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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 22 Dec 2013 12:50:39 -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/2013/Dec/22/t1387734702tzxz1c5t93e1dyw.htm/, Retrieved Sun, 05 Dec 2021 16:26:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232551, Retrieved Sun, 05 Dec 2021 16:26:56 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2013-12-22 17:50:39] [818da16b08b21220aa14002c9e16e6e1] [Current]
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Dataseries X:
85.73
85.73
85.74
86.32
87.59
87.81
87.87
87.94
87.96
88.01
88.01
88.01
88.01
88.01
88.59
89.43
89.63
89.73
89.88
89.89
89.9
89.91
89.86
90.07
90.17
90.17
90.28
90.87
92.05
92.1
92.16
92.22
92.25
92.29
92.29
92.29
92.29
92.29
91.95
91.82
92.16
92.31
92.33
92.4
92.54
92.49
92.54
92.58
92.58
92.39
92.33
93.59
95.51
95.99
96.22
97.2
98.54
99.64
100.23
100.17




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232551&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232551&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232551&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'Gertrude Mary Cox' @ cox.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9071837.0270
20.7992046.19060
30.6933055.37031e-06
40.6012384.65729e-06
50.5301514.10656.2e-05
60.467143.61840.000305
70.4041753.13070.001347
80.3472882.69010.004619
90.3153422.44260.008771
100.2994122.31920.011902
110.280812.17510.016786
120.2560661.98350.025948
130.2272891.76060.041704
140.1963931.52130.066725
150.1697591.31490.096766
160.1485461.15060.127225
170.1296831.00450.15958
180.1123220.870.193872
190.0968280.750.228085
200.0832950.64520.260627
210.0739020.57240.284579
220.0625990.48490.314759
230.0458420.35510.361883
240.0271190.21010.417165
250.0020290.01570.493756
26-0.027609-0.21390.415691
27-0.058444-0.45270.326196
28-0.086616-0.67090.252422
29-0.108854-0.84320.201238
30-0.134087-1.03860.151572
31-0.160399-1.24240.109453
32-0.186349-1.44350.077047
33-0.19715-1.52710.065994
34-0.200566-1.55360.062772
35-0.202621-1.56950.060896
36-0.204936-1.58740.058836
37-0.208731-1.61680.055582
38-0.214308-1.660.051064
39-0.226397-1.75370.042298
40-0.24109-1.86750.033361
41-0.25523-1.9770.026321
42-0.270946-2.09870.020028
43-0.287364-2.22590.014894
44-0.303828-2.35340.010947
45-0.317118-2.45640.008473
46-0.319695-2.47630.008056
47-0.314664-2.43740.008888
48-0.312454-2.42030.009277

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.907183 & 7.027 & 0 \tabularnewline
2 & 0.799204 & 6.1906 & 0 \tabularnewline
3 & 0.693305 & 5.3703 & 1e-06 \tabularnewline
4 & 0.601238 & 4.6572 & 9e-06 \tabularnewline
5 & 0.530151 & 4.1065 & 6.2e-05 \tabularnewline
6 & 0.46714 & 3.6184 & 0.000305 \tabularnewline
7 & 0.404175 & 3.1307 & 0.001347 \tabularnewline
8 & 0.347288 & 2.6901 & 0.004619 \tabularnewline
9 & 0.315342 & 2.4426 & 0.008771 \tabularnewline
10 & 0.299412 & 2.3192 & 0.011902 \tabularnewline
11 & 0.28081 & 2.1751 & 0.016786 \tabularnewline
12 & 0.256066 & 1.9835 & 0.025948 \tabularnewline
13 & 0.227289 & 1.7606 & 0.041704 \tabularnewline
14 & 0.196393 & 1.5213 & 0.066725 \tabularnewline
15 & 0.169759 & 1.3149 & 0.096766 \tabularnewline
16 & 0.148546 & 1.1506 & 0.127225 \tabularnewline
17 & 0.129683 & 1.0045 & 0.15958 \tabularnewline
18 & 0.112322 & 0.87 & 0.193872 \tabularnewline
19 & 0.096828 & 0.75 & 0.228085 \tabularnewline
20 & 0.083295 & 0.6452 & 0.260627 \tabularnewline
21 & 0.073902 & 0.5724 & 0.284579 \tabularnewline
22 & 0.062599 & 0.4849 & 0.314759 \tabularnewline
23 & 0.045842 & 0.3551 & 0.361883 \tabularnewline
24 & 0.027119 & 0.2101 & 0.417165 \tabularnewline
25 & 0.002029 & 0.0157 & 0.493756 \tabularnewline
26 & -0.027609 & -0.2139 & 0.415691 \tabularnewline
27 & -0.058444 & -0.4527 & 0.326196 \tabularnewline
28 & -0.086616 & -0.6709 & 0.252422 \tabularnewline
29 & -0.108854 & -0.8432 & 0.201238 \tabularnewline
30 & -0.134087 & -1.0386 & 0.151572 \tabularnewline
31 & -0.160399 & -1.2424 & 0.109453 \tabularnewline
32 & -0.186349 & -1.4435 & 0.077047 \tabularnewline
33 & -0.19715 & -1.5271 & 0.065994 \tabularnewline
34 & -0.200566 & -1.5536 & 0.062772 \tabularnewline
35 & -0.202621 & -1.5695 & 0.060896 \tabularnewline
36 & -0.204936 & -1.5874 & 0.058836 \tabularnewline
37 & -0.208731 & -1.6168 & 0.055582 \tabularnewline
38 & -0.214308 & -1.66 & 0.051064 \tabularnewline
39 & -0.226397 & -1.7537 & 0.042298 \tabularnewline
40 & -0.24109 & -1.8675 & 0.033361 \tabularnewline
41 & -0.25523 & -1.977 & 0.026321 \tabularnewline
42 & -0.270946 & -2.0987 & 0.020028 \tabularnewline
43 & -0.287364 & -2.2259 & 0.014894 \tabularnewline
44 & -0.303828 & -2.3534 & 0.010947 \tabularnewline
45 & -0.317118 & -2.4564 & 0.008473 \tabularnewline
46 & -0.319695 & -2.4763 & 0.008056 \tabularnewline
47 & -0.314664 & -2.4374 & 0.008888 \tabularnewline
48 & -0.312454 & -2.4203 & 0.009277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232551&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]0.907183[/C][C]7.027[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.799204[/C][C]6.1906[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.693305[/C][C]5.3703[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.601238[/C][C]4.6572[/C][C]9e-06[/C][/ROW]
[ROW][C]5[/C][C]0.530151[/C][C]4.1065[/C][C]6.2e-05[/C][/ROW]
[ROW][C]6[/C][C]0.46714[/C][C]3.6184[/C][C]0.000305[/C][/ROW]
[ROW][C]7[/C][C]0.404175[/C][C]3.1307[/C][C]0.001347[/C][/ROW]
[ROW][C]8[/C][C]0.347288[/C][C]2.6901[/C][C]0.004619[/C][/ROW]
[ROW][C]9[/C][C]0.315342[/C][C]2.4426[/C][C]0.008771[/C][/ROW]
[ROW][C]10[/C][C]0.299412[/C][C]2.3192[/C][C]0.011902[/C][/ROW]
[ROW][C]11[/C][C]0.28081[/C][C]2.1751[/C][C]0.016786[/C][/ROW]
[ROW][C]12[/C][C]0.256066[/C][C]1.9835[/C][C]0.025948[/C][/ROW]
[ROW][C]13[/C][C]0.227289[/C][C]1.7606[/C][C]0.041704[/C][/ROW]
[ROW][C]14[/C][C]0.196393[/C][C]1.5213[/C][C]0.066725[/C][/ROW]
[ROW][C]15[/C][C]0.169759[/C][C]1.3149[/C][C]0.096766[/C][/ROW]
[ROW][C]16[/C][C]0.148546[/C][C]1.1506[/C][C]0.127225[/C][/ROW]
[ROW][C]17[/C][C]0.129683[/C][C]1.0045[/C][C]0.15958[/C][/ROW]
[ROW][C]18[/C][C]0.112322[/C][C]0.87[/C][C]0.193872[/C][/ROW]
[ROW][C]19[/C][C]0.096828[/C][C]0.75[/C][C]0.228085[/C][/ROW]
[ROW][C]20[/C][C]0.083295[/C][C]0.6452[/C][C]0.260627[/C][/ROW]
[ROW][C]21[/C][C]0.073902[/C][C]0.5724[/C][C]0.284579[/C][/ROW]
[ROW][C]22[/C][C]0.062599[/C][C]0.4849[/C][C]0.314759[/C][/ROW]
[ROW][C]23[/C][C]0.045842[/C][C]0.3551[/C][C]0.361883[/C][/ROW]
[ROW][C]24[/C][C]0.027119[/C][C]0.2101[/C][C]0.417165[/C][/ROW]
[ROW][C]25[/C][C]0.002029[/C][C]0.0157[/C][C]0.493756[/C][/ROW]
[ROW][C]26[/C][C]-0.027609[/C][C]-0.2139[/C][C]0.415691[/C][/ROW]
[ROW][C]27[/C][C]-0.058444[/C][C]-0.4527[/C][C]0.326196[/C][/ROW]
[ROW][C]28[/C][C]-0.086616[/C][C]-0.6709[/C][C]0.252422[/C][/ROW]
[ROW][C]29[/C][C]-0.108854[/C][C]-0.8432[/C][C]0.201238[/C][/ROW]
[ROW][C]30[/C][C]-0.134087[/C][C]-1.0386[/C][C]0.151572[/C][/ROW]
[ROW][C]31[/C][C]-0.160399[/C][C]-1.2424[/C][C]0.109453[/C][/ROW]
[ROW][C]32[/C][C]-0.186349[/C][C]-1.4435[/C][C]0.077047[/C][/ROW]
[ROW][C]33[/C][C]-0.19715[/C][C]-1.5271[/C][C]0.065994[/C][/ROW]
[ROW][C]34[/C][C]-0.200566[/C][C]-1.5536[/C][C]0.062772[/C][/ROW]
[ROW][C]35[/C][C]-0.202621[/C][C]-1.5695[/C][C]0.060896[/C][/ROW]
[ROW][C]36[/C][C]-0.204936[/C][C]-1.5874[/C][C]0.058836[/C][/ROW]
[ROW][C]37[/C][C]-0.208731[/C][C]-1.6168[/C][C]0.055582[/C][/ROW]
[ROW][C]38[/C][C]-0.214308[/C][C]-1.66[/C][C]0.051064[/C][/ROW]
[ROW][C]39[/C][C]-0.226397[/C][C]-1.7537[/C][C]0.042298[/C][/ROW]
[ROW][C]40[/C][C]-0.24109[/C][C]-1.8675[/C][C]0.033361[/C][/ROW]
[ROW][C]41[/C][C]-0.25523[/C][C]-1.977[/C][C]0.026321[/C][/ROW]
[ROW][C]42[/C][C]-0.270946[/C][C]-2.0987[/C][C]0.020028[/C][/ROW]
[ROW][C]43[/C][C]-0.287364[/C][C]-2.2259[/C][C]0.014894[/C][/ROW]
[ROW][C]44[/C][C]-0.303828[/C][C]-2.3534[/C][C]0.010947[/C][/ROW]
[ROW][C]45[/C][C]-0.317118[/C][C]-2.4564[/C][C]0.008473[/C][/ROW]
[ROW][C]46[/C][C]-0.319695[/C][C]-2.4763[/C][C]0.008056[/C][/ROW]
[ROW][C]47[/C][C]-0.314664[/C][C]-2.4374[/C][C]0.008888[/C][/ROW]
[ROW][C]48[/C][C]-0.312454[/C][C]-2.4203[/C][C]0.009277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232551&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232551&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
10.9071837.0270
20.7992046.19060
30.6933055.37031e-06
40.6012384.65729e-06
50.5301514.10656.2e-05
60.467143.61840.000305
70.4041753.13070.001347
80.3472882.69010.004619
90.3153422.44260.008771
100.2994122.31920.011902
110.280812.17510.016786
120.2560661.98350.025948
130.2272891.76060.041704
140.1963931.52130.066725
150.1697591.31490.096766
160.1485461.15060.127225
170.1296831.00450.15958
180.1123220.870.193872
190.0968280.750.228085
200.0832950.64520.260627
210.0739020.57240.284579
220.0625990.48490.314759
230.0458420.35510.361883
240.0271190.21010.417165
250.0020290.01570.493756
26-0.027609-0.21390.415691
27-0.058444-0.45270.326196
28-0.086616-0.67090.252422
29-0.108854-0.84320.201238
30-0.134087-1.03860.151572
31-0.160399-1.24240.109453
32-0.186349-1.44350.077047
33-0.19715-1.52710.065994
34-0.200566-1.55360.062772
35-0.202621-1.56950.060896
36-0.204936-1.58740.058836
37-0.208731-1.61680.055582
38-0.214308-1.660.051064
39-0.226397-1.75370.042298
40-0.24109-1.86750.033361
41-0.25523-1.9770.026321
42-0.270946-2.09870.020028
43-0.287364-2.22590.014894
44-0.303828-2.35340.010947
45-0.317118-2.45640.008473
46-0.319695-2.47630.008056
47-0.314664-2.43740.008888
48-0.312454-2.42030.009277







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9071837.0270
2-0.134321-1.04040.151154
3-0.041722-0.32320.373844
40.0148350.11490.454451
50.0512550.3970.34638
6-0.018121-0.14040.444422
7-0.045496-0.35240.362883
80.0017020.01320.494764
90.1081580.83780.202738
100.0464530.35980.360121
11-0.046079-0.35690.361199
12-0.033666-0.26080.397579
13-0.004885-0.03780.484971
14-0.014506-0.11240.455455
15-0.005036-0.0390.484507
160.0019860.01540.493888
170.0066850.05180.479438
180.0068330.05290.478982
19-0.004695-0.03640.485554
20-0.009692-0.07510.470203
210.0082390.06380.474664
22-0.023827-0.18460.427096
23-0.036998-0.28660.387709
24-0.012278-0.09510.462274
25-0.0449-0.34780.364607
26-0.045151-0.34970.363879
27-0.034969-0.27090.39371
28-0.015931-0.12340.451102
29-0.000606-0.00470.498136
30-0.059847-0.46360.322315
31-0.04644-0.35970.36016
32-0.030604-0.23710.406709
330.0521120.40370.343949
34-0.010221-0.07920.468578
35-0.030529-0.23650.406933
36-0.012139-0.0940.462699
37-0.002244-0.01740.493095
38-0.025346-0.19630.422509
39-0.072506-0.56160.288232
40-0.040562-0.31420.377231
41-0.003289-0.02550.489881
42-0.029562-0.2290.40983
43-0.048337-0.37440.354707
44-0.042268-0.32740.372249
45-0.014699-0.11390.454866
460.022130.17140.432236
47-0.005206-0.04030.483984
48-0.053517-0.41450.339979

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.907183 & 7.027 & 0 \tabularnewline
2 & -0.134321 & -1.0404 & 0.151154 \tabularnewline
3 & -0.041722 & -0.3232 & 0.373844 \tabularnewline
4 & 0.014835 & 0.1149 & 0.454451 \tabularnewline
5 & 0.051255 & 0.397 & 0.34638 \tabularnewline
6 & -0.018121 & -0.1404 & 0.444422 \tabularnewline
7 & -0.045496 & -0.3524 & 0.362883 \tabularnewline
8 & 0.001702 & 0.0132 & 0.494764 \tabularnewline
9 & 0.108158 & 0.8378 & 0.202738 \tabularnewline
10 & 0.046453 & 0.3598 & 0.360121 \tabularnewline
11 & -0.046079 & -0.3569 & 0.361199 \tabularnewline
12 & -0.033666 & -0.2608 & 0.397579 \tabularnewline
13 & -0.004885 & -0.0378 & 0.484971 \tabularnewline
14 & -0.014506 & -0.1124 & 0.455455 \tabularnewline
15 & -0.005036 & -0.039 & 0.484507 \tabularnewline
16 & 0.001986 & 0.0154 & 0.493888 \tabularnewline
17 & 0.006685 & 0.0518 & 0.479438 \tabularnewline
18 & 0.006833 & 0.0529 & 0.478982 \tabularnewline
19 & -0.004695 & -0.0364 & 0.485554 \tabularnewline
20 & -0.009692 & -0.0751 & 0.470203 \tabularnewline
21 & 0.008239 & 0.0638 & 0.474664 \tabularnewline
22 & -0.023827 & -0.1846 & 0.427096 \tabularnewline
23 & -0.036998 & -0.2866 & 0.387709 \tabularnewline
24 & -0.012278 & -0.0951 & 0.462274 \tabularnewline
25 & -0.0449 & -0.3478 & 0.364607 \tabularnewline
26 & -0.045151 & -0.3497 & 0.363879 \tabularnewline
27 & -0.034969 & -0.2709 & 0.39371 \tabularnewline
28 & -0.015931 & -0.1234 & 0.451102 \tabularnewline
29 & -0.000606 & -0.0047 & 0.498136 \tabularnewline
30 & -0.059847 & -0.4636 & 0.322315 \tabularnewline
31 & -0.04644 & -0.3597 & 0.36016 \tabularnewline
32 & -0.030604 & -0.2371 & 0.406709 \tabularnewline
33 & 0.052112 & 0.4037 & 0.343949 \tabularnewline
34 & -0.010221 & -0.0792 & 0.468578 \tabularnewline
35 & -0.030529 & -0.2365 & 0.406933 \tabularnewline
36 & -0.012139 & -0.094 & 0.462699 \tabularnewline
37 & -0.002244 & -0.0174 & 0.493095 \tabularnewline
38 & -0.025346 & -0.1963 & 0.422509 \tabularnewline
39 & -0.072506 & -0.5616 & 0.288232 \tabularnewline
40 & -0.040562 & -0.3142 & 0.377231 \tabularnewline
41 & -0.003289 & -0.0255 & 0.489881 \tabularnewline
42 & -0.029562 & -0.229 & 0.40983 \tabularnewline
43 & -0.048337 & -0.3744 & 0.354707 \tabularnewline
44 & -0.042268 & -0.3274 & 0.372249 \tabularnewline
45 & -0.014699 & -0.1139 & 0.454866 \tabularnewline
46 & 0.02213 & 0.1714 & 0.432236 \tabularnewline
47 & -0.005206 & -0.0403 & 0.483984 \tabularnewline
48 & -0.053517 & -0.4145 & 0.339979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232551&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]0.907183[/C][C]7.027[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.134321[/C][C]-1.0404[/C][C]0.151154[/C][/ROW]
[ROW][C]3[/C][C]-0.041722[/C][C]-0.3232[/C][C]0.373844[/C][/ROW]
[ROW][C]4[/C][C]0.014835[/C][C]0.1149[/C][C]0.454451[/C][/ROW]
[ROW][C]5[/C][C]0.051255[/C][C]0.397[/C][C]0.34638[/C][/ROW]
[ROW][C]6[/C][C]-0.018121[/C][C]-0.1404[/C][C]0.444422[/C][/ROW]
[ROW][C]7[/C][C]-0.045496[/C][C]-0.3524[/C][C]0.362883[/C][/ROW]
[ROW][C]8[/C][C]0.001702[/C][C]0.0132[/C][C]0.494764[/C][/ROW]
[ROW][C]9[/C][C]0.108158[/C][C]0.8378[/C][C]0.202738[/C][/ROW]
[ROW][C]10[/C][C]0.046453[/C][C]0.3598[/C][C]0.360121[/C][/ROW]
[ROW][C]11[/C][C]-0.046079[/C][C]-0.3569[/C][C]0.361199[/C][/ROW]
[ROW][C]12[/C][C]-0.033666[/C][C]-0.2608[/C][C]0.397579[/C][/ROW]
[ROW][C]13[/C][C]-0.004885[/C][C]-0.0378[/C][C]0.484971[/C][/ROW]
[ROW][C]14[/C][C]-0.014506[/C][C]-0.1124[/C][C]0.455455[/C][/ROW]
[ROW][C]15[/C][C]-0.005036[/C][C]-0.039[/C][C]0.484507[/C][/ROW]
[ROW][C]16[/C][C]0.001986[/C][C]0.0154[/C][C]0.493888[/C][/ROW]
[ROW][C]17[/C][C]0.006685[/C][C]0.0518[/C][C]0.479438[/C][/ROW]
[ROW][C]18[/C][C]0.006833[/C][C]0.0529[/C][C]0.478982[/C][/ROW]
[ROW][C]19[/C][C]-0.004695[/C][C]-0.0364[/C][C]0.485554[/C][/ROW]
[ROW][C]20[/C][C]-0.009692[/C][C]-0.0751[/C][C]0.470203[/C][/ROW]
[ROW][C]21[/C][C]0.008239[/C][C]0.0638[/C][C]0.474664[/C][/ROW]
[ROW][C]22[/C][C]-0.023827[/C][C]-0.1846[/C][C]0.427096[/C][/ROW]
[ROW][C]23[/C][C]-0.036998[/C][C]-0.2866[/C][C]0.387709[/C][/ROW]
[ROW][C]24[/C][C]-0.012278[/C][C]-0.0951[/C][C]0.462274[/C][/ROW]
[ROW][C]25[/C][C]-0.0449[/C][C]-0.3478[/C][C]0.364607[/C][/ROW]
[ROW][C]26[/C][C]-0.045151[/C][C]-0.3497[/C][C]0.363879[/C][/ROW]
[ROW][C]27[/C][C]-0.034969[/C][C]-0.2709[/C][C]0.39371[/C][/ROW]
[ROW][C]28[/C][C]-0.015931[/C][C]-0.1234[/C][C]0.451102[/C][/ROW]
[ROW][C]29[/C][C]-0.000606[/C][C]-0.0047[/C][C]0.498136[/C][/ROW]
[ROW][C]30[/C][C]-0.059847[/C][C]-0.4636[/C][C]0.322315[/C][/ROW]
[ROW][C]31[/C][C]-0.04644[/C][C]-0.3597[/C][C]0.36016[/C][/ROW]
[ROW][C]32[/C][C]-0.030604[/C][C]-0.2371[/C][C]0.406709[/C][/ROW]
[ROW][C]33[/C][C]0.052112[/C][C]0.4037[/C][C]0.343949[/C][/ROW]
[ROW][C]34[/C][C]-0.010221[/C][C]-0.0792[/C][C]0.468578[/C][/ROW]
[ROW][C]35[/C][C]-0.030529[/C][C]-0.2365[/C][C]0.406933[/C][/ROW]
[ROW][C]36[/C][C]-0.012139[/C][C]-0.094[/C][C]0.462699[/C][/ROW]
[ROW][C]37[/C][C]-0.002244[/C][C]-0.0174[/C][C]0.493095[/C][/ROW]
[ROW][C]38[/C][C]-0.025346[/C][C]-0.1963[/C][C]0.422509[/C][/ROW]
[ROW][C]39[/C][C]-0.072506[/C][C]-0.5616[/C][C]0.288232[/C][/ROW]
[ROW][C]40[/C][C]-0.040562[/C][C]-0.3142[/C][C]0.377231[/C][/ROW]
[ROW][C]41[/C][C]-0.003289[/C][C]-0.0255[/C][C]0.489881[/C][/ROW]
[ROW][C]42[/C][C]-0.029562[/C][C]-0.229[/C][C]0.40983[/C][/ROW]
[ROW][C]43[/C][C]-0.048337[/C][C]-0.3744[/C][C]0.354707[/C][/ROW]
[ROW][C]44[/C][C]-0.042268[/C][C]-0.3274[/C][C]0.372249[/C][/ROW]
[ROW][C]45[/C][C]-0.014699[/C][C]-0.1139[/C][C]0.454866[/C][/ROW]
[ROW][C]46[/C][C]0.02213[/C][C]0.1714[/C][C]0.432236[/C][/ROW]
[ROW][C]47[/C][C]-0.005206[/C][C]-0.0403[/C][C]0.483984[/C][/ROW]
[ROW][C]48[/C][C]-0.053517[/C][C]-0.4145[/C][C]0.339979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232551&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232551&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
10.9071837.0270
2-0.134321-1.04040.151154
3-0.041722-0.32320.373844
40.0148350.11490.454451
50.0512550.3970.34638
6-0.018121-0.14040.444422
7-0.045496-0.35240.362883
80.0017020.01320.494764
90.1081580.83780.202738
100.0464530.35980.360121
11-0.046079-0.35690.361199
12-0.033666-0.26080.397579
13-0.004885-0.03780.484971
14-0.014506-0.11240.455455
15-0.005036-0.0390.484507
160.0019860.01540.493888
170.0066850.05180.479438
180.0068330.05290.478982
19-0.004695-0.03640.485554
20-0.009692-0.07510.470203
210.0082390.06380.474664
22-0.023827-0.18460.427096
23-0.036998-0.28660.387709
24-0.012278-0.09510.462274
25-0.0449-0.34780.364607
26-0.045151-0.34970.363879
27-0.034969-0.27090.39371
28-0.015931-0.12340.451102
29-0.000606-0.00470.498136
30-0.059847-0.46360.322315
31-0.04644-0.35970.36016
32-0.030604-0.23710.406709
330.0521120.40370.343949
34-0.010221-0.07920.468578
35-0.030529-0.23650.406933
36-0.012139-0.0940.462699
37-0.002244-0.01740.493095
38-0.025346-0.19630.422509
39-0.072506-0.56160.288232
40-0.040562-0.31420.377231
41-0.003289-0.02550.489881
42-0.029562-0.2290.40983
43-0.048337-0.37440.354707
44-0.042268-0.32740.372249
45-0.014699-0.11390.454866
460.022130.17140.432236
47-0.005206-0.04030.483984
48-0.053517-0.41450.339979



Parameters (Session):
par1 = 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):
par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '0'
par2 <- '1'
par1 <- 'Default'
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')