Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 16 Dec 2008 05:06:05 -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/16/t1229429196r6kpzd5xiebxskl.htm/, Retrieved Wed, 15 May 2024 16:32:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33931, Retrieved Wed, 15 May 2024 16:32:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact212
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2008-12-16 12:06:05] [a5ed2c45dea395ef181ba16fe56905d7] [Current]
Feedback Forum

Post a new message
Dataseries X:
111.7
98.6
96.9
95.1
97.0
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99.0
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102.0
106.0
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100.0
110.7
112.8
109.8
117.3
109.1
115.9
96.0
99.8
117.0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33931&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33931&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33931&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.176962-1.2260.113084
20.1834371.27090.104947
30.2828031.95930.027949
4-0.034666-0.24020.405609
50.1428690.98980.163611
60.2086251.44540.077422
7-0.064376-0.4460.328798
8-0.041808-0.28970.386664
90.1484771.02870.154393
10-0.162584-1.12640.132794
11-0.021231-0.14710.441839
12-0.073183-0.5070.307228
13-0.099123-0.68670.247775
14-0.136574-0.94620.17439
150.0362550.25120.401373
16-0.153032-1.06020.147171
17-0.059004-0.40880.342256
18-0.021916-0.15180.439976
19-0.22661-1.570.061492
20-0.010826-0.0750.470262
21-0.025663-0.17780.429815
22-0.255287-1.76870.041651
230.2017591.39780.084296
24-0.261703-1.81310.038033
25-0.025154-0.17430.431191
260.1117280.77410.221342
27-0.109888-0.76130.225093
28-0.045797-0.31730.376199
290.010820.0750.470277
30-0.057962-0.40160.344892
31-0.034809-0.24120.405227
320.1515621.05010.149475
33-0.091423-0.63340.264741
340.0629990.43650.332226
350.0112170.07770.469188
360.0414910.28750.387498
37-0.010828-0.0750.470257
380.0412770.2860.388064
390.004690.03250.487107
40-0.015894-0.11010.456387
410.122810.85090.199537
42-0.052788-0.36570.358087
430.009980.06910.472581
44-0.006345-0.0440.48256
45-0.018741-0.12980.448617
460.0294420.2040.419616
47-0.008066-0.05590.477834
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.176962 & -1.226 & 0.113084 \tabularnewline
2 & 0.183437 & 1.2709 & 0.104947 \tabularnewline
3 & 0.282803 & 1.9593 & 0.027949 \tabularnewline
4 & -0.034666 & -0.2402 & 0.405609 \tabularnewline
5 & 0.142869 & 0.9898 & 0.163611 \tabularnewline
6 & 0.208625 & 1.4454 & 0.077422 \tabularnewline
7 & -0.064376 & -0.446 & 0.328798 \tabularnewline
8 & -0.041808 & -0.2897 & 0.386664 \tabularnewline
9 & 0.148477 & 1.0287 & 0.154393 \tabularnewline
10 & -0.162584 & -1.1264 & 0.132794 \tabularnewline
11 & -0.021231 & -0.1471 & 0.441839 \tabularnewline
12 & -0.073183 & -0.507 & 0.307228 \tabularnewline
13 & -0.099123 & -0.6867 & 0.247775 \tabularnewline
14 & -0.136574 & -0.9462 & 0.17439 \tabularnewline
15 & 0.036255 & 0.2512 & 0.401373 \tabularnewline
16 & -0.153032 & -1.0602 & 0.147171 \tabularnewline
17 & -0.059004 & -0.4088 & 0.342256 \tabularnewline
18 & -0.021916 & -0.1518 & 0.439976 \tabularnewline
19 & -0.22661 & -1.57 & 0.061492 \tabularnewline
20 & -0.010826 & -0.075 & 0.470262 \tabularnewline
21 & -0.025663 & -0.1778 & 0.429815 \tabularnewline
22 & -0.255287 & -1.7687 & 0.041651 \tabularnewline
23 & 0.201759 & 1.3978 & 0.084296 \tabularnewline
24 & -0.261703 & -1.8131 & 0.038033 \tabularnewline
25 & -0.025154 & -0.1743 & 0.431191 \tabularnewline
26 & 0.111728 & 0.7741 & 0.221342 \tabularnewline
27 & -0.109888 & -0.7613 & 0.225093 \tabularnewline
28 & -0.045797 & -0.3173 & 0.376199 \tabularnewline
29 & 0.01082 & 0.075 & 0.470277 \tabularnewline
30 & -0.057962 & -0.4016 & 0.344892 \tabularnewline
31 & -0.034809 & -0.2412 & 0.405227 \tabularnewline
32 & 0.151562 & 1.0501 & 0.149475 \tabularnewline
33 & -0.091423 & -0.6334 & 0.264741 \tabularnewline
34 & 0.062999 & 0.4365 & 0.332226 \tabularnewline
35 & 0.011217 & 0.0777 & 0.469188 \tabularnewline
36 & 0.041491 & 0.2875 & 0.387498 \tabularnewline
37 & -0.010828 & -0.075 & 0.470257 \tabularnewline
38 & 0.041277 & 0.286 & 0.388064 \tabularnewline
39 & 0.00469 & 0.0325 & 0.487107 \tabularnewline
40 & -0.015894 & -0.1101 & 0.456387 \tabularnewline
41 & 0.12281 & 0.8509 & 0.199537 \tabularnewline
42 & -0.052788 & -0.3657 & 0.358087 \tabularnewline
43 & 0.00998 & 0.0691 & 0.472581 \tabularnewline
44 & -0.006345 & -0.044 & 0.48256 \tabularnewline
45 & -0.018741 & -0.1298 & 0.448617 \tabularnewline
46 & 0.029442 & 0.204 & 0.419616 \tabularnewline
47 & -0.008066 & -0.0559 & 0.477834 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33931&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]-0.176962[/C][C]-1.226[/C][C]0.113084[/C][/ROW]
[ROW][C]2[/C][C]0.183437[/C][C]1.2709[/C][C]0.104947[/C][/ROW]
[ROW][C]3[/C][C]0.282803[/C][C]1.9593[/C][C]0.027949[/C][/ROW]
[ROW][C]4[/C][C]-0.034666[/C][C]-0.2402[/C][C]0.405609[/C][/ROW]
[ROW][C]5[/C][C]0.142869[/C][C]0.9898[/C][C]0.163611[/C][/ROW]
[ROW][C]6[/C][C]0.208625[/C][C]1.4454[/C][C]0.077422[/C][/ROW]
[ROW][C]7[/C][C]-0.064376[/C][C]-0.446[/C][C]0.328798[/C][/ROW]
[ROW][C]8[/C][C]-0.041808[/C][C]-0.2897[/C][C]0.386664[/C][/ROW]
[ROW][C]9[/C][C]0.148477[/C][C]1.0287[/C][C]0.154393[/C][/ROW]
[ROW][C]10[/C][C]-0.162584[/C][C]-1.1264[/C][C]0.132794[/C][/ROW]
[ROW][C]11[/C][C]-0.021231[/C][C]-0.1471[/C][C]0.441839[/C][/ROW]
[ROW][C]12[/C][C]-0.073183[/C][C]-0.507[/C][C]0.307228[/C][/ROW]
[ROW][C]13[/C][C]-0.099123[/C][C]-0.6867[/C][C]0.247775[/C][/ROW]
[ROW][C]14[/C][C]-0.136574[/C][C]-0.9462[/C][C]0.17439[/C][/ROW]
[ROW][C]15[/C][C]0.036255[/C][C]0.2512[/C][C]0.401373[/C][/ROW]
[ROW][C]16[/C][C]-0.153032[/C][C]-1.0602[/C][C]0.147171[/C][/ROW]
[ROW][C]17[/C][C]-0.059004[/C][C]-0.4088[/C][C]0.342256[/C][/ROW]
[ROW][C]18[/C][C]-0.021916[/C][C]-0.1518[/C][C]0.439976[/C][/ROW]
[ROW][C]19[/C][C]-0.22661[/C][C]-1.57[/C][C]0.061492[/C][/ROW]
[ROW][C]20[/C][C]-0.010826[/C][C]-0.075[/C][C]0.470262[/C][/ROW]
[ROW][C]21[/C][C]-0.025663[/C][C]-0.1778[/C][C]0.429815[/C][/ROW]
[ROW][C]22[/C][C]-0.255287[/C][C]-1.7687[/C][C]0.041651[/C][/ROW]
[ROW][C]23[/C][C]0.201759[/C][C]1.3978[/C][C]0.084296[/C][/ROW]
[ROW][C]24[/C][C]-0.261703[/C][C]-1.8131[/C][C]0.038033[/C][/ROW]
[ROW][C]25[/C][C]-0.025154[/C][C]-0.1743[/C][C]0.431191[/C][/ROW]
[ROW][C]26[/C][C]0.111728[/C][C]0.7741[/C][C]0.221342[/C][/ROW]
[ROW][C]27[/C][C]-0.109888[/C][C]-0.7613[/C][C]0.225093[/C][/ROW]
[ROW][C]28[/C][C]-0.045797[/C][C]-0.3173[/C][C]0.376199[/C][/ROW]
[ROW][C]29[/C][C]0.01082[/C][C]0.075[/C][C]0.470277[/C][/ROW]
[ROW][C]30[/C][C]-0.057962[/C][C]-0.4016[/C][C]0.344892[/C][/ROW]
[ROW][C]31[/C][C]-0.034809[/C][C]-0.2412[/C][C]0.405227[/C][/ROW]
[ROW][C]32[/C][C]0.151562[/C][C]1.0501[/C][C]0.149475[/C][/ROW]
[ROW][C]33[/C][C]-0.091423[/C][C]-0.6334[/C][C]0.264741[/C][/ROW]
[ROW][C]34[/C][C]0.062999[/C][C]0.4365[/C][C]0.332226[/C][/ROW]
[ROW][C]35[/C][C]0.011217[/C][C]0.0777[/C][C]0.469188[/C][/ROW]
[ROW][C]36[/C][C]0.041491[/C][C]0.2875[/C][C]0.387498[/C][/ROW]
[ROW][C]37[/C][C]-0.010828[/C][C]-0.075[/C][C]0.470257[/C][/ROW]
[ROW][C]38[/C][C]0.041277[/C][C]0.286[/C][C]0.388064[/C][/ROW]
[ROW][C]39[/C][C]0.00469[/C][C]0.0325[/C][C]0.487107[/C][/ROW]
[ROW][C]40[/C][C]-0.015894[/C][C]-0.1101[/C][C]0.456387[/C][/ROW]
[ROW][C]41[/C][C]0.12281[/C][C]0.8509[/C][C]0.199537[/C][/ROW]
[ROW][C]42[/C][C]-0.052788[/C][C]-0.3657[/C][C]0.358087[/C][/ROW]
[ROW][C]43[/C][C]0.00998[/C][C]0.0691[/C][C]0.472581[/C][/ROW]
[ROW][C]44[/C][C]-0.006345[/C][C]-0.044[/C][C]0.48256[/C][/ROW]
[ROW][C]45[/C][C]-0.018741[/C][C]-0.1298[/C][C]0.448617[/C][/ROW]
[ROW][C]46[/C][C]0.029442[/C][C]0.204[/C][C]0.419616[/C][/ROW]
[ROW][C]47[/C][C]-0.008066[/C][C]-0.0559[/C][C]0.477834[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33931&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33931&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.176962-1.2260.113084
20.1834371.27090.104947
30.2828031.95930.027949
4-0.034666-0.24020.405609
50.1428690.98980.163611
60.2086251.44540.077422
7-0.064376-0.4460.328798
8-0.041808-0.28970.386664
90.1484771.02870.154393
10-0.162584-1.12640.132794
11-0.021231-0.14710.441839
12-0.073183-0.5070.307228
13-0.099123-0.68670.247775
14-0.136574-0.94620.17439
150.0362550.25120.401373
16-0.153032-1.06020.147171
17-0.059004-0.40880.342256
18-0.021916-0.15180.439976
19-0.22661-1.570.061492
20-0.010826-0.0750.470262
21-0.025663-0.17780.429815
22-0.255287-1.76870.041651
230.2017591.39780.084296
24-0.261703-1.81310.038033
25-0.025154-0.17430.431191
260.1117280.77410.221342
27-0.109888-0.76130.225093
28-0.045797-0.31730.376199
290.010820.0750.470277
30-0.057962-0.40160.344892
31-0.034809-0.24120.405227
320.1515621.05010.149475
33-0.091423-0.63340.264741
340.0629990.43650.332226
350.0112170.07770.469188
360.0414910.28750.387498
37-0.010828-0.0750.470257
380.0412770.2860.388064
390.004690.03250.487107
40-0.015894-0.11010.456387
410.122810.85090.199537
42-0.052788-0.36570.358087
430.009980.06910.472581
44-0.006345-0.0440.48256
45-0.018741-0.12980.448617
460.0294420.2040.419616
47-0.008066-0.05590.477834
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.176962-1.2260.113084
20.1570391.0880.141014
30.3577032.47820.008386
40.0583940.40460.343797
50.0262060.18160.428346
60.1675171.16060.125774
7-0.027875-0.19310.42384
8-0.238452-1.6520.052527
9-0.001842-0.01280.494937
10-0.073541-0.50950.306367
11-0.109288-0.75720.226325
12-0.16742-1.15990.125909
130.0013180.00910.496375
14-0.073256-0.50750.307054
150.0604470.41880.338618
160.0143370.09930.460646
170.0464950.32210.374379
189.7e-057e-040.499734
19-0.177693-1.23110.112143
20-0.094311-0.65340.258307
210.0272670.18890.425478
22-0.231536-1.60410.057623
230.1836891.27260.104639
24-0.157283-1.08970.140646
250.0039610.02740.489109
260.0914790.63380.264614
270.0912580.63230.265111
28-0.089466-0.61980.269148
29-0.146917-1.01790.156921
30-0.063886-0.44260.330017
31-0.035606-0.24670.403101
32-0.028925-0.20040.421009
330.0345670.23950.405873
340.0738130.51140.30571
350.0025290.01750.493046
36-0.026661-0.18470.427116
370.0510640.35380.362526
38-0.138767-0.96140.170583
39-0.058567-0.40580.34336
40-0.067127-0.46510.321992
410.0119880.08310.467077
42-0.019954-0.13820.445313
43-0.079493-0.55070.292181
44-0.047564-0.32950.371594
450.1222210.84680.200662
46-0.039274-0.27210.393356
470.0479980.33250.370466
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.176962 & -1.226 & 0.113084 \tabularnewline
2 & 0.157039 & 1.088 & 0.141014 \tabularnewline
3 & 0.357703 & 2.4782 & 0.008386 \tabularnewline
4 & 0.058394 & 0.4046 & 0.343797 \tabularnewline
5 & 0.026206 & 0.1816 & 0.428346 \tabularnewline
6 & 0.167517 & 1.1606 & 0.125774 \tabularnewline
7 & -0.027875 & -0.1931 & 0.42384 \tabularnewline
8 & -0.238452 & -1.652 & 0.052527 \tabularnewline
9 & -0.001842 & -0.0128 & 0.494937 \tabularnewline
10 & -0.073541 & -0.5095 & 0.306367 \tabularnewline
11 & -0.109288 & -0.7572 & 0.226325 \tabularnewline
12 & -0.16742 & -1.1599 & 0.125909 \tabularnewline
13 & 0.001318 & 0.0091 & 0.496375 \tabularnewline
14 & -0.073256 & -0.5075 & 0.307054 \tabularnewline
15 & 0.060447 & 0.4188 & 0.338618 \tabularnewline
16 & 0.014337 & 0.0993 & 0.460646 \tabularnewline
17 & 0.046495 & 0.3221 & 0.374379 \tabularnewline
18 & 9.7e-05 & 7e-04 & 0.499734 \tabularnewline
19 & -0.177693 & -1.2311 & 0.112143 \tabularnewline
20 & -0.094311 & -0.6534 & 0.258307 \tabularnewline
21 & 0.027267 & 0.1889 & 0.425478 \tabularnewline
22 & -0.231536 & -1.6041 & 0.057623 \tabularnewline
23 & 0.183689 & 1.2726 & 0.104639 \tabularnewline
24 & -0.157283 & -1.0897 & 0.140646 \tabularnewline
25 & 0.003961 & 0.0274 & 0.489109 \tabularnewline
26 & 0.091479 & 0.6338 & 0.264614 \tabularnewline
27 & 0.091258 & 0.6323 & 0.265111 \tabularnewline
28 & -0.089466 & -0.6198 & 0.269148 \tabularnewline
29 & -0.146917 & -1.0179 & 0.156921 \tabularnewline
30 & -0.063886 & -0.4426 & 0.330017 \tabularnewline
31 & -0.035606 & -0.2467 & 0.403101 \tabularnewline
32 & -0.028925 & -0.2004 & 0.421009 \tabularnewline
33 & 0.034567 & 0.2395 & 0.405873 \tabularnewline
34 & 0.073813 & 0.5114 & 0.30571 \tabularnewline
35 & 0.002529 & 0.0175 & 0.493046 \tabularnewline
36 & -0.026661 & -0.1847 & 0.427116 \tabularnewline
37 & 0.051064 & 0.3538 & 0.362526 \tabularnewline
38 & -0.138767 & -0.9614 & 0.170583 \tabularnewline
39 & -0.058567 & -0.4058 & 0.34336 \tabularnewline
40 & -0.067127 & -0.4651 & 0.321992 \tabularnewline
41 & 0.011988 & 0.0831 & 0.467077 \tabularnewline
42 & -0.019954 & -0.1382 & 0.445313 \tabularnewline
43 & -0.079493 & -0.5507 & 0.292181 \tabularnewline
44 & -0.047564 & -0.3295 & 0.371594 \tabularnewline
45 & 0.122221 & 0.8468 & 0.200662 \tabularnewline
46 & -0.039274 & -0.2721 & 0.393356 \tabularnewline
47 & 0.047998 & 0.3325 & 0.370466 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33931&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]-0.176962[/C][C]-1.226[/C][C]0.113084[/C][/ROW]
[ROW][C]2[/C][C]0.157039[/C][C]1.088[/C][C]0.141014[/C][/ROW]
[ROW][C]3[/C][C]0.357703[/C][C]2.4782[/C][C]0.008386[/C][/ROW]
[ROW][C]4[/C][C]0.058394[/C][C]0.4046[/C][C]0.343797[/C][/ROW]
[ROW][C]5[/C][C]0.026206[/C][C]0.1816[/C][C]0.428346[/C][/ROW]
[ROW][C]6[/C][C]0.167517[/C][C]1.1606[/C][C]0.125774[/C][/ROW]
[ROW][C]7[/C][C]-0.027875[/C][C]-0.1931[/C][C]0.42384[/C][/ROW]
[ROW][C]8[/C][C]-0.238452[/C][C]-1.652[/C][C]0.052527[/C][/ROW]
[ROW][C]9[/C][C]-0.001842[/C][C]-0.0128[/C][C]0.494937[/C][/ROW]
[ROW][C]10[/C][C]-0.073541[/C][C]-0.5095[/C][C]0.306367[/C][/ROW]
[ROW][C]11[/C][C]-0.109288[/C][C]-0.7572[/C][C]0.226325[/C][/ROW]
[ROW][C]12[/C][C]-0.16742[/C][C]-1.1599[/C][C]0.125909[/C][/ROW]
[ROW][C]13[/C][C]0.001318[/C][C]0.0091[/C][C]0.496375[/C][/ROW]
[ROW][C]14[/C][C]-0.073256[/C][C]-0.5075[/C][C]0.307054[/C][/ROW]
[ROW][C]15[/C][C]0.060447[/C][C]0.4188[/C][C]0.338618[/C][/ROW]
[ROW][C]16[/C][C]0.014337[/C][C]0.0993[/C][C]0.460646[/C][/ROW]
[ROW][C]17[/C][C]0.046495[/C][C]0.3221[/C][C]0.374379[/C][/ROW]
[ROW][C]18[/C][C]9.7e-05[/C][C]7e-04[/C][C]0.499734[/C][/ROW]
[ROW][C]19[/C][C]-0.177693[/C][C]-1.2311[/C][C]0.112143[/C][/ROW]
[ROW][C]20[/C][C]-0.094311[/C][C]-0.6534[/C][C]0.258307[/C][/ROW]
[ROW][C]21[/C][C]0.027267[/C][C]0.1889[/C][C]0.425478[/C][/ROW]
[ROW][C]22[/C][C]-0.231536[/C][C]-1.6041[/C][C]0.057623[/C][/ROW]
[ROW][C]23[/C][C]0.183689[/C][C]1.2726[/C][C]0.104639[/C][/ROW]
[ROW][C]24[/C][C]-0.157283[/C][C]-1.0897[/C][C]0.140646[/C][/ROW]
[ROW][C]25[/C][C]0.003961[/C][C]0.0274[/C][C]0.489109[/C][/ROW]
[ROW][C]26[/C][C]0.091479[/C][C]0.6338[/C][C]0.264614[/C][/ROW]
[ROW][C]27[/C][C]0.091258[/C][C]0.6323[/C][C]0.265111[/C][/ROW]
[ROW][C]28[/C][C]-0.089466[/C][C]-0.6198[/C][C]0.269148[/C][/ROW]
[ROW][C]29[/C][C]-0.146917[/C][C]-1.0179[/C][C]0.156921[/C][/ROW]
[ROW][C]30[/C][C]-0.063886[/C][C]-0.4426[/C][C]0.330017[/C][/ROW]
[ROW][C]31[/C][C]-0.035606[/C][C]-0.2467[/C][C]0.403101[/C][/ROW]
[ROW][C]32[/C][C]-0.028925[/C][C]-0.2004[/C][C]0.421009[/C][/ROW]
[ROW][C]33[/C][C]0.034567[/C][C]0.2395[/C][C]0.405873[/C][/ROW]
[ROW][C]34[/C][C]0.073813[/C][C]0.5114[/C][C]0.30571[/C][/ROW]
[ROW][C]35[/C][C]0.002529[/C][C]0.0175[/C][C]0.493046[/C][/ROW]
[ROW][C]36[/C][C]-0.026661[/C][C]-0.1847[/C][C]0.427116[/C][/ROW]
[ROW][C]37[/C][C]0.051064[/C][C]0.3538[/C][C]0.362526[/C][/ROW]
[ROW][C]38[/C][C]-0.138767[/C][C]-0.9614[/C][C]0.170583[/C][/ROW]
[ROW][C]39[/C][C]-0.058567[/C][C]-0.4058[/C][C]0.34336[/C][/ROW]
[ROW][C]40[/C][C]-0.067127[/C][C]-0.4651[/C][C]0.321992[/C][/ROW]
[ROW][C]41[/C][C]0.011988[/C][C]0.0831[/C][C]0.467077[/C][/ROW]
[ROW][C]42[/C][C]-0.019954[/C][C]-0.1382[/C][C]0.445313[/C][/ROW]
[ROW][C]43[/C][C]-0.079493[/C][C]-0.5507[/C][C]0.292181[/C][/ROW]
[ROW][C]44[/C][C]-0.047564[/C][C]-0.3295[/C][C]0.371594[/C][/ROW]
[ROW][C]45[/C][C]0.122221[/C][C]0.8468[/C][C]0.200662[/C][/ROW]
[ROW][C]46[/C][C]-0.039274[/C][C]-0.2721[/C][C]0.393356[/C][/ROW]
[ROW][C]47[/C][C]0.047998[/C][C]0.3325[/C][C]0.370466[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33931&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33931&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.176962-1.2260.113084
20.1570391.0880.141014
30.3577032.47820.008386
40.0583940.40460.343797
50.0262060.18160.428346
60.1675171.16060.125774
7-0.027875-0.19310.42384
8-0.238452-1.6520.052527
9-0.001842-0.01280.494937
10-0.073541-0.50950.306367
11-0.109288-0.75720.226325
12-0.16742-1.15990.125909
130.0013180.00910.496375
14-0.073256-0.50750.307054
150.0604470.41880.338618
160.0143370.09930.460646
170.0464950.32210.374379
189.7e-057e-040.499734
19-0.177693-1.23110.112143
20-0.094311-0.65340.258307
210.0272670.18890.425478
22-0.231536-1.60410.057623
230.1836891.27260.104639
24-0.157283-1.08970.140646
250.0039610.02740.489109
260.0914790.63380.264614
270.0912580.63230.265111
28-0.089466-0.61980.269148
29-0.146917-1.01790.156921
30-0.063886-0.44260.330017
31-0.035606-0.24670.403101
32-0.028925-0.20040.421009
330.0345670.23950.405873
340.0738130.51140.30571
350.0025290.01750.493046
36-0.026661-0.18470.427116
370.0510640.35380.362526
38-0.138767-0.96140.170583
39-0.058567-0.40580.34336
40-0.067127-0.46510.321992
410.0119880.08310.467077
42-0.019954-0.13820.445313
43-0.079493-0.55070.292181
44-0.047564-0.32950.371594
450.1222210.84680.200662
46-0.039274-0.27210.393356
470.0479980.33250.370466
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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')