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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, 21 Dec 2010 19:24:27 +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/Dec/21/t12929593498xde18836whbtss.htm/, Retrieved Thu, 31 Oct 2024 23:53:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113868, Retrieved Thu, 31 Oct 2024 23:53:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact216
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [Unemployment] [2010-11-29 09:29:57] [b98453cac15ba1066b407e146608df68]
-   PD  [Variance Reduction Matrix] [WS9 - Variance Re...] [2010-12-04 11:04:59] [8ef49741e164ec6343c90c7935194465]
-   P     [Variance Reduction Matrix] [WS 9 VRM] [2010-12-05 14:01:21] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD      [(Partial) Autocorrelation Function] [paper ACF] [2010-12-10 10:47:04] [8214fe6d084e5ad7598b249a26cc9f06]
-    D        [(Partial) Autocorrelation Function] [acf] [2010-12-20 19:45:58] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD            [(Partial) Autocorrelation Function] [acf laaggeschoolden] [2010-12-21 19:24:27] [b47314d83d48c7bf812ec2bcd743b159] [Current]
-   PD              [(Partial) Autocorrelation Function] [acf 1 middengesch...] [2010-12-22 14:24:40] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                [(Partial) Autocorrelation Function] [acf 1 hooggeschoo...] [2010-12-22 14:27:57] [8214fe6d084e5ad7598b249a26cc9f06]
-   P                   [(Partial) Autocorrelation Function] [acf 2 hooggeschoo...] [2010-12-22 14:30:09] [8214fe6d084e5ad7598b249a26cc9f06]
-                     [(Partial) Autocorrelation Function] [acf 2 middengesch...] [2010-12-22 14:31:49] [8214fe6d084e5ad7598b249a26cc9f06]
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Dataseries X:
104708
101817
97898
95559
92822
90848
101141
105841
93647
90923
89130
90212
93196
91861
90593
89895
88819
87924
96906
101217
98709
98139
95529
98577
100772
100180
99200
96251
94514
93780
105192
107682
99687
99436
102049
102673
105813
105056
103916
103513
101893
102503
113149
116696
108500
107800
105941
108742
111680
111270
110698
108517
107127
107088
116321
125045
116779
122887
120162
123198
123610
122293
121289
119393
117494
116693
125062
127281
120195
119804
117113
119240
115823
116281
113816
114632
112987
111633
116721
114850
112797
105368
102524
101327
102612
98873
95993
93244
90403
88539
98106
96963
90781
89253
87794
89810
90864
89025
87621
87718
83433
84535
92223
91052
88456
88706
89137
94066
99258
100673
102269
100833
99314
101764
108242
108148
104761
103772
103737
111043
109906
109335
107247
105690
102755
102280
110590
109122
102803
101424
99138




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113868&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113868&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113868&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'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.92697510.60970
20.8458599.68130
30.8090249.25970
40.7999389.15570
50.804049.20270
60.7833998.96640
70.7251398.29960
80.6426077.3550
90.5758336.59070
100.5317856.08660
110.5360076.13490
120.5281756.04520
130.4230164.84162e-06
140.3126723.57870.000242
150.242222.77230.003189
160.2019672.31160.01118
170.1774062.03050.022165
180.1363891.5610.060463
190.0642470.73530.231725
20-0.022399-0.25640.399036
21-0.090426-1.0350.151294
22-0.13426-1.53670.063392
23-0.126727-1.45050.07466
24-0.134541-1.53990.063
25-0.225413-2.580.005492
26-0.31535-3.60930.000218
27-0.354529-4.05784.2e-05
28-0.369107-4.22462.2e-05
29-0.366335-4.19292.5e-05
30-0.378389-4.33091.5e-05
31-0.412006-4.71563e-06
32-0.452968-5.18450
33-0.476675-5.45580
34-0.479-5.48240
35-0.435245-4.98161e-06
36-0.407469-4.66374e-06
37-0.454201-5.19860
38-0.499123-5.71270
39-0.504706-5.77660
40-0.488232-5.58810
41-0.454336-5.20010
42-0.438656-5.02071e-06
43-0.444233-5.08451e-06
44-0.459388-5.25790
45-0.462152-5.28960
46-0.443456-5.07561e-06
47-0.387787-4.43841e-05
48-0.343472-3.93126.8e-05

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.926975 & 10.6097 & 0 \tabularnewline
2 & 0.845859 & 9.6813 & 0 \tabularnewline
3 & 0.809024 & 9.2597 & 0 \tabularnewline
4 & 0.799938 & 9.1557 & 0 \tabularnewline
5 & 0.80404 & 9.2027 & 0 \tabularnewline
6 & 0.783399 & 8.9664 & 0 \tabularnewline
7 & 0.725139 & 8.2996 & 0 \tabularnewline
8 & 0.642607 & 7.355 & 0 \tabularnewline
9 & 0.575833 & 6.5907 & 0 \tabularnewline
10 & 0.531785 & 6.0866 & 0 \tabularnewline
11 & 0.536007 & 6.1349 & 0 \tabularnewline
12 & 0.528175 & 6.0452 & 0 \tabularnewline
13 & 0.423016 & 4.8416 & 2e-06 \tabularnewline
14 & 0.312672 & 3.5787 & 0.000242 \tabularnewline
15 & 0.24222 & 2.7723 & 0.003189 \tabularnewline
16 & 0.201967 & 2.3116 & 0.01118 \tabularnewline
17 & 0.177406 & 2.0305 & 0.022165 \tabularnewline
18 & 0.136389 & 1.561 & 0.060463 \tabularnewline
19 & 0.064247 & 0.7353 & 0.231725 \tabularnewline
20 & -0.022399 & -0.2564 & 0.399036 \tabularnewline
21 & -0.090426 & -1.035 & 0.151294 \tabularnewline
22 & -0.13426 & -1.5367 & 0.063392 \tabularnewline
23 & -0.126727 & -1.4505 & 0.07466 \tabularnewline
24 & -0.134541 & -1.5399 & 0.063 \tabularnewline
25 & -0.225413 & -2.58 & 0.005492 \tabularnewline
26 & -0.31535 & -3.6093 & 0.000218 \tabularnewline
27 & -0.354529 & -4.0578 & 4.2e-05 \tabularnewline
28 & -0.369107 & -4.2246 & 2.2e-05 \tabularnewline
29 & -0.366335 & -4.1929 & 2.5e-05 \tabularnewline
30 & -0.378389 & -4.3309 & 1.5e-05 \tabularnewline
31 & -0.412006 & -4.7156 & 3e-06 \tabularnewline
32 & -0.452968 & -5.1845 & 0 \tabularnewline
33 & -0.476675 & -5.4558 & 0 \tabularnewline
34 & -0.479 & -5.4824 & 0 \tabularnewline
35 & -0.435245 & -4.9816 & 1e-06 \tabularnewline
36 & -0.407469 & -4.6637 & 4e-06 \tabularnewline
37 & -0.454201 & -5.1986 & 0 \tabularnewline
38 & -0.499123 & -5.7127 & 0 \tabularnewline
39 & -0.504706 & -5.7766 & 0 \tabularnewline
40 & -0.488232 & -5.5881 & 0 \tabularnewline
41 & -0.454336 & -5.2001 & 0 \tabularnewline
42 & -0.438656 & -5.0207 & 1e-06 \tabularnewline
43 & -0.444233 & -5.0845 & 1e-06 \tabularnewline
44 & -0.459388 & -5.2579 & 0 \tabularnewline
45 & -0.462152 & -5.2896 & 0 \tabularnewline
46 & -0.443456 & -5.0756 & 1e-06 \tabularnewline
47 & -0.387787 & -4.4384 & 1e-05 \tabularnewline
48 & -0.343472 & -3.9312 & 6.8e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113868&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]0.926975[/C][C]10.6097[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.845859[/C][C]9.6813[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.809024[/C][C]9.2597[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.799938[/C][C]9.1557[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.80404[/C][C]9.2027[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.783399[/C][C]8.9664[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.725139[/C][C]8.2996[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.642607[/C][C]7.355[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.575833[/C][C]6.5907[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.531785[/C][C]6.0866[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.536007[/C][C]6.1349[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.528175[/C][C]6.0452[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.423016[/C][C]4.8416[/C][C]2e-06[/C][/ROW]
[ROW][C]14[/C][C]0.312672[/C][C]3.5787[/C][C]0.000242[/C][/ROW]
[ROW][C]15[/C][C]0.24222[/C][C]2.7723[/C][C]0.003189[/C][/ROW]
[ROW][C]16[/C][C]0.201967[/C][C]2.3116[/C][C]0.01118[/C][/ROW]
[ROW][C]17[/C][C]0.177406[/C][C]2.0305[/C][C]0.022165[/C][/ROW]
[ROW][C]18[/C][C]0.136389[/C][C]1.561[/C][C]0.060463[/C][/ROW]
[ROW][C]19[/C][C]0.064247[/C][C]0.7353[/C][C]0.231725[/C][/ROW]
[ROW][C]20[/C][C]-0.022399[/C][C]-0.2564[/C][C]0.399036[/C][/ROW]
[ROW][C]21[/C][C]-0.090426[/C][C]-1.035[/C][C]0.151294[/C][/ROW]
[ROW][C]22[/C][C]-0.13426[/C][C]-1.5367[/C][C]0.063392[/C][/ROW]
[ROW][C]23[/C][C]-0.126727[/C][C]-1.4505[/C][C]0.07466[/C][/ROW]
[ROW][C]24[/C][C]-0.134541[/C][C]-1.5399[/C][C]0.063[/C][/ROW]
[ROW][C]25[/C][C]-0.225413[/C][C]-2.58[/C][C]0.005492[/C][/ROW]
[ROW][C]26[/C][C]-0.31535[/C][C]-3.6093[/C][C]0.000218[/C][/ROW]
[ROW][C]27[/C][C]-0.354529[/C][C]-4.0578[/C][C]4.2e-05[/C][/ROW]
[ROW][C]28[/C][C]-0.369107[/C][C]-4.2246[/C][C]2.2e-05[/C][/ROW]
[ROW][C]29[/C][C]-0.366335[/C][C]-4.1929[/C][C]2.5e-05[/C][/ROW]
[ROW][C]30[/C][C]-0.378389[/C][C]-4.3309[/C][C]1.5e-05[/C][/ROW]
[ROW][C]31[/C][C]-0.412006[/C][C]-4.7156[/C][C]3e-06[/C][/ROW]
[ROW][C]32[/C][C]-0.452968[/C][C]-5.1845[/C][C]0[/C][/ROW]
[ROW][C]33[/C][C]-0.476675[/C][C]-5.4558[/C][C]0[/C][/ROW]
[ROW][C]34[/C][C]-0.479[/C][C]-5.4824[/C][C]0[/C][/ROW]
[ROW][C]35[/C][C]-0.435245[/C][C]-4.9816[/C][C]1e-06[/C][/ROW]
[ROW][C]36[/C][C]-0.407469[/C][C]-4.6637[/C][C]4e-06[/C][/ROW]
[ROW][C]37[/C][C]-0.454201[/C][C]-5.1986[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]-0.499123[/C][C]-5.7127[/C][C]0[/C][/ROW]
[ROW][C]39[/C][C]-0.504706[/C][C]-5.7766[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]-0.488232[/C][C]-5.5881[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]-0.454336[/C][C]-5.2001[/C][C]0[/C][/ROW]
[ROW][C]42[/C][C]-0.438656[/C][C]-5.0207[/C][C]1e-06[/C][/ROW]
[ROW][C]43[/C][C]-0.444233[/C][C]-5.0845[/C][C]1e-06[/C][/ROW]
[ROW][C]44[/C][C]-0.459388[/C][C]-5.2579[/C][C]0[/C][/ROW]
[ROW][C]45[/C][C]-0.462152[/C][C]-5.2896[/C][C]0[/C][/ROW]
[ROW][C]46[/C][C]-0.443456[/C][C]-5.0756[/C][C]1e-06[/C][/ROW]
[ROW][C]47[/C][C]-0.387787[/C][C]-4.4384[/C][C]1e-05[/C][/ROW]
[ROW][C]48[/C][C]-0.343472[/C][C]-3.9312[/C][C]6.8e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113868&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113868&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
10.92697510.60970
20.8458599.68130
30.8090249.25970
40.7999389.15570
50.804049.20270
60.7833998.96640
70.7251398.29960
80.6426077.3550
90.5758336.59070
100.5317856.08660
110.5360076.13490
120.5281756.04520
130.4230164.84162e-06
140.3126723.57870.000242
150.242222.77230.003189
160.2019672.31160.01118
170.1774062.03050.022165
180.1363891.5610.060463
190.0642470.73530.231725
20-0.022399-0.25640.399036
21-0.090426-1.0350.151294
22-0.13426-1.53670.063392
23-0.126727-1.45050.07466
24-0.134541-1.53990.063
25-0.225413-2.580.005492
26-0.31535-3.60930.000218
27-0.354529-4.05784.2e-05
28-0.369107-4.22462.2e-05
29-0.366335-4.19292.5e-05
30-0.378389-4.33091.5e-05
31-0.412006-4.71563e-06
32-0.452968-5.18450
33-0.476675-5.45580
34-0.479-5.48240
35-0.435245-4.98161e-06
36-0.407469-4.66374e-06
37-0.454201-5.19860
38-0.499123-5.71270
39-0.504706-5.77660
40-0.488232-5.58810
41-0.454336-5.20010
42-0.438656-5.02071e-06
43-0.444233-5.08451e-06
44-0.459388-5.25790
45-0.462152-5.28960
46-0.443456-5.07561e-06
47-0.387787-4.43841e-05
48-0.343472-3.93126.8e-05







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.92697510.60970
2-0.095396-1.09190.13845
30.2765713.16550.000963
40.1472981.68590.047098
50.1756052.00990.023248
6-0.087052-0.99640.160456
7-0.181594-2.07840.019811
8-0.267132-3.05750.001353
9-0.10655-1.21950.11242
10-0.114698-1.31280.095776
110.327133.74420.000135
120.0016650.01910.492414
13-0.538178-6.15970
14-0.027624-0.31620.37619
15-0.006197-0.07090.47178
16-0.045314-0.51860.302442
170.0034040.0390.484493
18-0.011866-0.13580.44609
190.003460.03960.484234
200.0009930.01140.495474
210.0240610.27540.391723
22-0.01003-0.11480.454389
230.0945531.08220.140575
24-0.065005-0.7440.229099
25-0.232364-2.65950.004401
26-0.013567-0.15530.438418
270.1624471.85930.032615
28-0.117922-1.34970.089724
290.0533210.61030.271365
30-0.020018-0.22910.409568
310.1250721.43150.077332
320.0101370.1160.453906
330.0319070.36520.357778
34-0.07188-0.82270.206086
350.0129790.14860.441068
36-0.063213-0.72350.235331
37-0.095857-1.09710.137298
38-0.084381-0.96580.167967
39-0.088243-1.010.157181
40-0.083386-0.95440.17082
410.0488820.55950.288396
42-0.056375-0.64520.259948
430.0432280.49480.310795
44-0.064711-0.74070.230115
45-0.00618-0.07070.47186
460.0027940.0320.487271
47-0.057156-0.65420.25707
480.0700840.80210.211961

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.926975 & 10.6097 & 0 \tabularnewline
2 & -0.095396 & -1.0919 & 0.13845 \tabularnewline
3 & 0.276571 & 3.1655 & 0.000963 \tabularnewline
4 & 0.147298 & 1.6859 & 0.047098 \tabularnewline
5 & 0.175605 & 2.0099 & 0.023248 \tabularnewline
6 & -0.087052 & -0.9964 & 0.160456 \tabularnewline
7 & -0.181594 & -2.0784 & 0.019811 \tabularnewline
8 & -0.267132 & -3.0575 & 0.001353 \tabularnewline
9 & -0.10655 & -1.2195 & 0.11242 \tabularnewline
10 & -0.114698 & -1.3128 & 0.095776 \tabularnewline
11 & 0.32713 & 3.7442 & 0.000135 \tabularnewline
12 & 0.001665 & 0.0191 & 0.492414 \tabularnewline
13 & -0.538178 & -6.1597 & 0 \tabularnewline
14 & -0.027624 & -0.3162 & 0.37619 \tabularnewline
15 & -0.006197 & -0.0709 & 0.47178 \tabularnewline
16 & -0.045314 & -0.5186 & 0.302442 \tabularnewline
17 & 0.003404 & 0.039 & 0.484493 \tabularnewline
18 & -0.011866 & -0.1358 & 0.44609 \tabularnewline
19 & 0.00346 & 0.0396 & 0.484234 \tabularnewline
20 & 0.000993 & 0.0114 & 0.495474 \tabularnewline
21 & 0.024061 & 0.2754 & 0.391723 \tabularnewline
22 & -0.01003 & -0.1148 & 0.454389 \tabularnewline
23 & 0.094553 & 1.0822 & 0.140575 \tabularnewline
24 & -0.065005 & -0.744 & 0.229099 \tabularnewline
25 & -0.232364 & -2.6595 & 0.004401 \tabularnewline
26 & -0.013567 & -0.1553 & 0.438418 \tabularnewline
27 & 0.162447 & 1.8593 & 0.032615 \tabularnewline
28 & -0.117922 & -1.3497 & 0.089724 \tabularnewline
29 & 0.053321 & 0.6103 & 0.271365 \tabularnewline
30 & -0.020018 & -0.2291 & 0.409568 \tabularnewline
31 & 0.125072 & 1.4315 & 0.077332 \tabularnewline
32 & 0.010137 & 0.116 & 0.453906 \tabularnewline
33 & 0.031907 & 0.3652 & 0.357778 \tabularnewline
34 & -0.07188 & -0.8227 & 0.206086 \tabularnewline
35 & 0.012979 & 0.1486 & 0.441068 \tabularnewline
36 & -0.063213 & -0.7235 & 0.235331 \tabularnewline
37 & -0.095857 & -1.0971 & 0.137298 \tabularnewline
38 & -0.084381 & -0.9658 & 0.167967 \tabularnewline
39 & -0.088243 & -1.01 & 0.157181 \tabularnewline
40 & -0.083386 & -0.9544 & 0.17082 \tabularnewline
41 & 0.048882 & 0.5595 & 0.288396 \tabularnewline
42 & -0.056375 & -0.6452 & 0.259948 \tabularnewline
43 & 0.043228 & 0.4948 & 0.310795 \tabularnewline
44 & -0.064711 & -0.7407 & 0.230115 \tabularnewline
45 & -0.00618 & -0.0707 & 0.47186 \tabularnewline
46 & 0.002794 & 0.032 & 0.487271 \tabularnewline
47 & -0.057156 & -0.6542 & 0.25707 \tabularnewline
48 & 0.070084 & 0.8021 & 0.211961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113868&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]0.926975[/C][C]10.6097[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.095396[/C][C]-1.0919[/C][C]0.13845[/C][/ROW]
[ROW][C]3[/C][C]0.276571[/C][C]3.1655[/C][C]0.000963[/C][/ROW]
[ROW][C]4[/C][C]0.147298[/C][C]1.6859[/C][C]0.047098[/C][/ROW]
[ROW][C]5[/C][C]0.175605[/C][C]2.0099[/C][C]0.023248[/C][/ROW]
[ROW][C]6[/C][C]-0.087052[/C][C]-0.9964[/C][C]0.160456[/C][/ROW]
[ROW][C]7[/C][C]-0.181594[/C][C]-2.0784[/C][C]0.019811[/C][/ROW]
[ROW][C]8[/C][C]-0.267132[/C][C]-3.0575[/C][C]0.001353[/C][/ROW]
[ROW][C]9[/C][C]-0.10655[/C][C]-1.2195[/C][C]0.11242[/C][/ROW]
[ROW][C]10[/C][C]-0.114698[/C][C]-1.3128[/C][C]0.095776[/C][/ROW]
[ROW][C]11[/C][C]0.32713[/C][C]3.7442[/C][C]0.000135[/C][/ROW]
[ROW][C]12[/C][C]0.001665[/C][C]0.0191[/C][C]0.492414[/C][/ROW]
[ROW][C]13[/C][C]-0.538178[/C][C]-6.1597[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]-0.027624[/C][C]-0.3162[/C][C]0.37619[/C][/ROW]
[ROW][C]15[/C][C]-0.006197[/C][C]-0.0709[/C][C]0.47178[/C][/ROW]
[ROW][C]16[/C][C]-0.045314[/C][C]-0.5186[/C][C]0.302442[/C][/ROW]
[ROW][C]17[/C][C]0.003404[/C][C]0.039[/C][C]0.484493[/C][/ROW]
[ROW][C]18[/C][C]-0.011866[/C][C]-0.1358[/C][C]0.44609[/C][/ROW]
[ROW][C]19[/C][C]0.00346[/C][C]0.0396[/C][C]0.484234[/C][/ROW]
[ROW][C]20[/C][C]0.000993[/C][C]0.0114[/C][C]0.495474[/C][/ROW]
[ROW][C]21[/C][C]0.024061[/C][C]0.2754[/C][C]0.391723[/C][/ROW]
[ROW][C]22[/C][C]-0.01003[/C][C]-0.1148[/C][C]0.454389[/C][/ROW]
[ROW][C]23[/C][C]0.094553[/C][C]1.0822[/C][C]0.140575[/C][/ROW]
[ROW][C]24[/C][C]-0.065005[/C][C]-0.744[/C][C]0.229099[/C][/ROW]
[ROW][C]25[/C][C]-0.232364[/C][C]-2.6595[/C][C]0.004401[/C][/ROW]
[ROW][C]26[/C][C]-0.013567[/C][C]-0.1553[/C][C]0.438418[/C][/ROW]
[ROW][C]27[/C][C]0.162447[/C][C]1.8593[/C][C]0.032615[/C][/ROW]
[ROW][C]28[/C][C]-0.117922[/C][C]-1.3497[/C][C]0.089724[/C][/ROW]
[ROW][C]29[/C][C]0.053321[/C][C]0.6103[/C][C]0.271365[/C][/ROW]
[ROW][C]30[/C][C]-0.020018[/C][C]-0.2291[/C][C]0.409568[/C][/ROW]
[ROW][C]31[/C][C]0.125072[/C][C]1.4315[/C][C]0.077332[/C][/ROW]
[ROW][C]32[/C][C]0.010137[/C][C]0.116[/C][C]0.453906[/C][/ROW]
[ROW][C]33[/C][C]0.031907[/C][C]0.3652[/C][C]0.357778[/C][/ROW]
[ROW][C]34[/C][C]-0.07188[/C][C]-0.8227[/C][C]0.206086[/C][/ROW]
[ROW][C]35[/C][C]0.012979[/C][C]0.1486[/C][C]0.441068[/C][/ROW]
[ROW][C]36[/C][C]-0.063213[/C][C]-0.7235[/C][C]0.235331[/C][/ROW]
[ROW][C]37[/C][C]-0.095857[/C][C]-1.0971[/C][C]0.137298[/C][/ROW]
[ROW][C]38[/C][C]-0.084381[/C][C]-0.9658[/C][C]0.167967[/C][/ROW]
[ROW][C]39[/C][C]-0.088243[/C][C]-1.01[/C][C]0.157181[/C][/ROW]
[ROW][C]40[/C][C]-0.083386[/C][C]-0.9544[/C][C]0.17082[/C][/ROW]
[ROW][C]41[/C][C]0.048882[/C][C]0.5595[/C][C]0.288396[/C][/ROW]
[ROW][C]42[/C][C]-0.056375[/C][C]-0.6452[/C][C]0.259948[/C][/ROW]
[ROW][C]43[/C][C]0.043228[/C][C]0.4948[/C][C]0.310795[/C][/ROW]
[ROW][C]44[/C][C]-0.064711[/C][C]-0.7407[/C][C]0.230115[/C][/ROW]
[ROW][C]45[/C][C]-0.00618[/C][C]-0.0707[/C][C]0.47186[/C][/ROW]
[ROW][C]46[/C][C]0.002794[/C][C]0.032[/C][C]0.487271[/C][/ROW]
[ROW][C]47[/C][C]-0.057156[/C][C]-0.6542[/C][C]0.25707[/C][/ROW]
[ROW][C]48[/C][C]0.070084[/C][C]0.8021[/C][C]0.211961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113868&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113868&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
10.92697510.60970
2-0.095396-1.09190.13845
30.2765713.16550.000963
40.1472981.68590.047098
50.1756052.00990.023248
6-0.087052-0.99640.160456
7-0.181594-2.07840.019811
8-0.267132-3.05750.001353
9-0.10655-1.21950.11242
10-0.114698-1.31280.095776
110.327133.74420.000135
120.0016650.01910.492414
13-0.538178-6.15970
14-0.027624-0.31620.37619
15-0.006197-0.07090.47178
16-0.045314-0.51860.302442
170.0034040.0390.484493
18-0.011866-0.13580.44609
190.003460.03960.484234
200.0009930.01140.495474
210.0240610.27540.391723
22-0.01003-0.11480.454389
230.0945531.08220.140575
24-0.065005-0.7440.229099
25-0.232364-2.65950.004401
26-0.013567-0.15530.438418
270.1624471.85930.032615
28-0.117922-1.34970.089724
290.0533210.61030.271365
30-0.020018-0.22910.409568
310.1250721.43150.077332
320.0101370.1160.453906
330.0319070.36520.357778
34-0.07188-0.82270.206086
350.0129790.14860.441068
36-0.063213-0.72350.235331
37-0.095857-1.09710.137298
38-0.084381-0.96580.167967
39-0.088243-1.010.157181
40-0.083386-0.95440.17082
410.0488820.55950.288396
42-0.056375-0.64520.259948
430.0432280.49480.310795
44-0.064711-0.74070.230115
45-0.00618-0.07070.47186
460.0027940.0320.487271
47-0.057156-0.65420.25707
480.0700840.80210.211961



Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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')