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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 computationTue, 20 Dec 2011 16:28:36 -0500
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/Dec/20/t1324416596jd3czf00ebh4hk5.htm/, Retrieved Thu, 31 Oct 2024 22:48:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158284, Retrieved Thu, 31 Oct 2024 22:48:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact239
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
- R PD          [(Partial) Autocorrelation Function] [WS9 3.1 ACF d=0, D=0] [2010-12-07 10:00:49] [afe9379cca749d06b3d6872e02cc47ed]
- R PD            [(Partial) Autocorrelation Function] [] [2011-12-04 10:34:49] [ec2187f7727da5d5d939740b21b8b68a]
-   PD                [(Partial) Autocorrelation Function] [] [2011-12-20 21:28:36] [542c32830549043c4555f1bd78aefedb] [Current]
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Dataseries X:
90604
97527
111940
100280
100009
95558
98533
92694
97920
110933
110855
111716
96348
105425
114874
104199
101166
99010
101607
97492
106088
113536
112475
115491
97733
102591
114783
100397
97772
96128
91261
90686
97792
108848
109989
109453
93945
98750
119043
104776
103262
106735
101600
99358
105240
114079
121637
111747
99496
104992
124255
108258
106940
104939
105896
107287
110783
122139
125823
120480
103296
117121
129924
118589
118062
113597
117161
112893
119657
136562
140446
138744
120324
118113
130257
125510
117986
118316
122075
117573
122566
135934
138394
137999
118780
117907
142932
132200
125666
127958
127718
124368
135241
144734
142320
141481
120471
123422
145829
134572
132156
140265
137771
134035
144016
151905
155791
148440
129862
134264
151952
143191
137242
136993
134431
132523
133486
140120
137521
112193
94256
99047
109761
102160
104792
104341
112430
113034
114197
127876
135199
123663
112578
117104
139703
114961
134222
128390
134197
135963
135936
146803
143231
131510




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158284&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158284&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158284&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'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.184817-2.11530.018148
20.1515641.73470.04257
30.2129512.43730.008069
4-0.086825-0.99380.161088
50.0868540.99410.161007
60.0876681.00340.158758
7-0.010379-0.11880.45281
8-0.07599-0.86970.193016
90.0448180.5130.304421
10-0.164618-1.88410.030881
11-0.11319-1.29550.09871
12-0.177835-2.03540.021913
13-0.196281-2.24650.013172
14-0.018531-0.21210.41618
15-0.031796-0.36390.358249
16-0.069227-0.79230.214799
17-0.033424-0.38260.351335
18-0.086791-0.99340.161181
19-0.148306-1.69740.045994
200.125721.43890.076278
21-0.055348-0.63350.263762
220.0083830.09590.461855
230.2248172.57310.005596
24-0.152608-1.74670.041519
250.1167321.33610.091924
260.085490.97850.164821
27-0.158716-1.81660.035783
280.0555130.63540.263147
290.0824410.94360.173561
30-0.034594-0.3960.346393
310.0792030.90650.183163
320.0223420.25570.399284
33-0.114964-1.31580.095266
34-0.003392-0.03880.484547
350.009520.1090.456698
36-0.111868-1.28040.101336
370.1009111.1550.125101
380.0125310.14340.443087
39-0.056689-0.64880.25879
400.1110411.27090.103005
41-0.061304-0.70170.242068
42-0.040347-0.46180.322498
430.0742750.85010.198407
44-0.026645-0.3050.380439
450.0479730.54910.291944
460.156761.79420.037544
47-0.054791-0.62710.265838
480.0593190.67890.249189
49-0.025048-0.28670.387402
50-0.079912-0.91460.181033
510.0062820.07190.471394
520.0449060.5140.304069
53-0.107019-1.22490.111407
540.0110120.1260.449946
550.0249250.28530.387942
56-0.118714-1.35870.088281
570.0160920.18420.427079
58-0.110952-1.26990.103185
590.0161020.18430.427034
600.0372190.4260.335406

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.184817 & -2.1153 & 0.018148 \tabularnewline
2 & 0.151564 & 1.7347 & 0.04257 \tabularnewline
3 & 0.212951 & 2.4373 & 0.008069 \tabularnewline
4 & -0.086825 & -0.9938 & 0.161088 \tabularnewline
5 & 0.086854 & 0.9941 & 0.161007 \tabularnewline
6 & 0.087668 & 1.0034 & 0.158758 \tabularnewline
7 & -0.010379 & -0.1188 & 0.45281 \tabularnewline
8 & -0.07599 & -0.8697 & 0.193016 \tabularnewline
9 & 0.044818 & 0.513 & 0.304421 \tabularnewline
10 & -0.164618 & -1.8841 & 0.030881 \tabularnewline
11 & -0.11319 & -1.2955 & 0.09871 \tabularnewline
12 & -0.177835 & -2.0354 & 0.021913 \tabularnewline
13 & -0.196281 & -2.2465 & 0.013172 \tabularnewline
14 & -0.018531 & -0.2121 & 0.41618 \tabularnewline
15 & -0.031796 & -0.3639 & 0.358249 \tabularnewline
16 & -0.069227 & -0.7923 & 0.214799 \tabularnewline
17 & -0.033424 & -0.3826 & 0.351335 \tabularnewline
18 & -0.086791 & -0.9934 & 0.161181 \tabularnewline
19 & -0.148306 & -1.6974 & 0.045994 \tabularnewline
20 & 0.12572 & 1.4389 & 0.076278 \tabularnewline
21 & -0.055348 & -0.6335 & 0.263762 \tabularnewline
22 & 0.008383 & 0.0959 & 0.461855 \tabularnewline
23 & 0.224817 & 2.5731 & 0.005596 \tabularnewline
24 & -0.152608 & -1.7467 & 0.041519 \tabularnewline
25 & 0.116732 & 1.3361 & 0.091924 \tabularnewline
26 & 0.08549 & 0.9785 & 0.164821 \tabularnewline
27 & -0.158716 & -1.8166 & 0.035783 \tabularnewline
28 & 0.055513 & 0.6354 & 0.263147 \tabularnewline
29 & 0.082441 & 0.9436 & 0.173561 \tabularnewline
30 & -0.034594 & -0.396 & 0.346393 \tabularnewline
31 & 0.079203 & 0.9065 & 0.183163 \tabularnewline
32 & 0.022342 & 0.2557 & 0.399284 \tabularnewline
33 & -0.114964 & -1.3158 & 0.095266 \tabularnewline
34 & -0.003392 & -0.0388 & 0.484547 \tabularnewline
35 & 0.00952 & 0.109 & 0.456698 \tabularnewline
36 & -0.111868 & -1.2804 & 0.101336 \tabularnewline
37 & 0.100911 & 1.155 & 0.125101 \tabularnewline
38 & 0.012531 & 0.1434 & 0.443087 \tabularnewline
39 & -0.056689 & -0.6488 & 0.25879 \tabularnewline
40 & 0.111041 & 1.2709 & 0.103005 \tabularnewline
41 & -0.061304 & -0.7017 & 0.242068 \tabularnewline
42 & -0.040347 & -0.4618 & 0.322498 \tabularnewline
43 & 0.074275 & 0.8501 & 0.198407 \tabularnewline
44 & -0.026645 & -0.305 & 0.380439 \tabularnewline
45 & 0.047973 & 0.5491 & 0.291944 \tabularnewline
46 & 0.15676 & 1.7942 & 0.037544 \tabularnewline
47 & -0.054791 & -0.6271 & 0.265838 \tabularnewline
48 & 0.059319 & 0.6789 & 0.249189 \tabularnewline
49 & -0.025048 & -0.2867 & 0.387402 \tabularnewline
50 & -0.079912 & -0.9146 & 0.181033 \tabularnewline
51 & 0.006282 & 0.0719 & 0.471394 \tabularnewline
52 & 0.044906 & 0.514 & 0.304069 \tabularnewline
53 & -0.107019 & -1.2249 & 0.111407 \tabularnewline
54 & 0.011012 & 0.126 & 0.449946 \tabularnewline
55 & 0.024925 & 0.2853 & 0.387942 \tabularnewline
56 & -0.118714 & -1.3587 & 0.088281 \tabularnewline
57 & 0.016092 & 0.1842 & 0.427079 \tabularnewline
58 & -0.110952 & -1.2699 & 0.103185 \tabularnewline
59 & 0.016102 & 0.1843 & 0.427034 \tabularnewline
60 & 0.037219 & 0.426 & 0.335406 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158284&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]-0.184817[/C][C]-2.1153[/C][C]0.018148[/C][/ROW]
[ROW][C]2[/C][C]0.151564[/C][C]1.7347[/C][C]0.04257[/C][/ROW]
[ROW][C]3[/C][C]0.212951[/C][C]2.4373[/C][C]0.008069[/C][/ROW]
[ROW][C]4[/C][C]-0.086825[/C][C]-0.9938[/C][C]0.161088[/C][/ROW]
[ROW][C]5[/C][C]0.086854[/C][C]0.9941[/C][C]0.161007[/C][/ROW]
[ROW][C]6[/C][C]0.087668[/C][C]1.0034[/C][C]0.158758[/C][/ROW]
[ROW][C]7[/C][C]-0.010379[/C][C]-0.1188[/C][C]0.45281[/C][/ROW]
[ROW][C]8[/C][C]-0.07599[/C][C]-0.8697[/C][C]0.193016[/C][/ROW]
[ROW][C]9[/C][C]0.044818[/C][C]0.513[/C][C]0.304421[/C][/ROW]
[ROW][C]10[/C][C]-0.164618[/C][C]-1.8841[/C][C]0.030881[/C][/ROW]
[ROW][C]11[/C][C]-0.11319[/C][C]-1.2955[/C][C]0.09871[/C][/ROW]
[ROW][C]12[/C][C]-0.177835[/C][C]-2.0354[/C][C]0.021913[/C][/ROW]
[ROW][C]13[/C][C]-0.196281[/C][C]-2.2465[/C][C]0.013172[/C][/ROW]
[ROW][C]14[/C][C]-0.018531[/C][C]-0.2121[/C][C]0.41618[/C][/ROW]
[ROW][C]15[/C][C]-0.031796[/C][C]-0.3639[/C][C]0.358249[/C][/ROW]
[ROW][C]16[/C][C]-0.069227[/C][C]-0.7923[/C][C]0.214799[/C][/ROW]
[ROW][C]17[/C][C]-0.033424[/C][C]-0.3826[/C][C]0.351335[/C][/ROW]
[ROW][C]18[/C][C]-0.086791[/C][C]-0.9934[/C][C]0.161181[/C][/ROW]
[ROW][C]19[/C][C]-0.148306[/C][C]-1.6974[/C][C]0.045994[/C][/ROW]
[ROW][C]20[/C][C]0.12572[/C][C]1.4389[/C][C]0.076278[/C][/ROW]
[ROW][C]21[/C][C]-0.055348[/C][C]-0.6335[/C][C]0.263762[/C][/ROW]
[ROW][C]22[/C][C]0.008383[/C][C]0.0959[/C][C]0.461855[/C][/ROW]
[ROW][C]23[/C][C]0.224817[/C][C]2.5731[/C][C]0.005596[/C][/ROW]
[ROW][C]24[/C][C]-0.152608[/C][C]-1.7467[/C][C]0.041519[/C][/ROW]
[ROW][C]25[/C][C]0.116732[/C][C]1.3361[/C][C]0.091924[/C][/ROW]
[ROW][C]26[/C][C]0.08549[/C][C]0.9785[/C][C]0.164821[/C][/ROW]
[ROW][C]27[/C][C]-0.158716[/C][C]-1.8166[/C][C]0.035783[/C][/ROW]
[ROW][C]28[/C][C]0.055513[/C][C]0.6354[/C][C]0.263147[/C][/ROW]
[ROW][C]29[/C][C]0.082441[/C][C]0.9436[/C][C]0.173561[/C][/ROW]
[ROW][C]30[/C][C]-0.034594[/C][C]-0.396[/C][C]0.346393[/C][/ROW]
[ROW][C]31[/C][C]0.079203[/C][C]0.9065[/C][C]0.183163[/C][/ROW]
[ROW][C]32[/C][C]0.022342[/C][C]0.2557[/C][C]0.399284[/C][/ROW]
[ROW][C]33[/C][C]-0.114964[/C][C]-1.3158[/C][C]0.095266[/C][/ROW]
[ROW][C]34[/C][C]-0.003392[/C][C]-0.0388[/C][C]0.484547[/C][/ROW]
[ROW][C]35[/C][C]0.00952[/C][C]0.109[/C][C]0.456698[/C][/ROW]
[ROW][C]36[/C][C]-0.111868[/C][C]-1.2804[/C][C]0.101336[/C][/ROW]
[ROW][C]37[/C][C]0.100911[/C][C]1.155[/C][C]0.125101[/C][/ROW]
[ROW][C]38[/C][C]0.012531[/C][C]0.1434[/C][C]0.443087[/C][/ROW]
[ROW][C]39[/C][C]-0.056689[/C][C]-0.6488[/C][C]0.25879[/C][/ROW]
[ROW][C]40[/C][C]0.111041[/C][C]1.2709[/C][C]0.103005[/C][/ROW]
[ROW][C]41[/C][C]-0.061304[/C][C]-0.7017[/C][C]0.242068[/C][/ROW]
[ROW][C]42[/C][C]-0.040347[/C][C]-0.4618[/C][C]0.322498[/C][/ROW]
[ROW][C]43[/C][C]0.074275[/C][C]0.8501[/C][C]0.198407[/C][/ROW]
[ROW][C]44[/C][C]-0.026645[/C][C]-0.305[/C][C]0.380439[/C][/ROW]
[ROW][C]45[/C][C]0.047973[/C][C]0.5491[/C][C]0.291944[/C][/ROW]
[ROW][C]46[/C][C]0.15676[/C][C]1.7942[/C][C]0.037544[/C][/ROW]
[ROW][C]47[/C][C]-0.054791[/C][C]-0.6271[/C][C]0.265838[/C][/ROW]
[ROW][C]48[/C][C]0.059319[/C][C]0.6789[/C][C]0.249189[/C][/ROW]
[ROW][C]49[/C][C]-0.025048[/C][C]-0.2867[/C][C]0.387402[/C][/ROW]
[ROW][C]50[/C][C]-0.079912[/C][C]-0.9146[/C][C]0.181033[/C][/ROW]
[ROW][C]51[/C][C]0.006282[/C][C]0.0719[/C][C]0.471394[/C][/ROW]
[ROW][C]52[/C][C]0.044906[/C][C]0.514[/C][C]0.304069[/C][/ROW]
[ROW][C]53[/C][C]-0.107019[/C][C]-1.2249[/C][C]0.111407[/C][/ROW]
[ROW][C]54[/C][C]0.011012[/C][C]0.126[/C][C]0.449946[/C][/ROW]
[ROW][C]55[/C][C]0.024925[/C][C]0.2853[/C][C]0.387942[/C][/ROW]
[ROW][C]56[/C][C]-0.118714[/C][C]-1.3587[/C][C]0.088281[/C][/ROW]
[ROW][C]57[/C][C]0.016092[/C][C]0.1842[/C][C]0.427079[/C][/ROW]
[ROW][C]58[/C][C]-0.110952[/C][C]-1.2699[/C][C]0.103185[/C][/ROW]
[ROW][C]59[/C][C]0.016102[/C][C]0.1843[/C][C]0.427034[/C][/ROW]
[ROW][C]60[/C][C]0.037219[/C][C]0.426[/C][C]0.335406[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158284&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158284&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
1-0.184817-2.11530.018148
20.1515641.73470.04257
30.2129512.43730.008069
4-0.086825-0.99380.161088
50.0868540.99410.161007
60.0876681.00340.158758
7-0.010379-0.11880.45281
8-0.07599-0.86970.193016
90.0448180.5130.304421
10-0.164618-1.88410.030881
11-0.11319-1.29550.09871
12-0.177835-2.03540.021913
13-0.196281-2.24650.013172
14-0.018531-0.21210.41618
15-0.031796-0.36390.358249
16-0.069227-0.79230.214799
17-0.033424-0.38260.351335
18-0.086791-0.99340.161181
19-0.148306-1.69740.045994
200.125721.43890.076278
21-0.055348-0.63350.263762
220.0083830.09590.461855
230.2248172.57310.005596
24-0.152608-1.74670.041519
250.1167321.33610.091924
260.085490.97850.164821
27-0.158716-1.81660.035783
280.0555130.63540.263147
290.0824410.94360.173561
30-0.034594-0.3960.346393
310.0792030.90650.183163
320.0223420.25570.399284
33-0.114964-1.31580.095266
34-0.003392-0.03880.484547
350.009520.1090.456698
36-0.111868-1.28040.101336
370.1009111.1550.125101
380.0125310.14340.443087
39-0.056689-0.64880.25879
400.1110411.27090.103005
41-0.061304-0.70170.242068
42-0.040347-0.46180.322498
430.0742750.85010.198407
44-0.026645-0.3050.380439
450.0479730.54910.291944
460.156761.79420.037544
47-0.054791-0.62710.265838
480.0593190.67890.249189
49-0.025048-0.28670.387402
50-0.079912-0.91460.181033
510.0062820.07190.471394
520.0449060.5140.304069
53-0.107019-1.22490.111407
540.0110120.1260.449946
550.0249250.28530.387942
56-0.118714-1.35870.088281
570.0160920.18420.427079
58-0.110952-1.26990.103185
590.0161020.18430.427034
600.0372190.4260.335406







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.184817-2.11530.018148
20.1215591.39130.083245
30.2732583.12760.001086
4-0.022513-0.25770.398531
5-0.01208-0.13830.445125
60.0715870.81940.207037
70.0385650.44140.329828
8-0.140754-1.6110.054793
9-0.037384-0.42790.334722
10-0.135317-1.54880.061924
11-0.15529-1.77740.038914
12-0.250955-2.87230.002377
13-0.215937-2.47150.007369
140.0054340.06220.47525
150.1390931.5920.056898
160.0654140.74870.22769
170.0047760.05470.478246
18-0.058458-0.66910.25231
19-0.178324-2.0410.021629
200.0334110.38240.35139
21-0.0103-0.11790.453166
22-0.060769-0.69550.243977
230.1098461.25720.10545
24-0.159265-1.82290.035301
25-0.087294-0.99910.159788
260.0372780.42670.335163
27-0.096565-1.10520.135541
28-0.088273-1.01030.1571
29-0.004451-0.05090.479724
30-0.024734-0.28310.388774
31-0.005023-0.05750.477123
32-0.0254-0.29070.385864
33-0.035795-0.40970.34135
34-0.036784-0.4210.33722
350.0035110.04020.484005
36-0.125037-1.43110.077389
37-0.020815-0.23820.406033
380.0359760.41180.340594
39-0.029041-0.33240.370064
400.0106990.12250.451363
41-0.010603-0.12140.451799
42-0.01944-0.22250.412134
43-0.020499-0.23460.407432
44-0.011399-0.13050.4482
45-0.021172-0.24230.404453
460.0642850.73580.231591
470.0394610.45160.326134
48-0.000418-0.00480.498095
49-0.093727-1.07280.142678
50-0.049851-0.57060.284635
51-0.108178-1.23820.108936
520.0086780.09930.460516
53-0.065465-0.74930.227516
54-0.088077-1.00810.157636
550.021120.24170.404685
560.0565570.64730.259277
570.032570.37280.354956
58-0.071556-0.8190.207138
590.1064731.21860.112586
600.0239290.27390.392303

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.184817 & -2.1153 & 0.018148 \tabularnewline
2 & 0.121559 & 1.3913 & 0.083245 \tabularnewline
3 & 0.273258 & 3.1276 & 0.001086 \tabularnewline
4 & -0.022513 & -0.2577 & 0.398531 \tabularnewline
5 & -0.01208 & -0.1383 & 0.445125 \tabularnewline
6 & 0.071587 & 0.8194 & 0.207037 \tabularnewline
7 & 0.038565 & 0.4414 & 0.329828 \tabularnewline
8 & -0.140754 & -1.611 & 0.054793 \tabularnewline
9 & -0.037384 & -0.4279 & 0.334722 \tabularnewline
10 & -0.135317 & -1.5488 & 0.061924 \tabularnewline
11 & -0.15529 & -1.7774 & 0.038914 \tabularnewline
12 & -0.250955 & -2.8723 & 0.002377 \tabularnewline
13 & -0.215937 & -2.4715 & 0.007369 \tabularnewline
14 & 0.005434 & 0.0622 & 0.47525 \tabularnewline
15 & 0.139093 & 1.592 & 0.056898 \tabularnewline
16 & 0.065414 & 0.7487 & 0.22769 \tabularnewline
17 & 0.004776 & 0.0547 & 0.478246 \tabularnewline
18 & -0.058458 & -0.6691 & 0.25231 \tabularnewline
19 & -0.178324 & -2.041 & 0.021629 \tabularnewline
20 & 0.033411 & 0.3824 & 0.35139 \tabularnewline
21 & -0.0103 & -0.1179 & 0.453166 \tabularnewline
22 & -0.060769 & -0.6955 & 0.243977 \tabularnewline
23 & 0.109846 & 1.2572 & 0.10545 \tabularnewline
24 & -0.159265 & -1.8229 & 0.035301 \tabularnewline
25 & -0.087294 & -0.9991 & 0.159788 \tabularnewline
26 & 0.037278 & 0.4267 & 0.335163 \tabularnewline
27 & -0.096565 & -1.1052 & 0.135541 \tabularnewline
28 & -0.088273 & -1.0103 & 0.1571 \tabularnewline
29 & -0.004451 & -0.0509 & 0.479724 \tabularnewline
30 & -0.024734 & -0.2831 & 0.388774 \tabularnewline
31 & -0.005023 & -0.0575 & 0.477123 \tabularnewline
32 & -0.0254 & -0.2907 & 0.385864 \tabularnewline
33 & -0.035795 & -0.4097 & 0.34135 \tabularnewline
34 & -0.036784 & -0.421 & 0.33722 \tabularnewline
35 & 0.003511 & 0.0402 & 0.484005 \tabularnewline
36 & -0.125037 & -1.4311 & 0.077389 \tabularnewline
37 & -0.020815 & -0.2382 & 0.406033 \tabularnewline
38 & 0.035976 & 0.4118 & 0.340594 \tabularnewline
39 & -0.029041 & -0.3324 & 0.370064 \tabularnewline
40 & 0.010699 & 0.1225 & 0.451363 \tabularnewline
41 & -0.010603 & -0.1214 & 0.451799 \tabularnewline
42 & -0.01944 & -0.2225 & 0.412134 \tabularnewline
43 & -0.020499 & -0.2346 & 0.407432 \tabularnewline
44 & -0.011399 & -0.1305 & 0.4482 \tabularnewline
45 & -0.021172 & -0.2423 & 0.404453 \tabularnewline
46 & 0.064285 & 0.7358 & 0.231591 \tabularnewline
47 & 0.039461 & 0.4516 & 0.326134 \tabularnewline
48 & -0.000418 & -0.0048 & 0.498095 \tabularnewline
49 & -0.093727 & -1.0728 & 0.142678 \tabularnewline
50 & -0.049851 & -0.5706 & 0.284635 \tabularnewline
51 & -0.108178 & -1.2382 & 0.108936 \tabularnewline
52 & 0.008678 & 0.0993 & 0.460516 \tabularnewline
53 & -0.065465 & -0.7493 & 0.227516 \tabularnewline
54 & -0.088077 & -1.0081 & 0.157636 \tabularnewline
55 & 0.02112 & 0.2417 & 0.404685 \tabularnewline
56 & 0.056557 & 0.6473 & 0.259277 \tabularnewline
57 & 0.03257 & 0.3728 & 0.354956 \tabularnewline
58 & -0.071556 & -0.819 & 0.207138 \tabularnewline
59 & 0.106473 & 1.2186 & 0.112586 \tabularnewline
60 & 0.023929 & 0.2739 & 0.392303 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158284&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]-0.184817[/C][C]-2.1153[/C][C]0.018148[/C][/ROW]
[ROW][C]2[/C][C]0.121559[/C][C]1.3913[/C][C]0.083245[/C][/ROW]
[ROW][C]3[/C][C]0.273258[/C][C]3.1276[/C][C]0.001086[/C][/ROW]
[ROW][C]4[/C][C]-0.022513[/C][C]-0.2577[/C][C]0.398531[/C][/ROW]
[ROW][C]5[/C][C]-0.01208[/C][C]-0.1383[/C][C]0.445125[/C][/ROW]
[ROW][C]6[/C][C]0.071587[/C][C]0.8194[/C][C]0.207037[/C][/ROW]
[ROW][C]7[/C][C]0.038565[/C][C]0.4414[/C][C]0.329828[/C][/ROW]
[ROW][C]8[/C][C]-0.140754[/C][C]-1.611[/C][C]0.054793[/C][/ROW]
[ROW][C]9[/C][C]-0.037384[/C][C]-0.4279[/C][C]0.334722[/C][/ROW]
[ROW][C]10[/C][C]-0.135317[/C][C]-1.5488[/C][C]0.061924[/C][/ROW]
[ROW][C]11[/C][C]-0.15529[/C][C]-1.7774[/C][C]0.038914[/C][/ROW]
[ROW][C]12[/C][C]-0.250955[/C][C]-2.8723[/C][C]0.002377[/C][/ROW]
[ROW][C]13[/C][C]-0.215937[/C][C]-2.4715[/C][C]0.007369[/C][/ROW]
[ROW][C]14[/C][C]0.005434[/C][C]0.0622[/C][C]0.47525[/C][/ROW]
[ROW][C]15[/C][C]0.139093[/C][C]1.592[/C][C]0.056898[/C][/ROW]
[ROW][C]16[/C][C]0.065414[/C][C]0.7487[/C][C]0.22769[/C][/ROW]
[ROW][C]17[/C][C]0.004776[/C][C]0.0547[/C][C]0.478246[/C][/ROW]
[ROW][C]18[/C][C]-0.058458[/C][C]-0.6691[/C][C]0.25231[/C][/ROW]
[ROW][C]19[/C][C]-0.178324[/C][C]-2.041[/C][C]0.021629[/C][/ROW]
[ROW][C]20[/C][C]0.033411[/C][C]0.3824[/C][C]0.35139[/C][/ROW]
[ROW][C]21[/C][C]-0.0103[/C][C]-0.1179[/C][C]0.453166[/C][/ROW]
[ROW][C]22[/C][C]-0.060769[/C][C]-0.6955[/C][C]0.243977[/C][/ROW]
[ROW][C]23[/C][C]0.109846[/C][C]1.2572[/C][C]0.10545[/C][/ROW]
[ROW][C]24[/C][C]-0.159265[/C][C]-1.8229[/C][C]0.035301[/C][/ROW]
[ROW][C]25[/C][C]-0.087294[/C][C]-0.9991[/C][C]0.159788[/C][/ROW]
[ROW][C]26[/C][C]0.037278[/C][C]0.4267[/C][C]0.335163[/C][/ROW]
[ROW][C]27[/C][C]-0.096565[/C][C]-1.1052[/C][C]0.135541[/C][/ROW]
[ROW][C]28[/C][C]-0.088273[/C][C]-1.0103[/C][C]0.1571[/C][/ROW]
[ROW][C]29[/C][C]-0.004451[/C][C]-0.0509[/C][C]0.479724[/C][/ROW]
[ROW][C]30[/C][C]-0.024734[/C][C]-0.2831[/C][C]0.388774[/C][/ROW]
[ROW][C]31[/C][C]-0.005023[/C][C]-0.0575[/C][C]0.477123[/C][/ROW]
[ROW][C]32[/C][C]-0.0254[/C][C]-0.2907[/C][C]0.385864[/C][/ROW]
[ROW][C]33[/C][C]-0.035795[/C][C]-0.4097[/C][C]0.34135[/C][/ROW]
[ROW][C]34[/C][C]-0.036784[/C][C]-0.421[/C][C]0.33722[/C][/ROW]
[ROW][C]35[/C][C]0.003511[/C][C]0.0402[/C][C]0.484005[/C][/ROW]
[ROW][C]36[/C][C]-0.125037[/C][C]-1.4311[/C][C]0.077389[/C][/ROW]
[ROW][C]37[/C][C]-0.020815[/C][C]-0.2382[/C][C]0.406033[/C][/ROW]
[ROW][C]38[/C][C]0.035976[/C][C]0.4118[/C][C]0.340594[/C][/ROW]
[ROW][C]39[/C][C]-0.029041[/C][C]-0.3324[/C][C]0.370064[/C][/ROW]
[ROW][C]40[/C][C]0.010699[/C][C]0.1225[/C][C]0.451363[/C][/ROW]
[ROW][C]41[/C][C]-0.010603[/C][C]-0.1214[/C][C]0.451799[/C][/ROW]
[ROW][C]42[/C][C]-0.01944[/C][C]-0.2225[/C][C]0.412134[/C][/ROW]
[ROW][C]43[/C][C]-0.020499[/C][C]-0.2346[/C][C]0.407432[/C][/ROW]
[ROW][C]44[/C][C]-0.011399[/C][C]-0.1305[/C][C]0.4482[/C][/ROW]
[ROW][C]45[/C][C]-0.021172[/C][C]-0.2423[/C][C]0.404453[/C][/ROW]
[ROW][C]46[/C][C]0.064285[/C][C]0.7358[/C][C]0.231591[/C][/ROW]
[ROW][C]47[/C][C]0.039461[/C][C]0.4516[/C][C]0.326134[/C][/ROW]
[ROW][C]48[/C][C]-0.000418[/C][C]-0.0048[/C][C]0.498095[/C][/ROW]
[ROW][C]49[/C][C]-0.093727[/C][C]-1.0728[/C][C]0.142678[/C][/ROW]
[ROW][C]50[/C][C]-0.049851[/C][C]-0.5706[/C][C]0.284635[/C][/ROW]
[ROW][C]51[/C][C]-0.108178[/C][C]-1.2382[/C][C]0.108936[/C][/ROW]
[ROW][C]52[/C][C]0.008678[/C][C]0.0993[/C][C]0.460516[/C][/ROW]
[ROW][C]53[/C][C]-0.065465[/C][C]-0.7493[/C][C]0.227516[/C][/ROW]
[ROW][C]54[/C][C]-0.088077[/C][C]-1.0081[/C][C]0.157636[/C][/ROW]
[ROW][C]55[/C][C]0.02112[/C][C]0.2417[/C][C]0.404685[/C][/ROW]
[ROW][C]56[/C][C]0.056557[/C][C]0.6473[/C][C]0.259277[/C][/ROW]
[ROW][C]57[/C][C]0.03257[/C][C]0.3728[/C][C]0.354956[/C][/ROW]
[ROW][C]58[/C][C]-0.071556[/C][C]-0.819[/C][C]0.207138[/C][/ROW]
[ROW][C]59[/C][C]0.106473[/C][C]1.2186[/C][C]0.112586[/C][/ROW]
[ROW][C]60[/C][C]0.023929[/C][C]0.2739[/C][C]0.392303[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158284&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158284&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
1-0.184817-2.11530.018148
20.1215591.39130.083245
30.2732583.12760.001086
4-0.022513-0.25770.398531
5-0.01208-0.13830.445125
60.0715870.81940.207037
70.0385650.44140.329828
8-0.140754-1.6110.054793
9-0.037384-0.42790.334722
10-0.135317-1.54880.061924
11-0.15529-1.77740.038914
12-0.250955-2.87230.002377
13-0.215937-2.47150.007369
140.0054340.06220.47525
150.1390931.5920.056898
160.0654140.74870.22769
170.0047760.05470.478246
18-0.058458-0.66910.25231
19-0.178324-2.0410.021629
200.0334110.38240.35139
21-0.0103-0.11790.453166
22-0.060769-0.69550.243977
230.1098461.25720.10545
24-0.159265-1.82290.035301
25-0.087294-0.99910.159788
260.0372780.42670.335163
27-0.096565-1.10520.135541
28-0.088273-1.01030.1571
29-0.004451-0.05090.479724
30-0.024734-0.28310.388774
31-0.005023-0.05750.477123
32-0.0254-0.29070.385864
33-0.035795-0.40970.34135
34-0.036784-0.4210.33722
350.0035110.04020.484005
36-0.125037-1.43110.077389
37-0.020815-0.23820.406033
380.0359760.41180.340594
39-0.029041-0.33240.370064
400.0106990.12250.451363
41-0.010603-0.12140.451799
42-0.01944-0.22250.412134
43-0.020499-0.23460.407432
44-0.011399-0.13050.4482
45-0.021172-0.24230.404453
460.0642850.73580.231591
470.0394610.45160.326134
48-0.000418-0.00480.498095
49-0.093727-1.07280.142678
50-0.049851-0.57060.284635
51-0.108178-1.23820.108936
520.0086780.09930.460516
53-0.065465-0.74930.227516
54-0.088077-1.00810.157636
550.021120.24170.404685
560.0565570.64730.259277
570.032570.37280.354956
58-0.071556-0.8190.207138
590.1064731.21860.112586
600.0239290.27390.392303



Parameters (Session):
par1 = 4 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')