## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Module--
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 04:32:06 -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/12/t13868408944lkbjqbilhcr3bx.htm/, Retrieved Tue, 07 Dec 2021 11:12:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232233, Retrieved Tue, 07 Dec 2021 11:12:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [personenwagens] [2013-12-05 09:34:05] [08f91d6d86abec7b504e1e24533558b8]
- RMP   [Classical Decomposition] [classical decompo...] [2013-12-09 11:06:00] [08f91d6d86abec7b504e1e24533558b8]
- RM        [Classical Decomposition] [decompositie] [2013-12-12 09:32:06] [efb3549c5c864f6f07b072e448ef7cfe] [Current]
Feedback Forum

Post a new message
Dataseries X:
41086
39690
43129
37863
35953
29133
24693
22205
21725
27192
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 6 seconds R Server 'Gwilym Jenkins' @ jenkins.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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232233&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232233&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232233&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 6 seconds R Server 'Gwilym Jenkins' @ jenkins.wessa.net

 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 41086 NA NA 1.32719 NA 2 39690 NA NA 1.20085 NA 3 43129 NA NA 1.32843 NA 4 37863 NA NA 1.22345 NA 5 35953 NA NA 1.01798 NA 6 29133 NA NA 1.0534 NA 7 24693 26076.9 29668.3 0.878948 0.946929 8 22205 22272.2 29138.7 0.76435 0.996983 9 21725 23606.1 28311.8 0.833789 0.920313 10 27192 28306.4 27554.7 1.02728 0.96063 11 21790 21346.1 26986.4 0.790996 1.02079 12 13253 14776.6 26704.4 0.55334 0.896891 13 37702 35460.5 26718.5 1.32719 1.06321 14 30364 32151.4 26774 1.20085 0.944405 15 32609 35511.5 26731.9 1.32843 0.918265 16 30212 32725.3 26748.3 1.22345 0.923201 17 29965 27316.4 26833.8 1.01798 1.09696 18 28352 28317.4 26882 1.0534 1.00122 19 25814 23622.8 26876.2 0.878948 1.09276 20 22414 20673.9 27047.8 0.76435 1.08417 21 20506 22808.8 27355.5 0.833789 0.899041 22 28806 28400.5 27646.3 1.02728 1.01428 23 22228 21917.1 27708.2 0.790996 1.01418 24 13971 15160.1 27397.4 0.55334 0.921565 25 36845 35951.4 27088.4 1.32719 1.02486 26 35338 32123.9 26751 1.20085 1.10005 27 35022 35305.2 26576.6 1.32843 0.991977 28 34777 32343.4 26436.2 1.22345 1.07524 29 26887 26527.1 26058.5 1.01798 1.01357 30 23970 27130.6 25755.4 1.0534 0.883504 31 22780 22352.4 25430.9 0.878948 1.01913 32 17351 19005 24864.3 0.76435 0.912969 33 21382 20251.2 24288.2 0.833789 1.05584 34 24561 24341.6 23695.2 1.02728 1.00901 35 17409 18309 23146.8 0.790996 0.950845 36 11514 12701.6 22954.4 0.55334 0.906502 37 31514 30398.2 22904.3 1.32719 1.0367 38 27071 27487.7 22890.2 1.20085 0.98484 39 29462 30414.8 22895.2 1.32843 0.968672 40 26105 28018.2 22901 1.22345 0.931716 41 22397 23357.3 22944.7 1.01798 0.958886 42 23843 24359.9 23125.1 1.0534 0.978782 43 21705 20345.9 23148 0.878948 1.0668 44 18089 17655.8 23099.1 0.76435 1.02454 45 20764 19582.4 23486.1 0.833789 1.06034 46 25316 24679.2 24023.8 1.02728 1.0258 47 17704 19207.4 24282.6 0.790996 0.921727 48 15548 13454 24314.2 0.55334 1.15564 49 28029 32091.1 24179.8 1.32719 0.87342 50 29383 28823.4 24002.6 1.20085 1.01941 51 36438 31833.3 23963 1.32843 1.14465 52 32034 29168.1 23840.8 1.22345 1.09825 53 22679 24224.2 23796.3 1.01798 0.936212 54 24319 25054.8 23784.8 1.0534 0.970633 55 18004 20904.6 23783.7 0.878948 0.861245 56 17537 18112.9 23697.1 0.76435 0.968207 57 20366 19371.6 23233.2 0.833789 1.05133 58 22782 23315.1 22695.9 1.02728 0.977136 59 19169 17760.4 22453.2 0.790996 1.07931 60 13807 12480.7 22555.3 0.55334 1.10626 61 29743 30083.9 22667.4 1.32719 0.988669 62 25591 27278.1 22715.7 1.20085 0.938152 63 29096 30204.6 22737 1.32843 0.963297 64 26482 27630.1 22583.7 1.22345 0.958449 65 22405 22833.4 22430.1 1.01798 0.981237 66 27044 23461 22271.8 1.0534 1.15272 67 17970 NA NA 0.878948 NA 68 18730 NA NA 0.76435 NA 69 19684 NA NA 0.833789 NA 70 19785 NA NA 1.02728 NA 71 18479 NA NA 0.790996 NA 72 10698 NA NA 0.55334 NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 41086 & NA & NA & 1.32719 & NA \tabularnewline
2 & 39690 & NA & NA & 1.20085 & NA \tabularnewline
3 & 43129 & NA & NA & 1.32843 & NA \tabularnewline
4 & 37863 & NA & NA & 1.22345 & NA \tabularnewline
5 & 35953 & NA & NA & 1.01798 & NA \tabularnewline
6 & 29133 & NA & NA & 1.0534 & NA \tabularnewline
7 & 24693 & 26076.9 & 29668.3 & 0.878948 & 0.946929 \tabularnewline
8 & 22205 & 22272.2 & 29138.7 & 0.76435 & 0.996983 \tabularnewline
9 & 21725 & 23606.1 & 28311.8 & 0.833789 & 0.920313 \tabularnewline
10 & 27192 & 28306.4 & 27554.7 & 1.02728 & 0.96063 \tabularnewline
11 & 21790 & 21346.1 & 26986.4 & 0.790996 & 1.02079 \tabularnewline
12 & 13253 & 14776.6 & 26704.4 & 0.55334 & 0.896891 \tabularnewline
13 & 37702 & 35460.5 & 26718.5 & 1.32719 & 1.06321 \tabularnewline
14 & 30364 & 32151.4 & 26774 & 1.20085 & 0.944405 \tabularnewline
15 & 32609 & 35511.5 & 26731.9 & 1.32843 & 0.918265 \tabularnewline
16 & 30212 & 32725.3 & 26748.3 & 1.22345 & 0.923201 \tabularnewline
17 & 29965 & 27316.4 & 26833.8 & 1.01798 & 1.09696 \tabularnewline
18 & 28352 & 28317.4 & 26882 & 1.0534 & 1.00122 \tabularnewline
19 & 25814 & 23622.8 & 26876.2 & 0.878948 & 1.09276 \tabularnewline
20 & 22414 & 20673.9 & 27047.8 & 0.76435 & 1.08417 \tabularnewline
21 & 20506 & 22808.8 & 27355.5 & 0.833789 & 0.899041 \tabularnewline
22 & 28806 & 28400.5 & 27646.3 & 1.02728 & 1.01428 \tabularnewline
23 & 22228 & 21917.1 & 27708.2 & 0.790996 & 1.01418 \tabularnewline
24 & 13971 & 15160.1 & 27397.4 & 0.55334 & 0.921565 \tabularnewline
25 & 36845 & 35951.4 & 27088.4 & 1.32719 & 1.02486 \tabularnewline
26 & 35338 & 32123.9 & 26751 & 1.20085 & 1.10005 \tabularnewline
27 & 35022 & 35305.2 & 26576.6 & 1.32843 & 0.991977 \tabularnewline
28 & 34777 & 32343.4 & 26436.2 & 1.22345 & 1.07524 \tabularnewline
29 & 26887 & 26527.1 & 26058.5 & 1.01798 & 1.01357 \tabularnewline
30 & 23970 & 27130.6 & 25755.4 & 1.0534 & 0.883504 \tabularnewline
31 & 22780 & 22352.4 & 25430.9 & 0.878948 & 1.01913 \tabularnewline
32 & 17351 & 19005 & 24864.3 & 0.76435 & 0.912969 \tabularnewline
33 & 21382 & 20251.2 & 24288.2 & 0.833789 & 1.05584 \tabularnewline
34 & 24561 & 24341.6 & 23695.2 & 1.02728 & 1.00901 \tabularnewline
35 & 17409 & 18309 & 23146.8 & 0.790996 & 0.950845 \tabularnewline
36 & 11514 & 12701.6 & 22954.4 & 0.55334 & 0.906502 \tabularnewline
37 & 31514 & 30398.2 & 22904.3 & 1.32719 & 1.0367 \tabularnewline
38 & 27071 & 27487.7 & 22890.2 & 1.20085 & 0.98484 \tabularnewline
39 & 29462 & 30414.8 & 22895.2 & 1.32843 & 0.968672 \tabularnewline
40 & 26105 & 28018.2 & 22901 & 1.22345 & 0.931716 \tabularnewline
41 & 22397 & 23357.3 & 22944.7 & 1.01798 & 0.958886 \tabularnewline
42 & 23843 & 24359.9 & 23125.1 & 1.0534 & 0.978782 \tabularnewline
43 & 21705 & 20345.9 & 23148 & 0.878948 & 1.0668 \tabularnewline
44 & 18089 & 17655.8 & 23099.1 & 0.76435 & 1.02454 \tabularnewline
45 & 20764 & 19582.4 & 23486.1 & 0.833789 & 1.06034 \tabularnewline
46 & 25316 & 24679.2 & 24023.8 & 1.02728 & 1.0258 \tabularnewline
47 & 17704 & 19207.4 & 24282.6 & 0.790996 & 0.921727 \tabularnewline
48 & 15548 & 13454 & 24314.2 & 0.55334 & 1.15564 \tabularnewline
49 & 28029 & 32091.1 & 24179.8 & 1.32719 & 0.87342 \tabularnewline
50 & 29383 & 28823.4 & 24002.6 & 1.20085 & 1.01941 \tabularnewline
51 & 36438 & 31833.3 & 23963 & 1.32843 & 1.14465 \tabularnewline
52 & 32034 & 29168.1 & 23840.8 & 1.22345 & 1.09825 \tabularnewline
53 & 22679 & 24224.2 & 23796.3 & 1.01798 & 0.936212 \tabularnewline
54 & 24319 & 25054.8 & 23784.8 & 1.0534 & 0.970633 \tabularnewline
55 & 18004 & 20904.6 & 23783.7 & 0.878948 & 0.861245 \tabularnewline
56 & 17537 & 18112.9 & 23697.1 & 0.76435 & 0.968207 \tabularnewline
57 & 20366 & 19371.6 & 23233.2 & 0.833789 & 1.05133 \tabularnewline
58 & 22782 & 23315.1 & 22695.9 & 1.02728 & 0.977136 \tabularnewline
59 & 19169 & 17760.4 & 22453.2 & 0.790996 & 1.07931 \tabularnewline
60 & 13807 & 12480.7 & 22555.3 & 0.55334 & 1.10626 \tabularnewline
61 & 29743 & 30083.9 & 22667.4 & 1.32719 & 0.988669 \tabularnewline
62 & 25591 & 27278.1 & 22715.7 & 1.20085 & 0.938152 \tabularnewline
63 & 29096 & 30204.6 & 22737 & 1.32843 & 0.963297 \tabularnewline
64 & 26482 & 27630.1 & 22583.7 & 1.22345 & 0.958449 \tabularnewline
65 & 22405 & 22833.4 & 22430.1 & 1.01798 & 0.981237 \tabularnewline
66 & 27044 & 23461 & 22271.8 & 1.0534 & 1.15272 \tabularnewline
67 & 17970 & NA & NA & 0.878948 & NA \tabularnewline
68 & 18730 & NA & NA & 0.76435 & NA \tabularnewline
69 & 19684 & NA & NA & 0.833789 & NA \tabularnewline
70 & 19785 & NA & NA & 1.02728 & NA \tabularnewline
71 & 18479 & NA & NA & 0.790996 & NA \tabularnewline
72 & 10698 & NA & NA & 0.55334 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232233&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]41086[/C][C]NA[/C][C]NA[/C][C]1.32719[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]39690[/C][C]NA[/C][C]NA[/C][C]1.20085[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]43129[/C][C]NA[/C][C]NA[/C][C]1.32843[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]37863[/C][C]NA[/C][C]NA[/C][C]1.22345[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]35953[/C][C]NA[/C][C]NA[/C][C]1.01798[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]29133[/C][C]NA[/C][C]NA[/C][C]1.0534[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]24693[/C][C]26076.9[/C][C]29668.3[/C][C]0.878948[/C][C]0.946929[/C][/ROW]
[ROW][C]8[/C][C]22205[/C][C]22272.2[/C][C]29138.7[/C][C]0.76435[/C][C]0.996983[/C][/ROW]
[ROW][C]9[/C][C]21725[/C][C]23606.1[/C][C]28311.8[/C][C]0.833789[/C][C]0.920313[/C][/ROW]
[ROW][C]10[/C][C]27192[/C][C]28306.4[/C][C]27554.7[/C][C]1.02728[/C][C]0.96063[/C][/ROW]
[ROW][C]11[/C][C]21790[/C][C]21346.1[/C][C]26986.4[/C][C]0.790996[/C][C]1.02079[/C][/ROW]
[ROW][C]12[/C][C]13253[/C][C]14776.6[/C][C]26704.4[/C][C]0.55334[/C][C]0.896891[/C][/ROW]
[ROW][C]13[/C][C]37702[/C][C]35460.5[/C][C]26718.5[/C][C]1.32719[/C][C]1.06321[/C][/ROW]
[ROW][C]14[/C][C]30364[/C][C]32151.4[/C][C]26774[/C][C]1.20085[/C][C]0.944405[/C][/ROW]
[ROW][C]15[/C][C]32609[/C][C]35511.5[/C][C]26731.9[/C][C]1.32843[/C][C]0.918265[/C][/ROW]
[ROW][C]16[/C][C]30212[/C][C]32725.3[/C][C]26748.3[/C][C]1.22345[/C][C]0.923201[/C][/ROW]
[ROW][C]17[/C][C]29965[/C][C]27316.4[/C][C]26833.8[/C][C]1.01798[/C][C]1.09696[/C][/ROW]
[ROW][C]18[/C][C]28352[/C][C]28317.4[/C][C]26882[/C][C]1.0534[/C][C]1.00122[/C][/ROW]
[ROW][C]19[/C][C]25814[/C][C]23622.8[/C][C]26876.2[/C][C]0.878948[/C][C]1.09276[/C][/ROW]
[ROW][C]20[/C][C]22414[/C][C]20673.9[/C][C]27047.8[/C][C]0.76435[/C][C]1.08417[/C][/ROW]
[ROW][C]21[/C][C]20506[/C][C]22808.8[/C][C]27355.5[/C][C]0.833789[/C][C]0.899041[/C][/ROW]
[ROW][C]22[/C][C]28806[/C][C]28400.5[/C][C]27646.3[/C][C]1.02728[/C][C]1.01428[/C][/ROW]
[ROW][C]23[/C][C]22228[/C][C]21917.1[/C][C]27708.2[/C][C]0.790996[/C][C]1.01418[/C][/ROW]
[ROW][C]24[/C][C]13971[/C][C]15160.1[/C][C]27397.4[/C][C]0.55334[/C][C]0.921565[/C][/ROW]
[ROW][C]25[/C][C]36845[/C][C]35951.4[/C][C]27088.4[/C][C]1.32719[/C][C]1.02486[/C][/ROW]
[ROW][C]26[/C][C]35338[/C][C]32123.9[/C][C]26751[/C][C]1.20085[/C][C]1.10005[/C][/ROW]
[ROW][C]27[/C][C]35022[/C][C]35305.2[/C][C]26576.6[/C][C]1.32843[/C][C]0.991977[/C][/ROW]
[ROW][C]28[/C][C]34777[/C][C]32343.4[/C][C]26436.2[/C][C]1.22345[/C][C]1.07524[/C][/ROW]
[ROW][C]29[/C][C]26887[/C][C]26527.1[/C][C]26058.5[/C][C]1.01798[/C][C]1.01357[/C][/ROW]
[ROW][C]30[/C][C]23970[/C][C]27130.6[/C][C]25755.4[/C][C]1.0534[/C][C]0.883504[/C][/ROW]
[ROW][C]31[/C][C]22780[/C][C]22352.4[/C][C]25430.9[/C][C]0.878948[/C][C]1.01913[/C][/ROW]
[ROW][C]32[/C][C]17351[/C][C]19005[/C][C]24864.3[/C][C]0.76435[/C][C]0.912969[/C][/ROW]
[ROW][C]33[/C][C]21382[/C][C]20251.2[/C][C]24288.2[/C][C]0.833789[/C][C]1.05584[/C][/ROW]
[ROW][C]34[/C][C]24561[/C][C]24341.6[/C][C]23695.2[/C][C]1.02728[/C][C]1.00901[/C][/ROW]
[ROW][C]35[/C][C]17409[/C][C]18309[/C][C]23146.8[/C][C]0.790996[/C][C]0.950845[/C][/ROW]
[ROW][C]36[/C][C]11514[/C][C]12701.6[/C][C]22954.4[/C][C]0.55334[/C][C]0.906502[/C][/ROW]
[ROW][C]37[/C][C]31514[/C][C]30398.2[/C][C]22904.3[/C][C]1.32719[/C][C]1.0367[/C][/ROW]
[ROW][C]38[/C][C]27071[/C][C]27487.7[/C][C]22890.2[/C][C]1.20085[/C][C]0.98484[/C][/ROW]
[ROW][C]39[/C][C]29462[/C][C]30414.8[/C][C]22895.2[/C][C]1.32843[/C][C]0.968672[/C][/ROW]
[ROW][C]40[/C][C]26105[/C][C]28018.2[/C][C]22901[/C][C]1.22345[/C][C]0.931716[/C][/ROW]
[ROW][C]41[/C][C]22397[/C][C]23357.3[/C][C]22944.7[/C][C]1.01798[/C][C]0.958886[/C][/ROW]
[ROW][C]42[/C][C]23843[/C][C]24359.9[/C][C]23125.1[/C][C]1.0534[/C][C]0.978782[/C][/ROW]
[ROW][C]43[/C][C]21705[/C][C]20345.9[/C][C]23148[/C][C]0.878948[/C][C]1.0668[/C][/ROW]
[ROW][C]44[/C][C]18089[/C][C]17655.8[/C][C]23099.1[/C][C]0.76435[/C][C]1.02454[/C][/ROW]
[ROW][C]45[/C][C]20764[/C][C]19582.4[/C][C]23486.1[/C][C]0.833789[/C][C]1.06034[/C][/ROW]
[ROW][C]46[/C][C]25316[/C][C]24679.2[/C][C]24023.8[/C][C]1.02728[/C][C]1.0258[/C][/ROW]
[ROW][C]47[/C][C]17704[/C][C]19207.4[/C][C]24282.6[/C][C]0.790996[/C][C]0.921727[/C][/ROW]
[ROW][C]48[/C][C]15548[/C][C]13454[/C][C]24314.2[/C][C]0.55334[/C][C]1.15564[/C][/ROW]
[ROW][C]49[/C][C]28029[/C][C]32091.1[/C][C]24179.8[/C][C]1.32719[/C][C]0.87342[/C][/ROW]
[ROW][C]50[/C][C]29383[/C][C]28823.4[/C][C]24002.6[/C][C]1.20085[/C][C]1.01941[/C][/ROW]
[ROW][C]51[/C][C]36438[/C][C]31833.3[/C][C]23963[/C][C]1.32843[/C][C]1.14465[/C][/ROW]
[ROW][C]52[/C][C]32034[/C][C]29168.1[/C][C]23840.8[/C][C]1.22345[/C][C]1.09825[/C][/ROW]
[ROW][C]53[/C][C]22679[/C][C]24224.2[/C][C]23796.3[/C][C]1.01798[/C][C]0.936212[/C][/ROW]
[ROW][C]54[/C][C]24319[/C][C]25054.8[/C][C]23784.8[/C][C]1.0534[/C][C]0.970633[/C][/ROW]
[ROW][C]55[/C][C]18004[/C][C]20904.6[/C][C]23783.7[/C][C]0.878948[/C][C]0.861245[/C][/ROW]
[ROW][C]56[/C][C]17537[/C][C]18112.9[/C][C]23697.1[/C][C]0.76435[/C][C]0.968207[/C][/ROW]
[ROW][C]57[/C][C]20366[/C][C]19371.6[/C][C]23233.2[/C][C]0.833789[/C][C]1.05133[/C][/ROW]
[ROW][C]58[/C][C]22782[/C][C]23315.1[/C][C]22695.9[/C][C]1.02728[/C][C]0.977136[/C][/ROW]
[ROW][C]59[/C][C]19169[/C][C]17760.4[/C][C]22453.2[/C][C]0.790996[/C][C]1.07931[/C][/ROW]
[ROW][C]60[/C][C]13807[/C][C]12480.7[/C][C]22555.3[/C][C]0.55334[/C][C]1.10626[/C][/ROW]
[ROW][C]61[/C][C]29743[/C][C]30083.9[/C][C]22667.4[/C][C]1.32719[/C][C]0.988669[/C][/ROW]
[ROW][C]62[/C][C]25591[/C][C]27278.1[/C][C]22715.7[/C][C]1.20085[/C][C]0.938152[/C][/ROW]
[ROW][C]63[/C][C]29096[/C][C]30204.6[/C][C]22737[/C][C]1.32843[/C][C]0.963297[/C][/ROW]
[ROW][C]64[/C][C]26482[/C][C]27630.1[/C][C]22583.7[/C][C]1.22345[/C][C]0.958449[/C][/ROW]
[ROW][C]65[/C][C]22405[/C][C]22833.4[/C][C]22430.1[/C][C]1.01798[/C][C]0.981237[/C][/ROW]
[ROW][C]66[/C][C]27044[/C][C]23461[/C][C]22271.8[/C][C]1.0534[/C][C]1.15272[/C][/ROW]
[ROW][C]67[/C][C]17970[/C][C]NA[/C][C]NA[/C][C]0.878948[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]18730[/C][C]NA[/C][C]NA[/C][C]0.76435[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]19684[/C][C]NA[/C][C]NA[/C][C]0.833789[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]19785[/C][C]NA[/C][C]NA[/C][C]1.02728[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]18479[/C][C]NA[/C][C]NA[/C][C]0.790996[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]10698[/C][C]NA[/C][C]NA[/C][C]0.55334[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232233&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232233&T=1

As an alternative you can also use a QR Code:

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

 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 41086 NA NA 1.32719 NA 2 39690 NA NA 1.20085 NA 3 43129 NA NA 1.32843 NA 4 37863 NA NA 1.22345 NA 5 35953 NA NA 1.01798 NA 6 29133 NA NA 1.0534 NA 7 24693 26076.9 29668.3 0.878948 0.946929 8 22205 22272.2 29138.7 0.76435 0.996983 9 21725 23606.1 28311.8 0.833789 0.920313 10 27192 28306.4 27554.7 1.02728 0.96063 11 21790 21346.1 26986.4 0.790996 1.02079 12 13253 14776.6 26704.4 0.55334 0.896891 13 37702 35460.5 26718.5 1.32719 1.06321 14 30364 32151.4 26774 1.20085 0.944405 15 32609 35511.5 26731.9 1.32843 0.918265 16 30212 32725.3 26748.3 1.22345 0.923201 17 29965 27316.4 26833.8 1.01798 1.09696 18 28352 28317.4 26882 1.0534 1.00122 19 25814 23622.8 26876.2 0.878948 1.09276 20 22414 20673.9 27047.8 0.76435 1.08417 21 20506 22808.8 27355.5 0.833789 0.899041 22 28806 28400.5 27646.3 1.02728 1.01428 23 22228 21917.1 27708.2 0.790996 1.01418 24 13971 15160.1 27397.4 0.55334 0.921565 25 36845 35951.4 27088.4 1.32719 1.02486 26 35338 32123.9 26751 1.20085 1.10005 27 35022 35305.2 26576.6 1.32843 0.991977 28 34777 32343.4 26436.2 1.22345 1.07524 29 26887 26527.1 26058.5 1.01798 1.01357 30 23970 27130.6 25755.4 1.0534 0.883504 31 22780 22352.4 25430.9 0.878948 1.01913 32 17351 19005 24864.3 0.76435 0.912969 33 21382 20251.2 24288.2 0.833789 1.05584 34 24561 24341.6 23695.2 1.02728 1.00901 35 17409 18309 23146.8 0.790996 0.950845 36 11514 12701.6 22954.4 0.55334 0.906502 37 31514 30398.2 22904.3 1.32719 1.0367 38 27071 27487.7 22890.2 1.20085 0.98484 39 29462 30414.8 22895.2 1.32843 0.968672 40 26105 28018.2 22901 1.22345 0.931716 41 22397 23357.3 22944.7 1.01798 0.958886 42 23843 24359.9 23125.1 1.0534 0.978782 43 21705 20345.9 23148 0.878948 1.0668 44 18089 17655.8 23099.1 0.76435 1.02454 45 20764 19582.4 23486.1 0.833789 1.06034 46 25316 24679.2 24023.8 1.02728 1.0258 47 17704 19207.4 24282.6 0.790996 0.921727 48 15548 13454 24314.2 0.55334 1.15564 49 28029 32091.1 24179.8 1.32719 0.87342 50 29383 28823.4 24002.6 1.20085 1.01941 51 36438 31833.3 23963 1.32843 1.14465 52 32034 29168.1 23840.8 1.22345 1.09825 53 22679 24224.2 23796.3 1.01798 0.936212 54 24319 25054.8 23784.8 1.0534 0.970633 55 18004 20904.6 23783.7 0.878948 0.861245 56 17537 18112.9 23697.1 0.76435 0.968207 57 20366 19371.6 23233.2 0.833789 1.05133 58 22782 23315.1 22695.9 1.02728 0.977136 59 19169 17760.4 22453.2 0.790996 1.07931 60 13807 12480.7 22555.3 0.55334 1.10626 61 29743 30083.9 22667.4 1.32719 0.988669 62 25591 27278.1 22715.7 1.20085 0.938152 63 29096 30204.6 22737 1.32843 0.963297 64 26482 27630.1 22583.7 1.22345 0.958449 65 22405 22833.4 22430.1 1.01798 0.981237 66 27044 23461 22271.8 1.0534 1.15272 67 17970 NA NA 0.878948 NA 68 18730 NA NA 0.76435 NA 69 19684 NA NA 0.833789 NA 70 19785 NA NA 1.02728 NA 71 18479 NA NA 0.790996 NA 72 10698 NA NA 0.55334 NA

par2 <- as.numeric(par2)x <- ts(x,freq=par2)m <- decompose(x,type=par1)m$figurebitmap(file='test1.png')plot(m)dev.off()mylagmax <- length(x)/2bitmap(file='test2.png')op <- par(mfrow = c(2,2))acf(as.numeric(x),lag.max = mylagmax,main='Observed')acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')par(op)dev.off()bitmap(file='test3.png')op <- par(mfrow = c(2,2))spectrum(as.numeric(x),main='Observed')spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')par(op)dev.off()bitmap(file='test4.png')op <- par(mfrow = c(2,2))cpgram(as.numeric(x),main='Observed')cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')par(op)dev.off()load(file='createtable')a<-table.start()a<-table.row.start(a)a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'t',header=TRUE)a<-table.element(a,'Observations',header=TRUE)a<-table.element(a,'Fit',header=TRUE)a<-table.element(a,'Trend',header=TRUE)a<-table.element(a,'Seasonal',header=TRUE)a<-table.element(a,'Random',header=TRUE)a<-table.row.end(a)for (i in 1:length(m$trend)) {a<-table.row.start(a)a<-table.element(a,i,header=TRUE)a<-table.element(a,x[i])if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))a<-table.element(a,signif(m$trend[i],6))a<-table.element(a,signif(m$seasonal[i],6))a<-table.element(a,signif(m$random[i],6))a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable.tab')