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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 26 Nov 2012 11:39:47 -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/2012/Nov/26/t1353948022nafs1pt18jbaa4l.htm/, Retrieved Fri, 29 Mar 2024 07:06:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=193315, Retrieved Fri, 29 Mar 2024 07:06:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [WS 8 birth by month] [2012-11-10 12:40:53] [b8e296c8065082998a3b20497b32219e]
- RMPD    [(Partial) Autocorrelation Function] [WS 9 ACF] [2012-11-26 16:39:47] [09a8c52255f1f9505addc8ea27636e79] [Current]
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Dataseries X:
9676
8642
9402
9610
9294
9448
10319
9548
9801
9596
8923
9746
9829
9125
9782
9441
9162
9915
10444
10209
9985
9842
9429
10132
9849
9172
10313
9819
9955
10048
10082
10541
10208
10233
9439
9963
10158
9225
10474
9757
10490
10281
10444
10640
10695
10786
9832
9747
10411
9511
10402
9701
10540
10112
10915
11183
10384
10834
9886
10216
10943
9867
10203
10837
10573
10647
11502
10656
10866
10835
9945
10331
10718
9462
10579
10633
10346
10757
11207
11013
11015
10765
10042
10661




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193315&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193315&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193315&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4494344.11914.4e-05
20.4630574.2442.8e-05
30.5023854.60447e-06
40.217751.99570.024603
50.2638422.41810.008881
60.266262.44030.008388
70.1764711.61740.054773
80.2129731.95190.027139
90.4134323.78920.000142
100.2979392.73070.00385
110.3333293.0550.001508
120.6201885.68410
130.2562492.34860.010597
140.33743.09230.001348
150.2884172.64340.004896
160.0523380.47970.316348
170.1069480.98020.164903
180.0283890.26020.397677
190.0604170.55370.290618
200.0902490.82710.205249
210.1764611.61730.054782
220.1721421.57770.059196
230.1437511.31750.095627
240.3309853.03350.001608
250.1094151.00280.159417
260.1057340.96910.167647
270.0424390.3890.349146
28-0.064523-0.59140.277933
29-0.098744-0.9050.184027
30-0.123872-1.13530.129738
31-0.084888-0.7780.219373
32-0.108336-0.99290.161801
330.0159120.14580.442202
340.0323810.29680.383684
35-0.033717-0.3090.379034
360.1275961.16940.122769
370.0133110.1220.451597
38-0.076429-0.70050.242781
39-0.09069-0.83120.204112
40-0.14902-1.36580.087826
41-0.221564-2.03070.022726
42-0.183186-1.67890.048442
43-0.17554-1.60890.0557
44-0.244334-2.23940.013887
45-0.097518-0.89380.187
46-0.076913-0.70490.241405
47-0.160131-1.46760.07297
48-0.006493-0.05950.476345

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.449434 & 4.1191 & 4.4e-05 \tabularnewline
2 & 0.463057 & 4.244 & 2.8e-05 \tabularnewline
3 & 0.502385 & 4.6044 & 7e-06 \tabularnewline
4 & 0.21775 & 1.9957 & 0.024603 \tabularnewline
5 & 0.263842 & 2.4181 & 0.008881 \tabularnewline
6 & 0.26626 & 2.4403 & 0.008388 \tabularnewline
7 & 0.176471 & 1.6174 & 0.054773 \tabularnewline
8 & 0.212973 & 1.9519 & 0.027139 \tabularnewline
9 & 0.413432 & 3.7892 & 0.000142 \tabularnewline
10 & 0.297939 & 2.7307 & 0.00385 \tabularnewline
11 & 0.333329 & 3.055 & 0.001508 \tabularnewline
12 & 0.620188 & 5.6841 & 0 \tabularnewline
13 & 0.256249 & 2.3486 & 0.010597 \tabularnewline
14 & 0.3374 & 3.0923 & 0.001348 \tabularnewline
15 & 0.288417 & 2.6434 & 0.004896 \tabularnewline
16 & 0.052338 & 0.4797 & 0.316348 \tabularnewline
17 & 0.106948 & 0.9802 & 0.164903 \tabularnewline
18 & 0.028389 & 0.2602 & 0.397677 \tabularnewline
19 & 0.060417 & 0.5537 & 0.290618 \tabularnewline
20 & 0.090249 & 0.8271 & 0.205249 \tabularnewline
21 & 0.176461 & 1.6173 & 0.054782 \tabularnewline
22 & 0.172142 & 1.5777 & 0.059196 \tabularnewline
23 & 0.143751 & 1.3175 & 0.095627 \tabularnewline
24 & 0.330985 & 3.0335 & 0.001608 \tabularnewline
25 & 0.109415 & 1.0028 & 0.159417 \tabularnewline
26 & 0.105734 & 0.9691 & 0.167647 \tabularnewline
27 & 0.042439 & 0.389 & 0.349146 \tabularnewline
28 & -0.064523 & -0.5914 & 0.277933 \tabularnewline
29 & -0.098744 & -0.905 & 0.184027 \tabularnewline
30 & -0.123872 & -1.1353 & 0.129738 \tabularnewline
31 & -0.084888 & -0.778 & 0.219373 \tabularnewline
32 & -0.108336 & -0.9929 & 0.161801 \tabularnewline
33 & 0.015912 & 0.1458 & 0.442202 \tabularnewline
34 & 0.032381 & 0.2968 & 0.383684 \tabularnewline
35 & -0.033717 & -0.309 & 0.379034 \tabularnewline
36 & 0.127596 & 1.1694 & 0.122769 \tabularnewline
37 & 0.013311 & 0.122 & 0.451597 \tabularnewline
38 & -0.076429 & -0.7005 & 0.242781 \tabularnewline
39 & -0.09069 & -0.8312 & 0.204112 \tabularnewline
40 & -0.14902 & -1.3658 & 0.087826 \tabularnewline
41 & -0.221564 & -2.0307 & 0.022726 \tabularnewline
42 & -0.183186 & -1.6789 & 0.048442 \tabularnewline
43 & -0.17554 & -1.6089 & 0.0557 \tabularnewline
44 & -0.244334 & -2.2394 & 0.013887 \tabularnewline
45 & -0.097518 & -0.8938 & 0.187 \tabularnewline
46 & -0.076913 & -0.7049 & 0.241405 \tabularnewline
47 & -0.160131 & -1.4676 & 0.07297 \tabularnewline
48 & -0.006493 & -0.0595 & 0.476345 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193315&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]0.449434[/C][C]4.1191[/C][C]4.4e-05[/C][/ROW]
[ROW][C]2[/C][C]0.463057[/C][C]4.244[/C][C]2.8e-05[/C][/ROW]
[ROW][C]3[/C][C]0.502385[/C][C]4.6044[/C][C]7e-06[/C][/ROW]
[ROW][C]4[/C][C]0.21775[/C][C]1.9957[/C][C]0.024603[/C][/ROW]
[ROW][C]5[/C][C]0.263842[/C][C]2.4181[/C][C]0.008881[/C][/ROW]
[ROW][C]6[/C][C]0.26626[/C][C]2.4403[/C][C]0.008388[/C][/ROW]
[ROW][C]7[/C][C]0.176471[/C][C]1.6174[/C][C]0.054773[/C][/ROW]
[ROW][C]8[/C][C]0.212973[/C][C]1.9519[/C][C]0.027139[/C][/ROW]
[ROW][C]9[/C][C]0.413432[/C][C]3.7892[/C][C]0.000142[/C][/ROW]
[ROW][C]10[/C][C]0.297939[/C][C]2.7307[/C][C]0.00385[/C][/ROW]
[ROW][C]11[/C][C]0.333329[/C][C]3.055[/C][C]0.001508[/C][/ROW]
[ROW][C]12[/C][C]0.620188[/C][C]5.6841[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.256249[/C][C]2.3486[/C][C]0.010597[/C][/ROW]
[ROW][C]14[/C][C]0.3374[/C][C]3.0923[/C][C]0.001348[/C][/ROW]
[ROW][C]15[/C][C]0.288417[/C][C]2.6434[/C][C]0.004896[/C][/ROW]
[ROW][C]16[/C][C]0.052338[/C][C]0.4797[/C][C]0.316348[/C][/ROW]
[ROW][C]17[/C][C]0.106948[/C][C]0.9802[/C][C]0.164903[/C][/ROW]
[ROW][C]18[/C][C]0.028389[/C][C]0.2602[/C][C]0.397677[/C][/ROW]
[ROW][C]19[/C][C]0.060417[/C][C]0.5537[/C][C]0.290618[/C][/ROW]
[ROW][C]20[/C][C]0.090249[/C][C]0.8271[/C][C]0.205249[/C][/ROW]
[ROW][C]21[/C][C]0.176461[/C][C]1.6173[/C][C]0.054782[/C][/ROW]
[ROW][C]22[/C][C]0.172142[/C][C]1.5777[/C][C]0.059196[/C][/ROW]
[ROW][C]23[/C][C]0.143751[/C][C]1.3175[/C][C]0.095627[/C][/ROW]
[ROW][C]24[/C][C]0.330985[/C][C]3.0335[/C][C]0.001608[/C][/ROW]
[ROW][C]25[/C][C]0.109415[/C][C]1.0028[/C][C]0.159417[/C][/ROW]
[ROW][C]26[/C][C]0.105734[/C][C]0.9691[/C][C]0.167647[/C][/ROW]
[ROW][C]27[/C][C]0.042439[/C][C]0.389[/C][C]0.349146[/C][/ROW]
[ROW][C]28[/C][C]-0.064523[/C][C]-0.5914[/C][C]0.277933[/C][/ROW]
[ROW][C]29[/C][C]-0.098744[/C][C]-0.905[/C][C]0.184027[/C][/ROW]
[ROW][C]30[/C][C]-0.123872[/C][C]-1.1353[/C][C]0.129738[/C][/ROW]
[ROW][C]31[/C][C]-0.084888[/C][C]-0.778[/C][C]0.219373[/C][/ROW]
[ROW][C]32[/C][C]-0.108336[/C][C]-0.9929[/C][C]0.161801[/C][/ROW]
[ROW][C]33[/C][C]0.015912[/C][C]0.1458[/C][C]0.442202[/C][/ROW]
[ROW][C]34[/C][C]0.032381[/C][C]0.2968[/C][C]0.383684[/C][/ROW]
[ROW][C]35[/C][C]-0.033717[/C][C]-0.309[/C][C]0.379034[/C][/ROW]
[ROW][C]36[/C][C]0.127596[/C][C]1.1694[/C][C]0.122769[/C][/ROW]
[ROW][C]37[/C][C]0.013311[/C][C]0.122[/C][C]0.451597[/C][/ROW]
[ROW][C]38[/C][C]-0.076429[/C][C]-0.7005[/C][C]0.242781[/C][/ROW]
[ROW][C]39[/C][C]-0.09069[/C][C]-0.8312[/C][C]0.204112[/C][/ROW]
[ROW][C]40[/C][C]-0.14902[/C][C]-1.3658[/C][C]0.087826[/C][/ROW]
[ROW][C]41[/C][C]-0.221564[/C][C]-2.0307[/C][C]0.022726[/C][/ROW]
[ROW][C]42[/C][C]-0.183186[/C][C]-1.6789[/C][C]0.048442[/C][/ROW]
[ROW][C]43[/C][C]-0.17554[/C][C]-1.6089[/C][C]0.0557[/C][/ROW]
[ROW][C]44[/C][C]-0.244334[/C][C]-2.2394[/C][C]0.013887[/C][/ROW]
[ROW][C]45[/C][C]-0.097518[/C][C]-0.8938[/C][C]0.187[/C][/ROW]
[ROW][C]46[/C][C]-0.076913[/C][C]-0.7049[/C][C]0.241405[/C][/ROW]
[ROW][C]47[/C][C]-0.160131[/C][C]-1.4676[/C][C]0.07297[/C][/ROW]
[ROW][C]48[/C][C]-0.006493[/C][C]-0.0595[/C][C]0.476345[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193315&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193315&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
10.4494344.11914.4e-05
20.4630574.2442.8e-05
30.5023854.60447e-06
40.217751.99570.024603
50.2638422.41810.008881
60.266262.44030.008388
70.1764711.61740.054773
80.2129731.95190.027139
90.4134323.78920.000142
100.2979392.73070.00385
110.3333293.0550.001508
120.6201885.68410
130.2562492.34860.010597
140.33743.09230.001348
150.2884172.64340.004896
160.0523380.47970.316348
170.1069480.98020.164903
180.0283890.26020.397677
190.0604170.55370.290618
200.0902490.82710.205249
210.1764611.61730.054782
220.1721421.57770.059196
230.1437511.31750.095627
240.3309853.03350.001608
250.1094151.00280.159417
260.1057340.96910.167647
270.0424390.3890.349146
28-0.064523-0.59140.277933
29-0.098744-0.9050.184027
30-0.123872-1.13530.129738
31-0.084888-0.7780.219373
32-0.108336-0.99290.161801
330.0159120.14580.442202
340.0323810.29680.383684
35-0.033717-0.3090.379034
360.1275961.16940.122769
370.0133110.1220.451597
38-0.076429-0.70050.242781
39-0.09069-0.83120.204112
40-0.14902-1.36580.087826
41-0.221564-2.03070.022726
42-0.183186-1.67890.048442
43-0.17554-1.60890.0557
44-0.244334-2.23940.013887
45-0.097518-0.89380.187
46-0.076913-0.70490.241405
47-0.160131-1.46760.07297
48-0.006493-0.05950.476345







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4494344.11914.4e-05
20.3271472.99830.001785
30.3021672.76940.003455
4-0.199973-1.83280.035189
5-0.007508-0.06880.472653
60.0910170.83420.203271
70.0716880.6570.256479
80.0228880.20980.417177
90.3599233.29880.000713
100.0697320.63910.262247
11-0.01213-0.11120.455874
120.4110633.76750.000153
13-0.214838-1.9690.026123
14-0.103491-0.94850.172794
15-0.16752-1.53530.064228
16-0.063154-0.57880.282131
17-0.123733-1.1340.130005
18-0.156639-1.43560.077412
190.2248942.06120.021189
200.0346320.31740.375862
21-0.116124-1.06430.145122
220.1041560.95460.171258
23-0.095215-0.87270.192669
240.0212840.19510.422904
25-0.038372-0.35170.362978
26-0.104627-0.95890.170176
27-0.076388-0.70010.242897
280.0346860.31790.375673
29-0.073657-0.67510.25074
300.0766380.70240.242186
31-0.086749-0.79510.214407
320.0052620.04820.480825
330.0092210.08450.466426
34-0.037272-0.34160.366753
350.0184140.16880.433192
36-0.029334-0.26890.39435
370.1363351.24950.10747
38-0.089403-0.81940.207442
39-0.127524-1.16880.122901
400.120081.10060.137117
41-0.007874-0.07220.471321
42-0.0372-0.34090.366999
43-0.04003-0.36690.357316
44-0.118114-1.08250.141057
45-0.029965-0.27460.392136
460.0168580.15450.438791
47-0.015101-0.13840.445125
480.0320580.29380.38481

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.449434 & 4.1191 & 4.4e-05 \tabularnewline
2 & 0.327147 & 2.9983 & 0.001785 \tabularnewline
3 & 0.302167 & 2.7694 & 0.003455 \tabularnewline
4 & -0.199973 & -1.8328 & 0.035189 \tabularnewline
5 & -0.007508 & -0.0688 & 0.472653 \tabularnewline
6 & 0.091017 & 0.8342 & 0.203271 \tabularnewline
7 & 0.071688 & 0.657 & 0.256479 \tabularnewline
8 & 0.022888 & 0.2098 & 0.417177 \tabularnewline
9 & 0.359923 & 3.2988 & 0.000713 \tabularnewline
10 & 0.069732 & 0.6391 & 0.262247 \tabularnewline
11 & -0.01213 & -0.1112 & 0.455874 \tabularnewline
12 & 0.411063 & 3.7675 & 0.000153 \tabularnewline
13 & -0.214838 & -1.969 & 0.026123 \tabularnewline
14 & -0.103491 & -0.9485 & 0.172794 \tabularnewline
15 & -0.16752 & -1.5353 & 0.064228 \tabularnewline
16 & -0.063154 & -0.5788 & 0.282131 \tabularnewline
17 & -0.123733 & -1.134 & 0.130005 \tabularnewline
18 & -0.156639 & -1.4356 & 0.077412 \tabularnewline
19 & 0.224894 & 2.0612 & 0.021189 \tabularnewline
20 & 0.034632 & 0.3174 & 0.375862 \tabularnewline
21 & -0.116124 & -1.0643 & 0.145122 \tabularnewline
22 & 0.104156 & 0.9546 & 0.171258 \tabularnewline
23 & -0.095215 & -0.8727 & 0.192669 \tabularnewline
24 & 0.021284 & 0.1951 & 0.422904 \tabularnewline
25 & -0.038372 & -0.3517 & 0.362978 \tabularnewline
26 & -0.104627 & -0.9589 & 0.170176 \tabularnewline
27 & -0.076388 & -0.7001 & 0.242897 \tabularnewline
28 & 0.034686 & 0.3179 & 0.375673 \tabularnewline
29 & -0.073657 & -0.6751 & 0.25074 \tabularnewline
30 & 0.076638 & 0.7024 & 0.242186 \tabularnewline
31 & -0.086749 & -0.7951 & 0.214407 \tabularnewline
32 & 0.005262 & 0.0482 & 0.480825 \tabularnewline
33 & 0.009221 & 0.0845 & 0.466426 \tabularnewline
34 & -0.037272 & -0.3416 & 0.366753 \tabularnewline
35 & 0.018414 & 0.1688 & 0.433192 \tabularnewline
36 & -0.029334 & -0.2689 & 0.39435 \tabularnewline
37 & 0.136335 & 1.2495 & 0.10747 \tabularnewline
38 & -0.089403 & -0.8194 & 0.207442 \tabularnewline
39 & -0.127524 & -1.1688 & 0.122901 \tabularnewline
40 & 0.12008 & 1.1006 & 0.137117 \tabularnewline
41 & -0.007874 & -0.0722 & 0.471321 \tabularnewline
42 & -0.0372 & -0.3409 & 0.366999 \tabularnewline
43 & -0.04003 & -0.3669 & 0.357316 \tabularnewline
44 & -0.118114 & -1.0825 & 0.141057 \tabularnewline
45 & -0.029965 & -0.2746 & 0.392136 \tabularnewline
46 & 0.016858 & 0.1545 & 0.438791 \tabularnewline
47 & -0.015101 & -0.1384 & 0.445125 \tabularnewline
48 & 0.032058 & 0.2938 & 0.38481 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193315&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]0.449434[/C][C]4.1191[/C][C]4.4e-05[/C][/ROW]
[ROW][C]2[/C][C]0.327147[/C][C]2.9983[/C][C]0.001785[/C][/ROW]
[ROW][C]3[/C][C]0.302167[/C][C]2.7694[/C][C]0.003455[/C][/ROW]
[ROW][C]4[/C][C]-0.199973[/C][C]-1.8328[/C][C]0.035189[/C][/ROW]
[ROW][C]5[/C][C]-0.007508[/C][C]-0.0688[/C][C]0.472653[/C][/ROW]
[ROW][C]6[/C][C]0.091017[/C][C]0.8342[/C][C]0.203271[/C][/ROW]
[ROW][C]7[/C][C]0.071688[/C][C]0.657[/C][C]0.256479[/C][/ROW]
[ROW][C]8[/C][C]0.022888[/C][C]0.2098[/C][C]0.417177[/C][/ROW]
[ROW][C]9[/C][C]0.359923[/C][C]3.2988[/C][C]0.000713[/C][/ROW]
[ROW][C]10[/C][C]0.069732[/C][C]0.6391[/C][C]0.262247[/C][/ROW]
[ROW][C]11[/C][C]-0.01213[/C][C]-0.1112[/C][C]0.455874[/C][/ROW]
[ROW][C]12[/C][C]0.411063[/C][C]3.7675[/C][C]0.000153[/C][/ROW]
[ROW][C]13[/C][C]-0.214838[/C][C]-1.969[/C][C]0.026123[/C][/ROW]
[ROW][C]14[/C][C]-0.103491[/C][C]-0.9485[/C][C]0.172794[/C][/ROW]
[ROW][C]15[/C][C]-0.16752[/C][C]-1.5353[/C][C]0.064228[/C][/ROW]
[ROW][C]16[/C][C]-0.063154[/C][C]-0.5788[/C][C]0.282131[/C][/ROW]
[ROW][C]17[/C][C]-0.123733[/C][C]-1.134[/C][C]0.130005[/C][/ROW]
[ROW][C]18[/C][C]-0.156639[/C][C]-1.4356[/C][C]0.077412[/C][/ROW]
[ROW][C]19[/C][C]0.224894[/C][C]2.0612[/C][C]0.021189[/C][/ROW]
[ROW][C]20[/C][C]0.034632[/C][C]0.3174[/C][C]0.375862[/C][/ROW]
[ROW][C]21[/C][C]-0.116124[/C][C]-1.0643[/C][C]0.145122[/C][/ROW]
[ROW][C]22[/C][C]0.104156[/C][C]0.9546[/C][C]0.171258[/C][/ROW]
[ROW][C]23[/C][C]-0.095215[/C][C]-0.8727[/C][C]0.192669[/C][/ROW]
[ROW][C]24[/C][C]0.021284[/C][C]0.1951[/C][C]0.422904[/C][/ROW]
[ROW][C]25[/C][C]-0.038372[/C][C]-0.3517[/C][C]0.362978[/C][/ROW]
[ROW][C]26[/C][C]-0.104627[/C][C]-0.9589[/C][C]0.170176[/C][/ROW]
[ROW][C]27[/C][C]-0.076388[/C][C]-0.7001[/C][C]0.242897[/C][/ROW]
[ROW][C]28[/C][C]0.034686[/C][C]0.3179[/C][C]0.375673[/C][/ROW]
[ROW][C]29[/C][C]-0.073657[/C][C]-0.6751[/C][C]0.25074[/C][/ROW]
[ROW][C]30[/C][C]0.076638[/C][C]0.7024[/C][C]0.242186[/C][/ROW]
[ROW][C]31[/C][C]-0.086749[/C][C]-0.7951[/C][C]0.214407[/C][/ROW]
[ROW][C]32[/C][C]0.005262[/C][C]0.0482[/C][C]0.480825[/C][/ROW]
[ROW][C]33[/C][C]0.009221[/C][C]0.0845[/C][C]0.466426[/C][/ROW]
[ROW][C]34[/C][C]-0.037272[/C][C]-0.3416[/C][C]0.366753[/C][/ROW]
[ROW][C]35[/C][C]0.018414[/C][C]0.1688[/C][C]0.433192[/C][/ROW]
[ROW][C]36[/C][C]-0.029334[/C][C]-0.2689[/C][C]0.39435[/C][/ROW]
[ROW][C]37[/C][C]0.136335[/C][C]1.2495[/C][C]0.10747[/C][/ROW]
[ROW][C]38[/C][C]-0.089403[/C][C]-0.8194[/C][C]0.207442[/C][/ROW]
[ROW][C]39[/C][C]-0.127524[/C][C]-1.1688[/C][C]0.122901[/C][/ROW]
[ROW][C]40[/C][C]0.12008[/C][C]1.1006[/C][C]0.137117[/C][/ROW]
[ROW][C]41[/C][C]-0.007874[/C][C]-0.0722[/C][C]0.471321[/C][/ROW]
[ROW][C]42[/C][C]-0.0372[/C][C]-0.3409[/C][C]0.366999[/C][/ROW]
[ROW][C]43[/C][C]-0.04003[/C][C]-0.3669[/C][C]0.357316[/C][/ROW]
[ROW][C]44[/C][C]-0.118114[/C][C]-1.0825[/C][C]0.141057[/C][/ROW]
[ROW][C]45[/C][C]-0.029965[/C][C]-0.2746[/C][C]0.392136[/C][/ROW]
[ROW][C]46[/C][C]0.016858[/C][C]0.1545[/C][C]0.438791[/C][/ROW]
[ROW][C]47[/C][C]-0.015101[/C][C]-0.1384[/C][C]0.445125[/C][/ROW]
[ROW][C]48[/C][C]0.032058[/C][C]0.2938[/C][C]0.38481[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193315&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193315&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
10.4494344.11914.4e-05
20.3271472.99830.001785
30.3021672.76940.003455
4-0.199973-1.83280.035189
5-0.007508-0.06880.472653
60.0910170.83420.203271
70.0716880.6570.256479
80.0228880.20980.417177
90.3599233.29880.000713
100.0697320.63910.262247
11-0.01213-0.11120.455874
120.4110633.76750.000153
13-0.214838-1.9690.026123
14-0.103491-0.94850.172794
15-0.16752-1.53530.064228
16-0.063154-0.57880.282131
17-0.123733-1.1340.130005
18-0.156639-1.43560.077412
190.2248942.06120.021189
200.0346320.31740.375862
21-0.116124-1.06430.145122
220.1041560.95460.171258
23-0.095215-0.87270.192669
240.0212840.19510.422904
25-0.038372-0.35170.362978
26-0.104627-0.95890.170176
27-0.076388-0.70010.242897
280.0346860.31790.375673
29-0.073657-0.67510.25074
300.0766380.70240.242186
31-0.086749-0.79510.214407
320.0052620.04820.480825
330.0092210.08450.466426
34-0.037272-0.34160.366753
350.0184140.16880.433192
36-0.029334-0.26890.39435
370.1363351.24950.10747
38-0.089403-0.81940.207442
39-0.127524-1.16880.122901
400.120081.10060.137117
41-0.007874-0.07220.471321
42-0.0372-0.34090.366999
43-0.04003-0.36690.357316
44-0.118114-1.08250.141057
45-0.029965-0.27460.392136
460.0168580.15450.438791
47-0.015101-0.13840.445125
480.0320580.29380.38481



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 (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')