.1152[/C][C]0.454226[/C][/ROW]
[ROW][C]41[/C][C]0.017679[/C][C]0.1937[/C][C]0.423382[/C][/ROW]
[ROW][C]42[/C][C]-0.083027[/C][C]-0.9095[/C][C]0.182449[/C][/ROW]
[ROW][C]43[/C][C]-0.043139[/C][C]-0.4726[/C][C]0.318691[/C][/ROW]
[ROW][C]44[/C][C]-0.02617[/C][C]-0.2867[/C][C]0.387425[/C][/ROW]
[ROW][C]45[/C][C]-0.03586[/C][C]-0.3928[/C][C]0.347571[/C][/ROW]
[ROW][C]46[/C][C]-0.01174[/C][C]-0.1286[/C][C]0.448944[/C][/ROW]
[ROW][C]47[/C][C]0.033001[/C][C]0.3615[/C][C]0.359177[/C][/ROW]
[ROW][C]48[/C][C]0.011208[/C][C]0.1228[/C][C]0.451244[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75107&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75107&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
10.4047324.43361e-05
20.4976465.45140
30.2208542.41930.008525
40.1957672.14450.017004
5-0.002617-0.02870.488587
6-0.131119-1.43630.076754
70.0441980.48420.314574
8-0.191238-2.09490.019141
90.2335382.55830.005882
100.0298990.32750.371919
11-0.150776-1.65170.050608
12-0.274757-3.00980.001593
13-0.039552-0.43330.3328
140.0307330.33670.368481
15-0.008615-0.09440.462487
16-0.035938-0.39370.347257
170.0962831.05470.146834
180.0072260.07920.468519
190.0651040.71320.238559
20-0.00867-0.0950.462245
210.1402111.53590.063594
22-0.003393-0.03720.485208
23-0.068694-0.75250.226612
24-0.040893-0.4480.327494
250.0627270.68710.246661
26-0.046022-0.50410.307541
27-0.025542-0.27980.390055
28-0.077197-0.84560.199716
290.0462540.50670.306652
30-0.075358-0.82550.20536
31-0.016845-0.18450.426955
320.0098260.10760.45723
330.0763390.83630.202338
34-0.003814-0.04180.483372
35-0.001123-0.01230.495101
360.049930.5470.292714
370.0329260.36070.359484
38-0.072295-0.79190.214977
390.0209690.22970.409357
400.0105190.11520.454226
410.0176790.19370.423382
42-0.083027-0.90950.182449
43-0.043139-0.47260.318691
44-0.02617-0.28670.387425
45-0.03586-0.39280.347571
46-0.01174-0.12860.448944
470.0330010.36150.359177
480.0112080.12280.451244



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')