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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 10 Jan 2011 20:58:25 +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/2011/Jan/10/t1294693053ir71n1dx3q9oarr.htm/, Retrieved Sun, 28 Apr 2024 19:08:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=117300, Retrieved Sun, 28 Apr 2024 19:08:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact248
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Monthly US soldie...] [2010-11-02 12:07:39] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Soldiers] [2010-11-29 09:48:36] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [Workshop 9] [2010-12-14 12:34:06] [20c5a34fea7ed3b9b27ff444f2eb4dfe]
- R P         [(Partial) Autocorrelation Function] [] [2011-01-10 20:58:25] [062de5fc17e30860c0960288bdb996a8] [Current]
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Dataseries X:
921365
987921
1132614
1332224
1418133
1411549
1695920
1636173
1539653
1395314
1127575
1036076
989236
1008380
1207763
1368839
1469798
1498721
1761769
1653214
1599104
1421179
1163995
1037735
1015407
1039210
1258049
1469445
1552346
1549144
1785895
1662335
1629440
1467430
1202209
1076982
1039367
1063449
1335135
1491602
1591972
1641248
1898849
1798580
1762444
1622044
1368955
1262973
1195650
1269530
1479279
1607819
1712466
1721766
1949843
1821326
1757802
1590367
1260647
1149235
1016367
1027885
1262159
1520854
1544144
1564709
1821776
1741365
1623386
1498658
1241822
1136029




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=117300&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=117300&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117300&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
10.9137647.0780
20.8502986.58640
30.7833886.06810
40.6895555.34131e-06
50.5622254.3552.6e-05
60.4540123.51680.000419
70.3366652.60780.005741
80.2070311.60370.057021
90.0687840.53280.298069
10-0.038804-0.30060.38239
11-0.145498-1.1270.132111
12-0.248504-1.92490.029493
13-0.304003-2.35480.010911
14-0.332273-2.57380.006274
15-0.364008-2.81960.003253
16-0.367278-2.84490.003034
17-0.365177-2.82870.003173
18-0.342493-2.65290.005098
19-0.324082-2.51030.007388
20-0.275004-2.13020.018633
21-0.222699-1.7250.044836
22-0.190592-1.47630.072544
23-0.161662-1.25220.107673
24-0.120754-0.93540.176678
25-0.078808-0.61040.271938
26-0.061416-0.47570.317999
27-0.039906-0.30910.379155
28-0.019158-0.14840.441262
290.0061360.04750.481124
300.0002790.00220.499142
31-0.00392-0.03040.487937
32-0.010789-0.08360.466837
33-0.028387-0.21990.413353
34-0.034241-0.26520.39587
35-0.023057-0.17860.429426
36-0.029752-0.23050.40926
37-0.03116-0.24140.405047
38-0.041011-0.31770.375919
39-0.049883-0.38640.350287
40-0.066827-0.51760.303307
41-0.077869-0.60320.274334
42-0.080061-0.62020.268753
43-0.078222-0.60590.273431
44-0.094804-0.73430.232799
45-0.078338-0.60680.273135
46-0.080681-0.62490.267187
47-0.086209-0.66780.25342
48-0.088334-0.68420.24823
49-0.07375-0.57130.284976
50-0.071637-0.55490.290514
51-0.060197-0.46630.321351
52-0.053181-0.41190.340925
53-0.039176-0.30350.381296
54-0.034111-0.26420.396256
55-0.020368-0.15780.437585
56-0.016287-0.12620.450014
57-0.011912-0.09230.463395
58-0.003073-0.02380.490545
59-0.002779-0.02150.491449
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.913764 & 7.078 & 0 \tabularnewline
2 & 0.850298 & 6.5864 & 0 \tabularnewline
3 & 0.783388 & 6.0681 & 0 \tabularnewline
4 & 0.689555 & 5.3413 & 1e-06 \tabularnewline
5 & 0.562225 & 4.355 & 2.6e-05 \tabularnewline
6 & 0.454012 & 3.5168 & 0.000419 \tabularnewline
7 & 0.336665 & 2.6078 & 0.005741 \tabularnewline
8 & 0.207031 & 1.6037 & 0.057021 \tabularnewline
9 & 0.068784 & 0.5328 & 0.298069 \tabularnewline
10 & -0.038804 & -0.3006 & 0.38239 \tabularnewline
11 & -0.145498 & -1.127 & 0.132111 \tabularnewline
12 & -0.248504 & -1.9249 & 0.029493 \tabularnewline
13 & -0.304003 & -2.3548 & 0.010911 \tabularnewline
14 & -0.332273 & -2.5738 & 0.006274 \tabularnewline
15 & -0.364008 & -2.8196 & 0.003253 \tabularnewline
16 & -0.367278 & -2.8449 & 0.003034 \tabularnewline
17 & -0.365177 & -2.8287 & 0.003173 \tabularnewline
18 & -0.342493 & -2.6529 & 0.005098 \tabularnewline
19 & -0.324082 & -2.5103 & 0.007388 \tabularnewline
20 & -0.275004 & -2.1302 & 0.018633 \tabularnewline
21 & -0.222699 & -1.725 & 0.044836 \tabularnewline
22 & -0.190592 & -1.4763 & 0.072544 \tabularnewline
23 & -0.161662 & -1.2522 & 0.107673 \tabularnewline
24 & -0.120754 & -0.9354 & 0.176678 \tabularnewline
25 & -0.078808 & -0.6104 & 0.271938 \tabularnewline
26 & -0.061416 & -0.4757 & 0.317999 \tabularnewline
27 & -0.039906 & -0.3091 & 0.379155 \tabularnewline
28 & -0.019158 & -0.1484 & 0.441262 \tabularnewline
29 & 0.006136 & 0.0475 & 0.481124 \tabularnewline
30 & 0.000279 & 0.0022 & 0.499142 \tabularnewline
31 & -0.00392 & -0.0304 & 0.487937 \tabularnewline
32 & -0.010789 & -0.0836 & 0.466837 \tabularnewline
33 & -0.028387 & -0.2199 & 0.413353 \tabularnewline
34 & -0.034241 & -0.2652 & 0.39587 \tabularnewline
35 & -0.023057 & -0.1786 & 0.429426 \tabularnewline
36 & -0.029752 & -0.2305 & 0.40926 \tabularnewline
37 & -0.03116 & -0.2414 & 0.405047 \tabularnewline
38 & -0.041011 & -0.3177 & 0.375919 \tabularnewline
39 & -0.049883 & -0.3864 & 0.350287 \tabularnewline
40 & -0.066827 & -0.5176 & 0.303307 \tabularnewline
41 & -0.077869 & -0.6032 & 0.274334 \tabularnewline
42 & -0.080061 & -0.6202 & 0.268753 \tabularnewline
43 & -0.078222 & -0.6059 & 0.273431 \tabularnewline
44 & -0.094804 & -0.7343 & 0.232799 \tabularnewline
45 & -0.078338 & -0.6068 & 0.273135 \tabularnewline
46 & -0.080681 & -0.6249 & 0.267187 \tabularnewline
47 & -0.086209 & -0.6678 & 0.25342 \tabularnewline
48 & -0.088334 & -0.6842 & 0.24823 \tabularnewline
49 & -0.07375 & -0.5713 & 0.284976 \tabularnewline
50 & -0.071637 & -0.5549 & 0.290514 \tabularnewline
51 & -0.060197 & -0.4663 & 0.321351 \tabularnewline
52 & -0.053181 & -0.4119 & 0.340925 \tabularnewline
53 & -0.039176 & -0.3035 & 0.381296 \tabularnewline
54 & -0.034111 & -0.2642 & 0.396256 \tabularnewline
55 & -0.020368 & -0.1578 & 0.437585 \tabularnewline
56 & -0.016287 & -0.1262 & 0.450014 \tabularnewline
57 & -0.011912 & -0.0923 & 0.463395 \tabularnewline
58 & -0.003073 & -0.0238 & 0.490545 \tabularnewline
59 & -0.002779 & -0.0215 & 0.491449 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117300&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]0.913764[/C][C]7.078[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.850298[/C][C]6.5864[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.783388[/C][C]6.0681[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.689555[/C][C]5.3413[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.562225[/C][C]4.355[/C][C]2.6e-05[/C][/ROW]
[ROW][C]6[/C][C]0.454012[/C][C]3.5168[/C][C]0.000419[/C][/ROW]
[ROW][C]7[/C][C]0.336665[/C][C]2.6078[/C][C]0.005741[/C][/ROW]
[ROW][C]8[/C][C]0.207031[/C][C]1.6037[/C][C]0.057021[/C][/ROW]
[ROW][C]9[/C][C]0.068784[/C][C]0.5328[/C][C]0.298069[/C][/ROW]
[ROW][C]10[/C][C]-0.038804[/C][C]-0.3006[/C][C]0.38239[/C][/ROW]
[ROW][C]11[/C][C]-0.145498[/C][C]-1.127[/C][C]0.132111[/C][/ROW]
[ROW][C]12[/C][C]-0.248504[/C][C]-1.9249[/C][C]0.029493[/C][/ROW]
[ROW][C]13[/C][C]-0.304003[/C][C]-2.3548[/C][C]0.010911[/C][/ROW]
[ROW][C]14[/C][C]-0.332273[/C][C]-2.5738[/C][C]0.006274[/C][/ROW]
[ROW][C]15[/C][C]-0.364008[/C][C]-2.8196[/C][C]0.003253[/C][/ROW]
[ROW][C]16[/C][C]-0.367278[/C][C]-2.8449[/C][C]0.003034[/C][/ROW]
[ROW][C]17[/C][C]-0.365177[/C][C]-2.8287[/C][C]0.003173[/C][/ROW]
[ROW][C]18[/C][C]-0.342493[/C][C]-2.6529[/C][C]0.005098[/C][/ROW]
[ROW][C]19[/C][C]-0.324082[/C][C]-2.5103[/C][C]0.007388[/C][/ROW]
[ROW][C]20[/C][C]-0.275004[/C][C]-2.1302[/C][C]0.018633[/C][/ROW]
[ROW][C]21[/C][C]-0.222699[/C][C]-1.725[/C][C]0.044836[/C][/ROW]
[ROW][C]22[/C][C]-0.190592[/C][C]-1.4763[/C][C]0.072544[/C][/ROW]
[ROW][C]23[/C][C]-0.161662[/C][C]-1.2522[/C][C]0.107673[/C][/ROW]
[ROW][C]24[/C][C]-0.120754[/C][C]-0.9354[/C][C]0.176678[/C][/ROW]
[ROW][C]25[/C][C]-0.078808[/C][C]-0.6104[/C][C]0.271938[/C][/ROW]
[ROW][C]26[/C][C]-0.061416[/C][C]-0.4757[/C][C]0.317999[/C][/ROW]
[ROW][C]27[/C][C]-0.039906[/C][C]-0.3091[/C][C]0.379155[/C][/ROW]
[ROW][C]28[/C][C]-0.019158[/C][C]-0.1484[/C][C]0.441262[/C][/ROW]
[ROW][C]29[/C][C]0.006136[/C][C]0.0475[/C][C]0.481124[/C][/ROW]
[ROW][C]30[/C][C]0.000279[/C][C]0.0022[/C][C]0.499142[/C][/ROW]
[ROW][C]31[/C][C]-0.00392[/C][C]-0.0304[/C][C]0.487937[/C][/ROW]
[ROW][C]32[/C][C]-0.010789[/C][C]-0.0836[/C][C]0.466837[/C][/ROW]
[ROW][C]33[/C][C]-0.028387[/C][C]-0.2199[/C][C]0.413353[/C][/ROW]
[ROW][C]34[/C][C]-0.034241[/C][C]-0.2652[/C][C]0.39587[/C][/ROW]
[ROW][C]35[/C][C]-0.023057[/C][C]-0.1786[/C][C]0.429426[/C][/ROW]
[ROW][C]36[/C][C]-0.029752[/C][C]-0.2305[/C][C]0.40926[/C][/ROW]
[ROW][C]37[/C][C]-0.03116[/C][C]-0.2414[/C][C]0.405047[/C][/ROW]
[ROW][C]38[/C][C]-0.041011[/C][C]-0.3177[/C][C]0.375919[/C][/ROW]
[ROW][C]39[/C][C]-0.049883[/C][C]-0.3864[/C][C]0.350287[/C][/ROW]
[ROW][C]40[/C][C]-0.066827[/C][C]-0.5176[/C][C]0.303307[/C][/ROW]
[ROW][C]41[/C][C]-0.077869[/C][C]-0.6032[/C][C]0.274334[/C][/ROW]
[ROW][C]42[/C][C]-0.080061[/C][C]-0.6202[/C][C]0.268753[/C][/ROW]
[ROW][C]43[/C][C]-0.078222[/C][C]-0.6059[/C][C]0.273431[/C][/ROW]
[ROW][C]44[/C][C]-0.094804[/C][C]-0.7343[/C][C]0.232799[/C][/ROW]
[ROW][C]45[/C][C]-0.078338[/C][C]-0.6068[/C][C]0.273135[/C][/ROW]
[ROW][C]46[/C][C]-0.080681[/C][C]-0.6249[/C][C]0.267187[/C][/ROW]
[ROW][C]47[/C][C]-0.086209[/C][C]-0.6678[/C][C]0.25342[/C][/ROW]
[ROW][C]48[/C][C]-0.088334[/C][C]-0.6842[/C][C]0.24823[/C][/ROW]
[ROW][C]49[/C][C]-0.07375[/C][C]-0.5713[/C][C]0.284976[/C][/ROW]
[ROW][C]50[/C][C]-0.071637[/C][C]-0.5549[/C][C]0.290514[/C][/ROW]
[ROW][C]51[/C][C]-0.060197[/C][C]-0.4663[/C][C]0.321351[/C][/ROW]
[ROW][C]52[/C][C]-0.053181[/C][C]-0.4119[/C][C]0.340925[/C][/ROW]
[ROW][C]53[/C][C]-0.039176[/C][C]-0.3035[/C][C]0.381296[/C][/ROW]
[ROW][C]54[/C][C]-0.034111[/C][C]-0.2642[/C][C]0.396256[/C][/ROW]
[ROW][C]55[/C][C]-0.020368[/C][C]-0.1578[/C][C]0.437585[/C][/ROW]
[ROW][C]56[/C][C]-0.016287[/C][C]-0.1262[/C][C]0.450014[/C][/ROW]
[ROW][C]57[/C][C]-0.011912[/C][C]-0.0923[/C][C]0.463395[/C][/ROW]
[ROW][C]58[/C][C]-0.003073[/C][C]-0.0238[/C][C]0.490545[/C][/ROW]
[ROW][C]59[/C][C]-0.002779[/C][C]-0.0215[/C][C]0.491449[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117300&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117300&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
10.9137647.0780
20.8502986.58640
30.7833886.06810
40.6895555.34131e-06
50.5622254.3552.6e-05
60.4540123.51680.000419
70.3366652.60780.005741
80.2070311.60370.057021
90.0687840.53280.298069
10-0.038804-0.30060.38239
11-0.145498-1.1270.132111
12-0.248504-1.92490.029493
13-0.304003-2.35480.010911
14-0.332273-2.57380.006274
15-0.364008-2.81960.003253
16-0.367278-2.84490.003034
17-0.365177-2.82870.003173
18-0.342493-2.65290.005098
19-0.324082-2.51030.007388
20-0.275004-2.13020.018633
21-0.222699-1.7250.044836
22-0.190592-1.47630.072544
23-0.161662-1.25220.107673
24-0.120754-0.93540.176678
25-0.078808-0.61040.271938
26-0.061416-0.47570.317999
27-0.039906-0.30910.379155
28-0.019158-0.14840.441262
290.0061360.04750.481124
300.0002790.00220.499142
31-0.00392-0.03040.487937
32-0.010789-0.08360.466837
33-0.028387-0.21990.413353
34-0.034241-0.26520.39587
35-0.023057-0.17860.429426
36-0.029752-0.23050.40926
37-0.03116-0.24140.405047
38-0.041011-0.31770.375919
39-0.049883-0.38640.350287
40-0.066827-0.51760.303307
41-0.077869-0.60320.274334
42-0.080061-0.62020.268753
43-0.078222-0.60590.273431
44-0.094804-0.73430.232799
45-0.078338-0.60680.273135
46-0.080681-0.62490.267187
47-0.086209-0.66780.25342
48-0.088334-0.68420.24823
49-0.07375-0.57130.284976
50-0.071637-0.55490.290514
51-0.060197-0.46630.321351
52-0.053181-0.41190.340925
53-0.039176-0.30350.381296
54-0.034111-0.26420.396256
55-0.020368-0.15780.437585
56-0.016287-0.12620.450014
57-0.011912-0.09230.463395
58-0.003073-0.02380.490545
59-0.002779-0.02150.491449
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9137647.0780
20.0929090.71970.23726
3-0.038457-0.29790.383409
4-0.205256-1.58990.058556
5-0.314363-2.4350.00894
6-0.036057-0.27930.390488
7-0.081024-0.62760.26632
8-0.112653-0.87260.193178
9-0.175804-1.36180.089181
100.0240150.1860.426529
11-0.008733-0.06760.473147
12-0.038798-0.30050.382407
130.1956061.51520.067492
140.1460841.13160.131161
15-0.007059-0.05470.478287
160.0373870.28960.386561
17-0.156194-1.20990.115536
180.0008240.00640.497464
19-0.087048-0.67430.251365
200.0642480.49770.31027
21-0.007488-0.0580.476971
22-0.184924-1.43240.078608
23-0.106363-0.82390.206634
24-0.044102-0.34160.366918
250.1979241.53310.065252
260.0083460.06460.474336
270.0037940.02940.488328
28-0.026748-0.20720.418282
290.0880670.68220.248881
30-0.074439-0.57660.283183
31-0.097494-0.75520.226547
32-0.052354-0.40550.343264
33-0.052853-0.40940.341854
340.0621710.48160.315929
350.1064790.82480.206382
36-0.083981-0.65050.258922
370.0558540.43260.333411
38-0.098745-0.76490.223673
39-0.061124-0.47350.318799
40-0.059607-0.46170.322979
41-0.06122-0.47420.318537
420.0479380.37130.355851
43-0.006272-0.04860.480708
44-0.057828-0.44790.327906
450.0768870.59560.276853
46-0.023732-0.18380.427384
470.07190.55690.289823
480.0234710.18180.428173
490.0365430.28310.389053
50-0.138052-1.06930.144599
51-0.031625-0.2450.403659
52-0.029692-0.230.40944
53-0.025466-0.19730.422145
540.0235320.18230.427991
55-0.037076-0.28720.387477
56-0.11864-0.9190.180892
57-0.004518-0.0350.486101
580.072720.56330.28767
59-0.030339-0.2350.407502
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.913764 & 7.078 & 0 \tabularnewline
2 & 0.092909 & 0.7197 & 0.23726 \tabularnewline
3 & -0.038457 & -0.2979 & 0.383409 \tabularnewline
4 & -0.205256 & -1.5899 & 0.058556 \tabularnewline
5 & -0.314363 & -2.435 & 0.00894 \tabularnewline
6 & -0.036057 & -0.2793 & 0.390488 \tabularnewline
7 & -0.081024 & -0.6276 & 0.26632 \tabularnewline
8 & -0.112653 & -0.8726 & 0.193178 \tabularnewline
9 & -0.175804 & -1.3618 & 0.089181 \tabularnewline
10 & 0.024015 & 0.186 & 0.426529 \tabularnewline
11 & -0.008733 & -0.0676 & 0.473147 \tabularnewline
12 & -0.038798 & -0.3005 & 0.382407 \tabularnewline
13 & 0.195606 & 1.5152 & 0.067492 \tabularnewline
14 & 0.146084 & 1.1316 & 0.131161 \tabularnewline
15 & -0.007059 & -0.0547 & 0.478287 \tabularnewline
16 & 0.037387 & 0.2896 & 0.386561 \tabularnewline
17 & -0.156194 & -1.2099 & 0.115536 \tabularnewline
18 & 0.000824 & 0.0064 & 0.497464 \tabularnewline
19 & -0.087048 & -0.6743 & 0.251365 \tabularnewline
20 & 0.064248 & 0.4977 & 0.31027 \tabularnewline
21 & -0.007488 & -0.058 & 0.476971 \tabularnewline
22 & -0.184924 & -1.4324 & 0.078608 \tabularnewline
23 & -0.106363 & -0.8239 & 0.206634 \tabularnewline
24 & -0.044102 & -0.3416 & 0.366918 \tabularnewline
25 & 0.197924 & 1.5331 & 0.065252 \tabularnewline
26 & 0.008346 & 0.0646 & 0.474336 \tabularnewline
27 & 0.003794 & 0.0294 & 0.488328 \tabularnewline
28 & -0.026748 & -0.2072 & 0.418282 \tabularnewline
29 & 0.088067 & 0.6822 & 0.248881 \tabularnewline
30 & -0.074439 & -0.5766 & 0.283183 \tabularnewline
31 & -0.097494 & -0.7552 & 0.226547 \tabularnewline
32 & -0.052354 & -0.4055 & 0.343264 \tabularnewline
33 & -0.052853 & -0.4094 & 0.341854 \tabularnewline
34 & 0.062171 & 0.4816 & 0.315929 \tabularnewline
35 & 0.106479 & 0.8248 & 0.206382 \tabularnewline
36 & -0.083981 & -0.6505 & 0.258922 \tabularnewline
37 & 0.055854 & 0.4326 & 0.333411 \tabularnewline
38 & -0.098745 & -0.7649 & 0.223673 \tabularnewline
39 & -0.061124 & -0.4735 & 0.318799 \tabularnewline
40 & -0.059607 & -0.4617 & 0.322979 \tabularnewline
41 & -0.06122 & -0.4742 & 0.318537 \tabularnewline
42 & 0.047938 & 0.3713 & 0.355851 \tabularnewline
43 & -0.006272 & -0.0486 & 0.480708 \tabularnewline
44 & -0.057828 & -0.4479 & 0.327906 \tabularnewline
45 & 0.076887 & 0.5956 & 0.276853 \tabularnewline
46 & -0.023732 & -0.1838 & 0.427384 \tabularnewline
47 & 0.0719 & 0.5569 & 0.289823 \tabularnewline
48 & 0.023471 & 0.1818 & 0.428173 \tabularnewline
49 & 0.036543 & 0.2831 & 0.389053 \tabularnewline
50 & -0.138052 & -1.0693 & 0.144599 \tabularnewline
51 & -0.031625 & -0.245 & 0.403659 \tabularnewline
52 & -0.029692 & -0.23 & 0.40944 \tabularnewline
53 & -0.025466 & -0.1973 & 0.422145 \tabularnewline
54 & 0.023532 & 0.1823 & 0.427991 \tabularnewline
55 & -0.037076 & -0.2872 & 0.387477 \tabularnewline
56 & -0.11864 & -0.919 & 0.180892 \tabularnewline
57 & -0.004518 & -0.035 & 0.486101 \tabularnewline
58 & 0.07272 & 0.5633 & 0.28767 \tabularnewline
59 & -0.030339 & -0.235 & 0.407502 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117300&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]0.913764[/C][C]7.078[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.092909[/C][C]0.7197[/C][C]0.23726[/C][/ROW]
[ROW][C]3[/C][C]-0.038457[/C][C]-0.2979[/C][C]0.383409[/C][/ROW]
[ROW][C]4[/C][C]-0.205256[/C][C]-1.5899[/C][C]0.058556[/C][/ROW]
[ROW][C]5[/C][C]-0.314363[/C][C]-2.435[/C][C]0.00894[/C][/ROW]
[ROW][C]6[/C][C]-0.036057[/C][C]-0.2793[/C][C]0.390488[/C][/ROW]
[ROW][C]7[/C][C]-0.081024[/C][C]-0.6276[/C][C]0.26632[/C][/ROW]
[ROW][C]8[/C][C]-0.112653[/C][C]-0.8726[/C][C]0.193178[/C][/ROW]
[ROW][C]9[/C][C]-0.175804[/C][C]-1.3618[/C][C]0.089181[/C][/ROW]
[ROW][C]10[/C][C]0.024015[/C][C]0.186[/C][C]0.426529[/C][/ROW]
[ROW][C]11[/C][C]-0.008733[/C][C]-0.0676[/C][C]0.473147[/C][/ROW]
[ROW][C]12[/C][C]-0.038798[/C][C]-0.3005[/C][C]0.382407[/C][/ROW]
[ROW][C]13[/C][C]0.195606[/C][C]1.5152[/C][C]0.067492[/C][/ROW]
[ROW][C]14[/C][C]0.146084[/C][C]1.1316[/C][C]0.131161[/C][/ROW]
[ROW][C]15[/C][C]-0.007059[/C][C]-0.0547[/C][C]0.478287[/C][/ROW]
[ROW][C]16[/C][C]0.037387[/C][C]0.2896[/C][C]0.386561[/C][/ROW]
[ROW][C]17[/C][C]-0.156194[/C][C]-1.2099[/C][C]0.115536[/C][/ROW]
[ROW][C]18[/C][C]0.000824[/C][C]0.0064[/C][C]0.497464[/C][/ROW]
[ROW][C]19[/C][C]-0.087048[/C][C]-0.6743[/C][C]0.251365[/C][/ROW]
[ROW][C]20[/C][C]0.064248[/C][C]0.4977[/C][C]0.31027[/C][/ROW]
[ROW][C]21[/C][C]-0.007488[/C][C]-0.058[/C][C]0.476971[/C][/ROW]
[ROW][C]22[/C][C]-0.184924[/C][C]-1.4324[/C][C]0.078608[/C][/ROW]
[ROW][C]23[/C][C]-0.106363[/C][C]-0.8239[/C][C]0.206634[/C][/ROW]
[ROW][C]24[/C][C]-0.044102[/C][C]-0.3416[/C][C]0.366918[/C][/ROW]
[ROW][C]25[/C][C]0.197924[/C][C]1.5331[/C][C]0.065252[/C][/ROW]
[ROW][C]26[/C][C]0.008346[/C][C]0.0646[/C][C]0.474336[/C][/ROW]
[ROW][C]27[/C][C]0.003794[/C][C]0.0294[/C][C]0.488328[/C][/ROW]
[ROW][C]28[/C][C]-0.026748[/C][C]-0.2072[/C][C]0.418282[/C][/ROW]
[ROW][C]29[/C][C]0.088067[/C][C]0.6822[/C][C]0.248881[/C][/ROW]
[ROW][C]30[/C][C]-0.074439[/C][C]-0.5766[/C][C]0.283183[/C][/ROW]
[ROW][C]31[/C][C]-0.097494[/C][C]-0.7552[/C][C]0.226547[/C][/ROW]
[ROW][C]32[/C][C]-0.052354[/C][C]-0.4055[/C][C]0.343264[/C][/ROW]
[ROW][C]33[/C][C]-0.052853[/C][C]-0.4094[/C][C]0.341854[/C][/ROW]
[ROW][C]34[/C][C]0.062171[/C][C]0.4816[/C][C]0.315929[/C][/ROW]
[ROW][C]35[/C][C]0.106479[/C][C]0.8248[/C][C]0.206382[/C][/ROW]
[ROW][C]36[/C][C]-0.083981[/C][C]-0.6505[/C][C]0.258922[/C][/ROW]
[ROW][C]37[/C][C]0.055854[/C][C]0.4326[/C][C]0.333411[/C][/ROW]
[ROW][C]38[/C][C]-0.098745[/C][C]-0.7649[/C][C]0.223673[/C][/ROW]
[ROW][C]39[/C][C]-0.061124[/C][C]-0.4735[/C][C]0.318799[/C][/ROW]
[ROW][C]40[/C][C]-0.059607[/C][C]-0.4617[/C][C]0.322979[/C][/ROW]
[ROW][C]41[/C][C]-0.06122[/C][C]-0.4742[/C][C]0.318537[/C][/ROW]
[ROW][C]42[/C][C]0.047938[/C][C]0.3713[/C][C]0.355851[/C][/ROW]
[ROW][C]43[/C][C]-0.006272[/C][C]-0.0486[/C][C]0.480708[/C][/ROW]
[ROW][C]44[/C][C]-0.057828[/C][C]-0.4479[/C][C]0.327906[/C][/ROW]
[ROW][C]45[/C][C]0.076887[/C][C]0.5956[/C][C]0.276853[/C][/ROW]
[ROW][C]46[/C][C]-0.023732[/C][C]-0.1838[/C][C]0.427384[/C][/ROW]
[ROW][C]47[/C][C]0.0719[/C][C]0.5569[/C][C]0.289823[/C][/ROW]
[ROW][C]48[/C][C]0.023471[/C][C]0.1818[/C][C]0.428173[/C][/ROW]
[ROW][C]49[/C][C]0.036543[/C][C]0.2831[/C][C]0.389053[/C][/ROW]
[ROW][C]50[/C][C]-0.138052[/C][C]-1.0693[/C][C]0.144599[/C][/ROW]
[ROW][C]51[/C][C]-0.031625[/C][C]-0.245[/C][C]0.403659[/C][/ROW]
[ROW][C]52[/C][C]-0.029692[/C][C]-0.23[/C][C]0.40944[/C][/ROW]
[ROW][C]53[/C][C]-0.025466[/C][C]-0.1973[/C][C]0.422145[/C][/ROW]
[ROW][C]54[/C][C]0.023532[/C][C]0.1823[/C][C]0.427991[/C][/ROW]
[ROW][C]55[/C][C]-0.037076[/C][C]-0.2872[/C][C]0.387477[/C][/ROW]
[ROW][C]56[/C][C]-0.11864[/C][C]-0.919[/C][C]0.180892[/C][/ROW]
[ROW][C]57[/C][C]-0.004518[/C][C]-0.035[/C][C]0.486101[/C][/ROW]
[ROW][C]58[/C][C]0.07272[/C][C]0.5633[/C][C]0.28767[/C][/ROW]
[ROW][C]59[/C][C]-0.030339[/C][C]-0.235[/C][C]0.407502[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117300&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117300&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
10.9137647.0780
20.0929090.71970.23726
3-0.038457-0.29790.383409
4-0.205256-1.58990.058556
5-0.314363-2.4350.00894
6-0.036057-0.27930.390488
7-0.081024-0.62760.26632
8-0.112653-0.87260.193178
9-0.175804-1.36180.089181
100.0240150.1860.426529
11-0.008733-0.06760.473147
12-0.038798-0.30050.382407
130.1956061.51520.067492
140.1460841.13160.131161
15-0.007059-0.05470.478287
160.0373870.28960.386561
17-0.156194-1.20990.115536
180.0008240.00640.497464
19-0.087048-0.67430.251365
200.0642480.49770.31027
21-0.007488-0.0580.476971
22-0.184924-1.43240.078608
23-0.106363-0.82390.206634
24-0.044102-0.34160.366918
250.1979241.53310.065252
260.0083460.06460.474336
270.0037940.02940.488328
28-0.026748-0.20720.418282
290.0880670.68220.248881
30-0.074439-0.57660.283183
31-0.097494-0.75520.226547
32-0.052354-0.40550.343264
33-0.052853-0.40940.341854
340.0621710.48160.315929
350.1064790.82480.206382
36-0.083981-0.65050.258922
370.0558540.43260.333411
38-0.098745-0.76490.223673
39-0.061124-0.47350.318799
40-0.059607-0.46170.322979
41-0.06122-0.47420.318537
420.0479380.37130.355851
43-0.006272-0.04860.480708
44-0.057828-0.44790.327906
450.0768870.59560.276853
46-0.023732-0.18380.427384
470.07190.55690.289823
480.0234710.18180.428173
490.0365430.28310.389053
50-0.138052-1.06930.144599
51-0.031625-0.2450.403659
52-0.029692-0.230.40944
53-0.025466-0.19730.422145
540.0235320.18230.427991
55-0.037076-0.28720.387477
56-0.11864-0.9190.180892
57-0.004518-0.0350.486101
580.072720.56330.28767
59-0.030339-0.2350.407502
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (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')