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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 11:32:47 +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/t1292931052480sfbb77chmpc9.htm/, Retrieved Thu, 09 May 2024 19:44:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113293, Retrieved Thu, 09 May 2024 19:44:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [Workshop 9] [2010-12-03 10:43:29] [39c51da0be01189e8a44eb69e891b7a1]
-   P       [(Partial) Autocorrelation Function] [Workshop 9] [2010-12-03 10:48:00] [39c51da0be01189e8a44eb69e891b7a1]
-    D          [(Partial) Autocorrelation Function] [Autocorrelation ACF] [2010-12-21 11:32:47] [2e49bff66bb3e1f5d7fa8957e12fbb12] [Current]
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Dataseries X:
175.348
154.439
136.186
113.662
106.157
100.546
98.314
118.179
112.295
126.938
130.92
181.279
180.389
146.917
150.597
124.222
101.554
102.138
110.315
111.015
105.017
119.888
127.623
149.415
159.755
139.737
136.283
101.952
104.044
96.712
100.665
103.699
103.765
122.732
127.297
160.278
191.784
155.375
142.616
115.331
102.136
95.205
101.566
105.273
117.394
121.148
116.666
154.841
177.74
154.427
133.159
118.102
101.361
101.345
102.233
108.522
101.939
118.405
125.06
178
167.714
143.582
139.259
104.674
103.722
106.153
106.21
113.986
96.906
107.512
112.616
148.507
130.48
137.436
128.21
97.552
91.55
83.104
84.68
85.98
84.891
89.896
94.835
115.348
131.284
134.701
127.193
87.077
72.744
77.542
78.005
85.329
86.041
96.384
116.678
160.672
152.364
144.936
122.974
94.456
82.491
84.89
85.277
81.206
71.012
87.302
97.427
133.242
137.064
119.042
116.47
96.028
79.281
73.872
80.964
86.739
89.997
96.292
101.355
136.543




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 11 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113293&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113293&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113293&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 time11 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7633478.3620
20.4492944.92181e-06
30.109991.20490.11531
4-0.168032-1.84070.034068
5-0.314798-3.44840.000389
6-0.374461-4.1023.7e-05
7-0.315506-3.45620.000379
8-0.194906-2.13510.017394
90.0677990.74270.229559
100.3811194.1752.8e-05
110.6643047.27710
120.7784438.52740
130.5961586.53060
140.3496313.830.000103
150.0429730.47070.319337
16-0.207561-2.27370.01238
17-0.327896-3.59190.000238
18-0.384956-4.2172.4e-05
19-0.346459-3.79530.000116
20-0.240774-2.63750.004728
210.011090.12150.451757
220.2937293.21760.000831
230.5315985.82340
240.6538387.16240
250.5185645.68060
260.300883.2960.000645
270.0234830.25720.398716
28-0.186932-2.04770.021384
29-0.290266-3.17970.000938
30-0.344658-3.77550.000125
31-0.316175-3.46350.00037
32-0.234157-2.56510.005774
33-0.021985-0.24080.405049
340.2100772.30130.011551
350.4297154.70733e-06
360.5408425.92460
370.4165184.56276e-06
380.2175062.38270.009379
39-0.036869-0.40390.343509
40-0.214013-2.34440.010351
41-0.307776-3.37150.000503
42-0.361491-3.95996.4e-05
43-0.338993-3.71350.000156
44-0.26999-2.95760.001868
45-0.104178-1.14120.128027
460.1009351.10570.135537
470.3111033.4080.000446
480.4204154.60545e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.763347 & 8.362 & 0 \tabularnewline
2 & 0.449294 & 4.9218 & 1e-06 \tabularnewline
3 & 0.10999 & 1.2049 & 0.11531 \tabularnewline
4 & -0.168032 & -1.8407 & 0.034068 \tabularnewline
5 & -0.314798 & -3.4484 & 0.000389 \tabularnewline
6 & -0.374461 & -4.102 & 3.7e-05 \tabularnewline
7 & -0.315506 & -3.4562 & 0.000379 \tabularnewline
8 & -0.194906 & -2.1351 & 0.017394 \tabularnewline
9 & 0.067799 & 0.7427 & 0.229559 \tabularnewline
10 & 0.381119 & 4.175 & 2.8e-05 \tabularnewline
11 & 0.664304 & 7.2771 & 0 \tabularnewline
12 & 0.778443 & 8.5274 & 0 \tabularnewline
13 & 0.596158 & 6.5306 & 0 \tabularnewline
14 & 0.349631 & 3.83 & 0.000103 \tabularnewline
15 & 0.042973 & 0.4707 & 0.319337 \tabularnewline
16 & -0.207561 & -2.2737 & 0.01238 \tabularnewline
17 & -0.327896 & -3.5919 & 0.000238 \tabularnewline
18 & -0.384956 & -4.217 & 2.4e-05 \tabularnewline
19 & -0.346459 & -3.7953 & 0.000116 \tabularnewline
20 & -0.240774 & -2.6375 & 0.004728 \tabularnewline
21 & 0.01109 & 0.1215 & 0.451757 \tabularnewline
22 & 0.293729 & 3.2176 & 0.000831 \tabularnewline
23 & 0.531598 & 5.8234 & 0 \tabularnewline
24 & 0.653838 & 7.1624 & 0 \tabularnewline
25 & 0.518564 & 5.6806 & 0 \tabularnewline
26 & 0.30088 & 3.296 & 0.000645 \tabularnewline
27 & 0.023483 & 0.2572 & 0.398716 \tabularnewline
28 & -0.186932 & -2.0477 & 0.021384 \tabularnewline
29 & -0.290266 & -3.1797 & 0.000938 \tabularnewline
30 & -0.344658 & -3.7755 & 0.000125 \tabularnewline
31 & -0.316175 & -3.4635 & 0.00037 \tabularnewline
32 & -0.234157 & -2.5651 & 0.005774 \tabularnewline
33 & -0.021985 & -0.2408 & 0.405049 \tabularnewline
34 & 0.210077 & 2.3013 & 0.011551 \tabularnewline
35 & 0.429715 & 4.7073 & 3e-06 \tabularnewline
36 & 0.540842 & 5.9246 & 0 \tabularnewline
37 & 0.416518 & 4.5627 & 6e-06 \tabularnewline
38 & 0.217506 & 2.3827 & 0.009379 \tabularnewline
39 & -0.036869 & -0.4039 & 0.343509 \tabularnewline
40 & -0.214013 & -2.3444 & 0.010351 \tabularnewline
41 & -0.307776 & -3.3715 & 0.000503 \tabularnewline
42 & -0.361491 & -3.9599 & 6.4e-05 \tabularnewline
43 & -0.338993 & -3.7135 & 0.000156 \tabularnewline
44 & -0.26999 & -2.9576 & 0.001868 \tabularnewline
45 & -0.104178 & -1.1412 & 0.128027 \tabularnewline
46 & 0.100935 & 1.1057 & 0.135537 \tabularnewline
47 & 0.311103 & 3.408 & 0.000446 \tabularnewline
48 & 0.420415 & 4.6054 & 5e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113293&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]0.763347[/C][C]8.362[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.449294[/C][C]4.9218[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.10999[/C][C]1.2049[/C][C]0.11531[/C][/ROW]
[ROW][C]4[/C][C]-0.168032[/C][C]-1.8407[/C][C]0.034068[/C][/ROW]
[ROW][C]5[/C][C]-0.314798[/C][C]-3.4484[/C][C]0.000389[/C][/ROW]
[ROW][C]6[/C][C]-0.374461[/C][C]-4.102[/C][C]3.7e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.315506[/C][C]-3.4562[/C][C]0.000379[/C][/ROW]
[ROW][C]8[/C][C]-0.194906[/C][C]-2.1351[/C][C]0.017394[/C][/ROW]
[ROW][C]9[/C][C]0.067799[/C][C]0.7427[/C][C]0.229559[/C][/ROW]
[ROW][C]10[/C][C]0.381119[/C][C]4.175[/C][C]2.8e-05[/C][/ROW]
[ROW][C]11[/C][C]0.664304[/C][C]7.2771[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.778443[/C][C]8.5274[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.596158[/C][C]6.5306[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.349631[/C][C]3.83[/C][C]0.000103[/C][/ROW]
[ROW][C]15[/C][C]0.042973[/C][C]0.4707[/C][C]0.319337[/C][/ROW]
[ROW][C]16[/C][C]-0.207561[/C][C]-2.2737[/C][C]0.01238[/C][/ROW]
[ROW][C]17[/C][C]-0.327896[/C][C]-3.5919[/C][C]0.000238[/C][/ROW]
[ROW][C]18[/C][C]-0.384956[/C][C]-4.217[/C][C]2.4e-05[/C][/ROW]
[ROW][C]19[/C][C]-0.346459[/C][C]-3.7953[/C][C]0.000116[/C][/ROW]
[ROW][C]20[/C][C]-0.240774[/C][C]-2.6375[/C][C]0.004728[/C][/ROW]
[ROW][C]21[/C][C]0.01109[/C][C]0.1215[/C][C]0.451757[/C][/ROW]
[ROW][C]22[/C][C]0.293729[/C][C]3.2176[/C][C]0.000831[/C][/ROW]
[ROW][C]23[/C][C]0.531598[/C][C]5.8234[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.653838[/C][C]7.1624[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.518564[/C][C]5.6806[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.30088[/C][C]3.296[/C][C]0.000645[/C][/ROW]
[ROW][C]27[/C][C]0.023483[/C][C]0.2572[/C][C]0.398716[/C][/ROW]
[ROW][C]28[/C][C]-0.186932[/C][C]-2.0477[/C][C]0.021384[/C][/ROW]
[ROW][C]29[/C][C]-0.290266[/C][C]-3.1797[/C][C]0.000938[/C][/ROW]
[ROW][C]30[/C][C]-0.344658[/C][C]-3.7755[/C][C]0.000125[/C][/ROW]
[ROW][C]31[/C][C]-0.316175[/C][C]-3.4635[/C][C]0.00037[/C][/ROW]
[ROW][C]32[/C][C]-0.234157[/C][C]-2.5651[/C][C]0.005774[/C][/ROW]
[ROW][C]33[/C][C]-0.021985[/C][C]-0.2408[/C][C]0.405049[/C][/ROW]
[ROW][C]34[/C][C]0.210077[/C][C]2.3013[/C][C]0.011551[/C][/ROW]
[ROW][C]35[/C][C]0.429715[/C][C]4.7073[/C][C]3e-06[/C][/ROW]
[ROW][C]36[/C][C]0.540842[/C][C]5.9246[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.416518[/C][C]4.5627[/C][C]6e-06[/C][/ROW]
[ROW][C]38[/C][C]0.217506[/C][C]2.3827[/C][C]0.009379[/C][/ROW]
[ROW][C]39[/C][C]-0.036869[/C][C]-0.4039[/C][C]0.343509[/C][/ROW]
[ROW][C]40[/C][C]-0.214013[/C][C]-2.3444[/C][C]0.010351[/C][/ROW]
[ROW][C]41[/C][C]-0.307776[/C][C]-3.3715[/C][C]0.000503[/C][/ROW]
[ROW][C]42[/C][C]-0.361491[/C][C]-3.9599[/C][C]6.4e-05[/C][/ROW]
[ROW][C]43[/C][C]-0.338993[/C][C]-3.7135[/C][C]0.000156[/C][/ROW]
[ROW][C]44[/C][C]-0.26999[/C][C]-2.9576[/C][C]0.001868[/C][/ROW]
[ROW][C]45[/C][C]-0.104178[/C][C]-1.1412[/C][C]0.128027[/C][/ROW]
[ROW][C]46[/C][C]0.100935[/C][C]1.1057[/C][C]0.135537[/C][/ROW]
[ROW][C]47[/C][C]0.311103[/C][C]3.408[/C][C]0.000446[/C][/ROW]
[ROW][C]48[/C][C]0.420415[/C][C]4.6054[/C][C]5e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113293&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113293&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
10.7633478.3620
20.4492944.92181e-06
30.109991.20490.11531
4-0.168032-1.84070.034068
5-0.314798-3.44840.000389
6-0.374461-4.1023.7e-05
7-0.315506-3.45620.000379
8-0.194906-2.13510.017394
90.0677990.74270.229559
100.3811194.1752.8e-05
110.6643047.27710
120.7784438.52740
130.5961586.53060
140.3496313.830.000103
150.0429730.47070.319337
16-0.207561-2.27370.01238
17-0.327896-3.59190.000238
18-0.384956-4.2172.4e-05
19-0.346459-3.79530.000116
20-0.240774-2.63750.004728
210.011090.12150.451757
220.2937293.21760.000831
230.5315985.82340
240.6538387.16240
250.5185645.68060
260.300883.2960.000645
270.0234830.25720.398716
28-0.186932-2.04770.021384
29-0.290266-3.17970.000938
30-0.344658-3.77550.000125
31-0.316175-3.46350.00037
32-0.234157-2.56510.005774
33-0.021985-0.24080.405049
340.2100772.30130.011551
350.4297154.70733e-06
360.5408425.92460
370.4165184.56276e-06
380.2175062.38270.009379
39-0.036869-0.40390.343509
40-0.214013-2.34440.010351
41-0.307776-3.37150.000503
42-0.361491-3.95996.4e-05
43-0.338993-3.71350.000156
44-0.26999-2.95760.001868
45-0.104178-1.14120.128027
460.1009351.10570.135537
470.3111033.4080.000446
480.4204154.60545e-06







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7633478.3620
2-0.319684-3.5020.000325
3-0.263147-2.88260.002337
4-0.126691-1.38780.083879
50.0113320.12410.450707
6-0.102369-1.12140.132179
70.0479550.52530.300165
80.013680.14990.440564
90.3717974.07284.2e-05
100.3222543.53010.000295
110.3603493.94746.7e-05
120.1261921.38240.084713
13-0.335987-3.68050.000175
140.0729930.79960.21276
15-0.046434-0.50870.305964
16-0.063438-0.69490.244223
170.0891630.97670.165333
18-0.078568-0.86070.19557
19-0.039713-0.4350.33216
20-0.087747-0.96120.169188
210.0246080.26960.393976
22-0.006951-0.07610.469715
230.0065220.07140.471583
240.239432.62280.004926
25-0.112296-1.23010.110526
26-0.024485-0.26820.394497
270.0322980.35380.362051
280.0042390.04640.481521
290.1083461.18690.118812
300.0293470.32150.374203
31-0.026339-0.28850.38672
32-0.081186-0.88930.187798
33-0.021949-0.24040.4052
34-0.031669-0.34690.36463
35-0.031121-0.34090.366882
360.0471020.5160.303409
37-0.086584-0.94850.172396
38-0.092878-1.01740.155499
39-0.069093-0.75690.225305
40-0.004681-0.05130.479593
41-0.018249-0.19990.420945
42-0.046311-0.50730.306434
430.0137250.15040.440369
44-0.018066-0.19790.421726
45-0.137021-1.5010.067992
460.0054810.060.476113
470.0170630.18690.426023
480.0782060.85670.196659

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.763347 & 8.362 & 0 \tabularnewline
2 & -0.319684 & -3.502 & 0.000325 \tabularnewline
3 & -0.263147 & -2.8826 & 0.002337 \tabularnewline
4 & -0.126691 & -1.3878 & 0.083879 \tabularnewline
5 & 0.011332 & 0.1241 & 0.450707 \tabularnewline
6 & -0.102369 & -1.1214 & 0.132179 \tabularnewline
7 & 0.047955 & 0.5253 & 0.300165 \tabularnewline
8 & 0.01368 & 0.1499 & 0.440564 \tabularnewline
9 & 0.371797 & 4.0728 & 4.2e-05 \tabularnewline
10 & 0.322254 & 3.5301 & 0.000295 \tabularnewline
11 & 0.360349 & 3.9474 & 6.7e-05 \tabularnewline
12 & 0.126192 & 1.3824 & 0.084713 \tabularnewline
13 & -0.335987 & -3.6805 & 0.000175 \tabularnewline
14 & 0.072993 & 0.7996 & 0.21276 \tabularnewline
15 & -0.046434 & -0.5087 & 0.305964 \tabularnewline
16 & -0.063438 & -0.6949 & 0.244223 \tabularnewline
17 & 0.089163 & 0.9767 & 0.165333 \tabularnewline
18 & -0.078568 & -0.8607 & 0.19557 \tabularnewline
19 & -0.039713 & -0.435 & 0.33216 \tabularnewline
20 & -0.087747 & -0.9612 & 0.169188 \tabularnewline
21 & 0.024608 & 0.2696 & 0.393976 \tabularnewline
22 & -0.006951 & -0.0761 & 0.469715 \tabularnewline
23 & 0.006522 & 0.0714 & 0.471583 \tabularnewline
24 & 0.23943 & 2.6228 & 0.004926 \tabularnewline
25 & -0.112296 & -1.2301 & 0.110526 \tabularnewline
26 & -0.024485 & -0.2682 & 0.394497 \tabularnewline
27 & 0.032298 & 0.3538 & 0.362051 \tabularnewline
28 & 0.004239 & 0.0464 & 0.481521 \tabularnewline
29 & 0.108346 & 1.1869 & 0.118812 \tabularnewline
30 & 0.029347 & 0.3215 & 0.374203 \tabularnewline
31 & -0.026339 & -0.2885 & 0.38672 \tabularnewline
32 & -0.081186 & -0.8893 & 0.187798 \tabularnewline
33 & -0.021949 & -0.2404 & 0.4052 \tabularnewline
34 & -0.031669 & -0.3469 & 0.36463 \tabularnewline
35 & -0.031121 & -0.3409 & 0.366882 \tabularnewline
36 & 0.047102 & 0.516 & 0.303409 \tabularnewline
37 & -0.086584 & -0.9485 & 0.172396 \tabularnewline
38 & -0.092878 & -1.0174 & 0.155499 \tabularnewline
39 & -0.069093 & -0.7569 & 0.225305 \tabularnewline
40 & -0.004681 & -0.0513 & 0.479593 \tabularnewline
41 & -0.018249 & -0.1999 & 0.420945 \tabularnewline
42 & -0.046311 & -0.5073 & 0.306434 \tabularnewline
43 & 0.013725 & 0.1504 & 0.440369 \tabularnewline
44 & -0.018066 & -0.1979 & 0.421726 \tabularnewline
45 & -0.137021 & -1.501 & 0.067992 \tabularnewline
46 & 0.005481 & 0.06 & 0.476113 \tabularnewline
47 & 0.017063 & 0.1869 & 0.426023 \tabularnewline
48 & 0.078206 & 0.8567 & 0.196659 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113293&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]0.763347[/C][C]8.362[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.319684[/C][C]-3.502[/C][C]0.000325[/C][/ROW]
[ROW][C]3[/C][C]-0.263147[/C][C]-2.8826[/C][C]0.002337[/C][/ROW]
[ROW][C]4[/C][C]-0.126691[/C][C]-1.3878[/C][C]0.083879[/C][/ROW]
[ROW][C]5[/C][C]0.011332[/C][C]0.1241[/C][C]0.450707[/C][/ROW]
[ROW][C]6[/C][C]-0.102369[/C][C]-1.1214[/C][C]0.132179[/C][/ROW]
[ROW][C]7[/C][C]0.047955[/C][C]0.5253[/C][C]0.300165[/C][/ROW]
[ROW][C]8[/C][C]0.01368[/C][C]0.1499[/C][C]0.440564[/C][/ROW]
[ROW][C]9[/C][C]0.371797[/C][C]4.0728[/C][C]4.2e-05[/C][/ROW]
[ROW][C]10[/C][C]0.322254[/C][C]3.5301[/C][C]0.000295[/C][/ROW]
[ROW][C]11[/C][C]0.360349[/C][C]3.9474[/C][C]6.7e-05[/C][/ROW]
[ROW][C]12[/C][C]0.126192[/C][C]1.3824[/C][C]0.084713[/C][/ROW]
[ROW][C]13[/C][C]-0.335987[/C][C]-3.6805[/C][C]0.000175[/C][/ROW]
[ROW][C]14[/C][C]0.072993[/C][C]0.7996[/C][C]0.21276[/C][/ROW]
[ROW][C]15[/C][C]-0.046434[/C][C]-0.5087[/C][C]0.305964[/C][/ROW]
[ROW][C]16[/C][C]-0.063438[/C][C]-0.6949[/C][C]0.244223[/C][/ROW]
[ROW][C]17[/C][C]0.089163[/C][C]0.9767[/C][C]0.165333[/C][/ROW]
[ROW][C]18[/C][C]-0.078568[/C][C]-0.8607[/C][C]0.19557[/C][/ROW]
[ROW][C]19[/C][C]-0.039713[/C][C]-0.435[/C][C]0.33216[/C][/ROW]
[ROW][C]20[/C][C]-0.087747[/C][C]-0.9612[/C][C]0.169188[/C][/ROW]
[ROW][C]21[/C][C]0.024608[/C][C]0.2696[/C][C]0.393976[/C][/ROW]
[ROW][C]22[/C][C]-0.006951[/C][C]-0.0761[/C][C]0.469715[/C][/ROW]
[ROW][C]23[/C][C]0.006522[/C][C]0.0714[/C][C]0.471583[/C][/ROW]
[ROW][C]24[/C][C]0.23943[/C][C]2.6228[/C][C]0.004926[/C][/ROW]
[ROW][C]25[/C][C]-0.112296[/C][C]-1.2301[/C][C]0.110526[/C][/ROW]
[ROW][C]26[/C][C]-0.024485[/C][C]-0.2682[/C][C]0.394497[/C][/ROW]
[ROW][C]27[/C][C]0.032298[/C][C]0.3538[/C][C]0.362051[/C][/ROW]
[ROW][C]28[/C][C]0.004239[/C][C]0.0464[/C][C]0.481521[/C][/ROW]
[ROW][C]29[/C][C]0.108346[/C][C]1.1869[/C][C]0.118812[/C][/ROW]
[ROW][C]30[/C][C]0.029347[/C][C]0.3215[/C][C]0.374203[/C][/ROW]
[ROW][C]31[/C][C]-0.026339[/C][C]-0.2885[/C][C]0.38672[/C][/ROW]
[ROW][C]32[/C][C]-0.081186[/C][C]-0.8893[/C][C]0.187798[/C][/ROW]
[ROW][C]33[/C][C]-0.021949[/C][C]-0.2404[/C][C]0.4052[/C][/ROW]
[ROW][C]34[/C][C]-0.031669[/C][C]-0.3469[/C][C]0.36463[/C][/ROW]
[ROW][C]35[/C][C]-0.031121[/C][C]-0.3409[/C][C]0.366882[/C][/ROW]
[ROW][C]36[/C][C]0.047102[/C][C]0.516[/C][C]0.303409[/C][/ROW]
[ROW][C]37[/C][C]-0.086584[/C][C]-0.9485[/C][C]0.172396[/C][/ROW]
[ROW][C]38[/C][C]-0.092878[/C][C]-1.0174[/C][C]0.155499[/C][/ROW]
[ROW][C]39[/C][C]-0.069093[/C][C]-0.7569[/C][C]0.225305[/C][/ROW]
[ROW][C]40[/C][C]-0.004681[/C][C]-0.0513[/C][C]0.479593[/C][/ROW]
[ROW][C]41[/C][C]-0.018249[/C][C]-0.1999[/C][C]0.420945[/C][/ROW]
[ROW][C]42[/C][C]-0.046311[/C][C]-0.5073[/C][C]0.306434[/C][/ROW]
[ROW][C]43[/C][C]0.013725[/C][C]0.1504[/C][C]0.440369[/C][/ROW]
[ROW][C]44[/C][C]-0.018066[/C][C]-0.1979[/C][C]0.421726[/C][/ROW]
[ROW][C]45[/C][C]-0.137021[/C][C]-1.501[/C][C]0.067992[/C][/ROW]
[ROW][C]46[/C][C]0.005481[/C][C]0.06[/C][C]0.476113[/C][/ROW]
[ROW][C]47[/C][C]0.017063[/C][C]0.1869[/C][C]0.426023[/C][/ROW]
[ROW][C]48[/C][C]0.078206[/C][C]0.8567[/C][C]0.196659[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113293&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113293&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
10.7633478.3620
2-0.319684-3.5020.000325
3-0.263147-2.88260.002337
4-0.126691-1.38780.083879
50.0113320.12410.450707
6-0.102369-1.12140.132179
70.0479550.52530.300165
80.013680.14990.440564
90.3717974.07284.2e-05
100.3222543.53010.000295
110.3603493.94746.7e-05
120.1261921.38240.084713
13-0.335987-3.68050.000175
140.0729930.79960.21276
15-0.046434-0.50870.305964
16-0.063438-0.69490.244223
170.0891630.97670.165333
18-0.078568-0.86070.19557
19-0.039713-0.4350.33216
20-0.087747-0.96120.169188
210.0246080.26960.393976
22-0.006951-0.07610.469715
230.0065220.07140.471583
240.239432.62280.004926
25-0.112296-1.23010.110526
26-0.024485-0.26820.394497
270.0322980.35380.362051
280.0042390.04640.481521
290.1083461.18690.118812
300.0293470.32150.374203
31-0.026339-0.28850.38672
32-0.081186-0.88930.187798
33-0.021949-0.24040.4052
34-0.031669-0.34690.36463
35-0.031121-0.34090.366882
360.0471020.5160.303409
37-0.086584-0.94850.172396
38-0.092878-1.01740.155499
39-0.069093-0.75690.225305
40-0.004681-0.05130.479593
41-0.018249-0.19990.420945
42-0.046311-0.50730.306434
430.0137250.15040.440369
44-0.018066-0.19790.421726
45-0.137021-1.5010.067992
460.0054810.060.476113
470.0170630.18690.426023
480.0782060.85670.196659



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; 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')