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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 09 Dec 2008 12:53:18 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/09/t1228852466xmevxrtccxnoq7c.htm/, Retrieved Fri, 17 May 2024 05:14:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31753, Retrieved Fri, 17 May 2024 05:14:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact215
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [Laura_Reussens_VRM5] [2008-12-09 13:33:45] [66eaf6cf5556820c444aae1569718ff9]
- RMPD    [(Partial) Autocorrelation Function] [Laura_Reussens_ACF] [2008-12-09 19:53:18] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
5.5
5.3
5.2
5.3
5.3
5
4.8
4.9
5.3
6
6.2
6.4
6.4
6.4
6.2
6.1
6
5.9
6.2
6.2
6.4
6.8
6.9
7
7
6.9
6.7
6.6
6.5
6.4
6.5
6.5
6.6
6.7
6.8
7.2
7.6
7.6
7.3
6.4
6.1
6.3
7.1
7.5
7.4
7.1
6.8
6.9
7.2
7.4
7.3
6.9
6.9
6.8
7.1
7.2
7.1
7
6.9
7
7.4
7.5
7.5
7.4
7.3
7
6.7
6.5
6.5
6.5
6.6
6.8
6.9
6.9
6.8
6.8
6.5
6.1
6
5.9
5.8
5.9
5.9
6.2
6.3
6.2
6
5.8
5.5
5.5
5.7
5.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31753&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31753&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0636470.60380.273746
2-0.143101-1.35760.088996
3-0.417689-3.96257.4e-05
4-0.328957-3.12080.001212
50.121871.15620.125338
60.2419422.29530.012021
70.1452741.37820.08578
8-0.11777-1.11730.133427
9-0.206894-1.96280.026381
10-0.075407-0.71540.238116
110.0445370.42250.336829
120.3714843.52420.000335
13-0.021373-0.20280.419889
140.0233790.22180.41249
15-0.104372-0.99020.162375
16-0.183887-1.74450.042243
170.007960.07550.469987
180.0386540.36670.357352
190.0716040.67930.249346
20-0.005718-0.05420.47843
21-0.058083-0.5510.29149
220.0154940.1470.441734
23-0.040676-0.38590.350245
240.0754630.71590.237953
25-0.038681-0.3670.357253
260.0387650.36780.356958
270.1140841.08230.141006
28-0.071641-0.67960.249237
290.0638440.60570.273126
30-0.170375-1.61630.054763
31-0.033148-0.31450.376944
32-0.038761-0.36770.356973
330.1277421.21190.114367
340.1066531.01180.157173
35-0.081006-0.76850.222103
36-0.065919-0.62540.266659
37-0.073982-0.70190.242291
380.0226180.21460.415294
390.1312761.24540.10811
400.0331890.31490.376798
410.0604650.57360.283827
42-0.077346-0.73380.232499
43-0.00035-0.00330.498678
44-0.149318-1.41660.080033
450.0192490.18260.427755
46-0.00371-0.03520.486
470.0078950.07490.470229
480.0578060.54840.292388

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.063647 & 0.6038 & 0.273746 \tabularnewline
2 & -0.143101 & -1.3576 & 0.088996 \tabularnewline
3 & -0.417689 & -3.9625 & 7.4e-05 \tabularnewline
4 & -0.328957 & -3.1208 & 0.001212 \tabularnewline
5 & 0.12187 & 1.1562 & 0.125338 \tabularnewline
6 & 0.241942 & 2.2953 & 0.012021 \tabularnewline
7 & 0.145274 & 1.3782 & 0.08578 \tabularnewline
8 & -0.11777 & -1.1173 & 0.133427 \tabularnewline
9 & -0.206894 & -1.9628 & 0.026381 \tabularnewline
10 & -0.075407 & -0.7154 & 0.238116 \tabularnewline
11 & 0.044537 & 0.4225 & 0.336829 \tabularnewline
12 & 0.371484 & 3.5242 & 0.000335 \tabularnewline
13 & -0.021373 & -0.2028 & 0.419889 \tabularnewline
14 & 0.023379 & 0.2218 & 0.41249 \tabularnewline
15 & -0.104372 & -0.9902 & 0.162375 \tabularnewline
16 & -0.183887 & -1.7445 & 0.042243 \tabularnewline
17 & 0.00796 & 0.0755 & 0.469987 \tabularnewline
18 & 0.038654 & 0.3667 & 0.357352 \tabularnewline
19 & 0.071604 & 0.6793 & 0.249346 \tabularnewline
20 & -0.005718 & -0.0542 & 0.47843 \tabularnewline
21 & -0.058083 & -0.551 & 0.29149 \tabularnewline
22 & 0.015494 & 0.147 & 0.441734 \tabularnewline
23 & -0.040676 & -0.3859 & 0.350245 \tabularnewline
24 & 0.075463 & 0.7159 & 0.237953 \tabularnewline
25 & -0.038681 & -0.367 & 0.357253 \tabularnewline
26 & 0.038765 & 0.3678 & 0.356958 \tabularnewline
27 & 0.114084 & 1.0823 & 0.141006 \tabularnewline
28 & -0.071641 & -0.6796 & 0.249237 \tabularnewline
29 & 0.063844 & 0.6057 & 0.273126 \tabularnewline
30 & -0.170375 & -1.6163 & 0.054763 \tabularnewline
31 & -0.033148 & -0.3145 & 0.376944 \tabularnewline
32 & -0.038761 & -0.3677 & 0.356973 \tabularnewline
33 & 0.127742 & 1.2119 & 0.114367 \tabularnewline
34 & 0.106653 & 1.0118 & 0.157173 \tabularnewline
35 & -0.081006 & -0.7685 & 0.222103 \tabularnewline
36 & -0.065919 & -0.6254 & 0.266659 \tabularnewline
37 & -0.073982 & -0.7019 & 0.242291 \tabularnewline
38 & 0.022618 & 0.2146 & 0.415294 \tabularnewline
39 & 0.131276 & 1.2454 & 0.10811 \tabularnewline
40 & 0.033189 & 0.3149 & 0.376798 \tabularnewline
41 & 0.060465 & 0.5736 & 0.283827 \tabularnewline
42 & -0.077346 & -0.7338 & 0.232499 \tabularnewline
43 & -0.00035 & -0.0033 & 0.498678 \tabularnewline
44 & -0.149318 & -1.4166 & 0.080033 \tabularnewline
45 & 0.019249 & 0.1826 & 0.427755 \tabularnewline
46 & -0.00371 & -0.0352 & 0.486 \tabularnewline
47 & 0.007895 & 0.0749 & 0.470229 \tabularnewline
48 & 0.057806 & 0.5484 & 0.292388 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31753&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]0.063647[/C][C]0.6038[/C][C]0.273746[/C][/ROW]
[ROW][C]2[/C][C]-0.143101[/C][C]-1.3576[/C][C]0.088996[/C][/ROW]
[ROW][C]3[/C][C]-0.417689[/C][C]-3.9625[/C][C]7.4e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.328957[/C][C]-3.1208[/C][C]0.001212[/C][/ROW]
[ROW][C]5[/C][C]0.12187[/C][C]1.1562[/C][C]0.125338[/C][/ROW]
[ROW][C]6[/C][C]0.241942[/C][C]2.2953[/C][C]0.012021[/C][/ROW]
[ROW][C]7[/C][C]0.145274[/C][C]1.3782[/C][C]0.08578[/C][/ROW]
[ROW][C]8[/C][C]-0.11777[/C][C]-1.1173[/C][C]0.133427[/C][/ROW]
[ROW][C]9[/C][C]-0.206894[/C][C]-1.9628[/C][C]0.026381[/C][/ROW]
[ROW][C]10[/C][C]-0.075407[/C][C]-0.7154[/C][C]0.238116[/C][/ROW]
[ROW][C]11[/C][C]0.044537[/C][C]0.4225[/C][C]0.336829[/C][/ROW]
[ROW][C]12[/C][C]0.371484[/C][C]3.5242[/C][C]0.000335[/C][/ROW]
[ROW][C]13[/C][C]-0.021373[/C][C]-0.2028[/C][C]0.419889[/C][/ROW]
[ROW][C]14[/C][C]0.023379[/C][C]0.2218[/C][C]0.41249[/C][/ROW]
[ROW][C]15[/C][C]-0.104372[/C][C]-0.9902[/C][C]0.162375[/C][/ROW]
[ROW][C]16[/C][C]-0.183887[/C][C]-1.7445[/C][C]0.042243[/C][/ROW]
[ROW][C]17[/C][C]0.00796[/C][C]0.0755[/C][C]0.469987[/C][/ROW]
[ROW][C]18[/C][C]0.038654[/C][C]0.3667[/C][C]0.357352[/C][/ROW]
[ROW][C]19[/C][C]0.071604[/C][C]0.6793[/C][C]0.249346[/C][/ROW]
[ROW][C]20[/C][C]-0.005718[/C][C]-0.0542[/C][C]0.47843[/C][/ROW]
[ROW][C]21[/C][C]-0.058083[/C][C]-0.551[/C][C]0.29149[/C][/ROW]
[ROW][C]22[/C][C]0.015494[/C][C]0.147[/C][C]0.441734[/C][/ROW]
[ROW][C]23[/C][C]-0.040676[/C][C]-0.3859[/C][C]0.350245[/C][/ROW]
[ROW][C]24[/C][C]0.075463[/C][C]0.7159[/C][C]0.237953[/C][/ROW]
[ROW][C]25[/C][C]-0.038681[/C][C]-0.367[/C][C]0.357253[/C][/ROW]
[ROW][C]26[/C][C]0.038765[/C][C]0.3678[/C][C]0.356958[/C][/ROW]
[ROW][C]27[/C][C]0.114084[/C][C]1.0823[/C][C]0.141006[/C][/ROW]
[ROW][C]28[/C][C]-0.071641[/C][C]-0.6796[/C][C]0.249237[/C][/ROW]
[ROW][C]29[/C][C]0.063844[/C][C]0.6057[/C][C]0.273126[/C][/ROW]
[ROW][C]30[/C][C]-0.170375[/C][C]-1.6163[/C][C]0.054763[/C][/ROW]
[ROW][C]31[/C][C]-0.033148[/C][C]-0.3145[/C][C]0.376944[/C][/ROW]
[ROW][C]32[/C][C]-0.038761[/C][C]-0.3677[/C][C]0.356973[/C][/ROW]
[ROW][C]33[/C][C]0.127742[/C][C]1.2119[/C][C]0.114367[/C][/ROW]
[ROW][C]34[/C][C]0.106653[/C][C]1.0118[/C][C]0.157173[/C][/ROW]
[ROW][C]35[/C][C]-0.081006[/C][C]-0.7685[/C][C]0.222103[/C][/ROW]
[ROW][C]36[/C][C]-0.065919[/C][C]-0.6254[/C][C]0.266659[/C][/ROW]
[ROW][C]37[/C][C]-0.073982[/C][C]-0.7019[/C][C]0.242291[/C][/ROW]
[ROW][C]38[/C][C]0.022618[/C][C]0.2146[/C][C]0.415294[/C][/ROW]
[ROW][C]39[/C][C]0.131276[/C][C]1.2454[/C][C]0.10811[/C][/ROW]
[ROW][C]40[/C][C]0.033189[/C][C]0.3149[/C][C]0.376798[/C][/ROW]
[ROW][C]41[/C][C]0.060465[/C][C]0.5736[/C][C]0.283827[/C][/ROW]
[ROW][C]42[/C][C]-0.077346[/C][C]-0.7338[/C][C]0.232499[/C][/ROW]
[ROW][C]43[/C][C]-0.00035[/C][C]-0.0033[/C][C]0.498678[/C][/ROW]
[ROW][C]44[/C][C]-0.149318[/C][C]-1.4166[/C][C]0.080033[/C][/ROW]
[ROW][C]45[/C][C]0.019249[/C][C]0.1826[/C][C]0.427755[/C][/ROW]
[ROW][C]46[/C][C]-0.00371[/C][C]-0.0352[/C][C]0.486[/C][/ROW]
[ROW][C]47[/C][C]0.007895[/C][C]0.0749[/C][C]0.470229[/C][/ROW]
[ROW][C]48[/C][C]0.057806[/C][C]0.5484[/C][C]0.292388[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31753&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
10.0636470.60380.273746
2-0.143101-1.35760.088996
3-0.417689-3.96257.4e-05
4-0.328957-3.12080.001212
50.121871.15620.125338
60.2419422.29530.012021
70.1452741.37820.08578
8-0.11777-1.11730.133427
9-0.206894-1.96280.026381
10-0.075407-0.71540.238116
110.0445370.42250.336829
120.3714843.52420.000335
13-0.021373-0.20280.419889
140.0233790.22180.41249
15-0.104372-0.99020.162375
16-0.183887-1.74450.042243
170.007960.07550.469987
180.0386540.36670.357352
190.0716040.67930.249346
20-0.005718-0.05420.47843
21-0.058083-0.5510.29149
220.0154940.1470.441734
23-0.040676-0.38590.350245
240.0754630.71590.237953
25-0.038681-0.3670.357253
260.0387650.36780.356958
270.1140841.08230.141006
28-0.071641-0.67960.249237
290.0638440.60570.273126
30-0.170375-1.61630.054763
31-0.033148-0.31450.376944
32-0.038761-0.36770.356973
330.1277421.21190.114367
340.1066531.01180.157173
35-0.081006-0.76850.222103
36-0.065919-0.62540.266659
37-0.073982-0.70190.242291
380.0226180.21460.415294
390.1312761.24540.10811
400.0331890.31490.376798
410.0604650.57360.283827
42-0.077346-0.73380.232499
43-0.00035-0.00330.498678
44-0.149318-1.41660.080033
450.0192490.18260.427755
46-0.00371-0.03520.486
470.0078950.07490.470229
480.0578060.54840.292388







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0636470.60380.273746
2-0.14775-1.40170.082225
3-0.408364-3.87410.000101
4-0.387472-3.67590.000201
5-0.039728-0.37690.353569
6-0.032686-0.31010.378607
7-0.148752-1.41120.080819
8-0.249551-2.36750.010027
9-0.202956-1.92540.028668
10-0.148054-1.40460.081796
11-0.255348-2.42240.00871
120.0979540.92930.177617
13-0.223946-2.12450.018183
140.0226360.21470.415226
150.1412711.34020.091774
16-0.011869-0.11260.4553
17-0.014134-0.13410.446817
180.075430.71560.238048
190.085460.81070.209824
20-0.008714-0.08270.467151
21-0.011485-0.1090.456739
220.1071041.01610.156159
23-0.028267-0.26820.394593
24-0.104346-0.98990.162435
25-0.0811-0.76940.221841
26-0.115547-1.09620.137963
270.0616140.58450.280166
28-0.082142-0.77930.218933
290.0818330.77630.219792
30-0.114384-1.08510.140378
310.0539970.51230.304862
32-0.054159-0.51380.304326
330.1247981.18390.119778
340.0358790.34040.367181
35-0.021756-0.20640.418475
36-0.006473-0.06140.475584
370.0434850.41250.340464
38-0.063107-0.59870.275442
39-0.125267-1.18840.118904
40-0.02284-0.21670.414474
41-0.065399-0.62040.268273
420.0701820.66580.253619
430.1109441.05250.147692
44-0.078314-0.7430.229723
450.0006490.00620.497549
460.0201380.1910.42446
47-0.013714-0.13010.44839
48-0.085793-0.81390.208924

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.063647 & 0.6038 & 0.273746 \tabularnewline
2 & -0.14775 & -1.4017 & 0.082225 \tabularnewline
3 & -0.408364 & -3.8741 & 0.000101 \tabularnewline
4 & -0.387472 & -3.6759 & 0.000201 \tabularnewline
5 & -0.039728 & -0.3769 & 0.353569 \tabularnewline
6 & -0.032686 & -0.3101 & 0.378607 \tabularnewline
7 & -0.148752 & -1.4112 & 0.080819 \tabularnewline
8 & -0.249551 & -2.3675 & 0.010027 \tabularnewline
9 & -0.202956 & -1.9254 & 0.028668 \tabularnewline
10 & -0.148054 & -1.4046 & 0.081796 \tabularnewline
11 & -0.255348 & -2.4224 & 0.00871 \tabularnewline
12 & 0.097954 & 0.9293 & 0.177617 \tabularnewline
13 & -0.223946 & -2.1245 & 0.018183 \tabularnewline
14 & 0.022636 & 0.2147 & 0.415226 \tabularnewline
15 & 0.141271 & 1.3402 & 0.091774 \tabularnewline
16 & -0.011869 & -0.1126 & 0.4553 \tabularnewline
17 & -0.014134 & -0.1341 & 0.446817 \tabularnewline
18 & 0.07543 & 0.7156 & 0.238048 \tabularnewline
19 & 0.08546 & 0.8107 & 0.209824 \tabularnewline
20 & -0.008714 & -0.0827 & 0.467151 \tabularnewline
21 & -0.011485 & -0.109 & 0.456739 \tabularnewline
22 & 0.107104 & 1.0161 & 0.156159 \tabularnewline
23 & -0.028267 & -0.2682 & 0.394593 \tabularnewline
24 & -0.104346 & -0.9899 & 0.162435 \tabularnewline
25 & -0.0811 & -0.7694 & 0.221841 \tabularnewline
26 & -0.115547 & -1.0962 & 0.137963 \tabularnewline
27 & 0.061614 & 0.5845 & 0.280166 \tabularnewline
28 & -0.082142 & -0.7793 & 0.218933 \tabularnewline
29 & 0.081833 & 0.7763 & 0.219792 \tabularnewline
30 & -0.114384 & -1.0851 & 0.140378 \tabularnewline
31 & 0.053997 & 0.5123 & 0.304862 \tabularnewline
32 & -0.054159 & -0.5138 & 0.304326 \tabularnewline
33 & 0.124798 & 1.1839 & 0.119778 \tabularnewline
34 & 0.035879 & 0.3404 & 0.367181 \tabularnewline
35 & -0.021756 & -0.2064 & 0.418475 \tabularnewline
36 & -0.006473 & -0.0614 & 0.475584 \tabularnewline
37 & 0.043485 & 0.4125 & 0.340464 \tabularnewline
38 & -0.063107 & -0.5987 & 0.275442 \tabularnewline
39 & -0.125267 & -1.1884 & 0.118904 \tabularnewline
40 & -0.02284 & -0.2167 & 0.414474 \tabularnewline
41 & -0.065399 & -0.6204 & 0.268273 \tabularnewline
42 & 0.070182 & 0.6658 & 0.253619 \tabularnewline
43 & 0.110944 & 1.0525 & 0.147692 \tabularnewline
44 & -0.078314 & -0.743 & 0.229723 \tabularnewline
45 & 0.000649 & 0.0062 & 0.497549 \tabularnewline
46 & 0.020138 & 0.191 & 0.42446 \tabularnewline
47 & -0.013714 & -0.1301 & 0.44839 \tabularnewline
48 & -0.085793 & -0.8139 & 0.208924 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31753&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]0.063647[/C][C]0.6038[/C][C]0.273746[/C][/ROW]
[ROW][C]2[/C][C]-0.14775[/C][C]-1.4017[/C][C]0.082225[/C][/ROW]
[ROW][C]3[/C][C]-0.408364[/C][C]-3.8741[/C][C]0.000101[/C][/ROW]
[ROW][C]4[/C][C]-0.387472[/C][C]-3.6759[/C][C]0.000201[/C][/ROW]
[ROW][C]5[/C][C]-0.039728[/C][C]-0.3769[/C][C]0.353569[/C][/ROW]
[ROW][C]6[/C][C]-0.032686[/C][C]-0.3101[/C][C]0.378607[/C][/ROW]
[ROW][C]7[/C][C]-0.148752[/C][C]-1.4112[/C][C]0.080819[/C][/ROW]
[ROW][C]8[/C][C]-0.249551[/C][C]-2.3675[/C][C]0.010027[/C][/ROW]
[ROW][C]9[/C][C]-0.202956[/C][C]-1.9254[/C][C]0.028668[/C][/ROW]
[ROW][C]10[/C][C]-0.148054[/C][C]-1.4046[/C][C]0.081796[/C][/ROW]
[ROW][C]11[/C][C]-0.255348[/C][C]-2.4224[/C][C]0.00871[/C][/ROW]
[ROW][C]12[/C][C]0.097954[/C][C]0.9293[/C][C]0.177617[/C][/ROW]
[ROW][C]13[/C][C]-0.223946[/C][C]-2.1245[/C][C]0.018183[/C][/ROW]
[ROW][C]14[/C][C]0.022636[/C][C]0.2147[/C][C]0.415226[/C][/ROW]
[ROW][C]15[/C][C]0.141271[/C][C]1.3402[/C][C]0.091774[/C][/ROW]
[ROW][C]16[/C][C]-0.011869[/C][C]-0.1126[/C][C]0.4553[/C][/ROW]
[ROW][C]17[/C][C]-0.014134[/C][C]-0.1341[/C][C]0.446817[/C][/ROW]
[ROW][C]18[/C][C]0.07543[/C][C]0.7156[/C][C]0.238048[/C][/ROW]
[ROW][C]19[/C][C]0.08546[/C][C]0.8107[/C][C]0.209824[/C][/ROW]
[ROW][C]20[/C][C]-0.008714[/C][C]-0.0827[/C][C]0.467151[/C][/ROW]
[ROW][C]21[/C][C]-0.011485[/C][C]-0.109[/C][C]0.456739[/C][/ROW]
[ROW][C]22[/C][C]0.107104[/C][C]1.0161[/C][C]0.156159[/C][/ROW]
[ROW][C]23[/C][C]-0.028267[/C][C]-0.2682[/C][C]0.394593[/C][/ROW]
[ROW][C]24[/C][C]-0.104346[/C][C]-0.9899[/C][C]0.162435[/C][/ROW]
[ROW][C]25[/C][C]-0.0811[/C][C]-0.7694[/C][C]0.221841[/C][/ROW]
[ROW][C]26[/C][C]-0.115547[/C][C]-1.0962[/C][C]0.137963[/C][/ROW]
[ROW][C]27[/C][C]0.061614[/C][C]0.5845[/C][C]0.280166[/C][/ROW]
[ROW][C]28[/C][C]-0.082142[/C][C]-0.7793[/C][C]0.218933[/C][/ROW]
[ROW][C]29[/C][C]0.081833[/C][C]0.7763[/C][C]0.219792[/C][/ROW]
[ROW][C]30[/C][C]-0.114384[/C][C]-1.0851[/C][C]0.140378[/C][/ROW]
[ROW][C]31[/C][C]0.053997[/C][C]0.5123[/C][C]0.304862[/C][/ROW]
[ROW][C]32[/C][C]-0.054159[/C][C]-0.5138[/C][C]0.304326[/C][/ROW]
[ROW][C]33[/C][C]0.124798[/C][C]1.1839[/C][C]0.119778[/C][/ROW]
[ROW][C]34[/C][C]0.035879[/C][C]0.3404[/C][C]0.367181[/C][/ROW]
[ROW][C]35[/C][C]-0.021756[/C][C]-0.2064[/C][C]0.418475[/C][/ROW]
[ROW][C]36[/C][C]-0.006473[/C][C]-0.0614[/C][C]0.475584[/C][/ROW]
[ROW][C]37[/C][C]0.043485[/C][C]0.4125[/C][C]0.340464[/C][/ROW]
[ROW][C]38[/C][C]-0.063107[/C][C]-0.5987[/C][C]0.275442[/C][/ROW]
[ROW][C]39[/C][C]-0.125267[/C][C]-1.1884[/C][C]0.118904[/C][/ROW]
[ROW][C]40[/C][C]-0.02284[/C][C]-0.2167[/C][C]0.414474[/C][/ROW]
[ROW][C]41[/C][C]-0.065399[/C][C]-0.6204[/C][C]0.268273[/C][/ROW]
[ROW][C]42[/C][C]0.070182[/C][C]0.6658[/C][C]0.253619[/C][/ROW]
[ROW][C]43[/C][C]0.110944[/C][C]1.0525[/C][C]0.147692[/C][/ROW]
[ROW][C]44[/C][C]-0.078314[/C][C]-0.743[/C][C]0.229723[/C][/ROW]
[ROW][C]45[/C][C]0.000649[/C][C]0.0062[/C][C]0.497549[/C][/ROW]
[ROW][C]46[/C][C]0.020138[/C][C]0.191[/C][C]0.42446[/C][/ROW]
[ROW][C]47[/C][C]-0.013714[/C][C]-0.1301[/C][C]0.44839[/C][/ROW]
[ROW][C]48[/C][C]-0.085793[/C][C]-0.8139[/C][C]0.208924[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31753&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31753&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
10.0636470.60380.273746
2-0.14775-1.40170.082225
3-0.408364-3.87410.000101
4-0.387472-3.67590.000201
5-0.039728-0.37690.353569
6-0.032686-0.31010.378607
7-0.148752-1.41120.080819
8-0.249551-2.36750.010027
9-0.202956-1.92540.028668
10-0.148054-1.40460.081796
11-0.255348-2.42240.00871
120.0979540.92930.177617
13-0.223946-2.12450.018183
140.0226360.21470.415226
150.1412711.34020.091774
16-0.011869-0.11260.4553
17-0.014134-0.13410.446817
180.075430.71560.238048
190.085460.81070.209824
20-0.008714-0.08270.467151
21-0.011485-0.1090.456739
220.1071041.01610.156159
23-0.028267-0.26820.394593
24-0.104346-0.98990.162435
25-0.0811-0.76940.221841
26-0.115547-1.09620.137963
270.0616140.58450.280166
28-0.082142-0.77930.218933
290.0818330.77630.219792
30-0.114384-1.08510.140378
310.0539970.51230.304862
32-0.054159-0.51380.304326
330.1247981.18390.119778
340.0358790.34040.367181
35-0.021756-0.20640.418475
36-0.006473-0.06140.475584
370.0434850.41250.340464
38-0.063107-0.59870.275442
39-0.125267-1.18840.118904
40-0.02284-0.21670.414474
41-0.065399-0.62040.268273
420.0701820.66580.253619
430.1109441.05250.147692
44-0.078314-0.7430.229723
450.0006490.00620.497549
460.0201380.1910.42446
47-0.013714-0.13010.44839
48-0.085793-0.81390.208924



Parameters (Session):
par1 = 48 ; par2 = 1.0 ; par3 = 2 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1.0 ; par3 = 2 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')