## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSat, 10 Nov 2012 05:49:39 -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/2012/Nov/10/t13525446130z8qj3wr6gdzzqm.htm/, Retrieved Tue, 31 Jan 2023 01:14:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=187286, Retrieved Tue, 31 Jan 2023 01:14:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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- RMP         [Mean versus Median] [mean-median] [2012-11-28 14:02:18] [2c4ddb4bf62114b8025bb962e2c7a2b5]
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- RMPD      [Skewness and Kurtosis Test] [Skewness-kurtosis...] [2012-11-28 13:42:42] [2c4ddb4bf62114b8025bb962e2c7a2b5]
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Dataseries X:
2,25
2,25
2,45
2,5
2,5
2,64
2,75
2,93
3
3,17
3,25
3,39
3,5
3,5
3,65
3,75
3,75
3,9
4
4
4
4
4
4
4
4
4
4
4
4
4,18
4,25
4,25
3,97
3,42
2,75
2,31
2
1,66
1,31
1,09
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1,14
1,25
1,25
1,4
1,5
1,5
1,5
1,32
1,11
1
1
1
1
1
1
0,83
0,75
0,75
0,75

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187286&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]4 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=187286&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187286&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 4 seconds R Server 'Gwilym Jenkins' @ jenkins.wessa.net

 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 2.25 NA NA -0.0796990740740741 NA 2 2.25 NA NA -0.102893518518519 NA 3 2.45 NA NA -0.103796296296296 NA 4 2.5 NA NA -0.0896990740740739 NA 5 2.5 NA NA -0.0995601851851852 NA 6 2.64 NA NA -0.0524768518518518 NA 7 2.75 2.85842592592593 2.80875 0.0496759259259259 -0.108425925925926 8 2.93 3.03828703703704 2.91291666666667 0.12537037037037 -0.108287037037037 9 3 3.17078703703704 3.015 0.155787037037037 -0.170787037037037 10 3.17 3.27502314814815 3.11708333333333 0.157939814814815 -0.105023148148148 11 3.25 3.29168981481481 3.22125 0.0704398148148148 -0.0416898148148146 12 3.39 3.29474537037037 3.32583333333333 -0.0310879629629629 0.0952546296296299 13 3.5 3.35071759259259 3.43041666666667 -0.0796990740740741 0.149282407407407 14 3.5 3.42418981481481 3.52708333333333 -0.102893518518519 0.0758101851851851 15 3.65 3.50953703703704 3.61333333333333 -0.103796296296296 0.140462962962963 16 3.75 3.59988425925926 3.68958333333333 -0.0896990740740739 0.150115740740741 17 3.75 3.65585648148148 3.75541666666667 -0.0995601851851852 0.0941435185185191 18 3.9 3.75960648148148 3.81208333333333 -0.0524768518518518 0.140393518518519 19 4 3.90800925925926 3.85833333333333 0.0496759259259259 0.0919907407407408 20 4 4.02537037037037 3.9 0.12537037037037 -0.0253703703703705 21 4 4.0912037037037 3.93541666666667 0.155787037037037 -0.0912037037037039 22 4 4.11835648148148 3.96041666666667 0.157939814814815 -0.118356481481482 23 4 4.05168981481482 3.98125 0.0704398148148148 -0.0516898148148153 24 4 3.96474537037037 3.99583333333333 -0.0310879629629629 0.035254629629629 25 4 3.92780092592593 4.0075 -0.0796990740740741 0.0721990740740734 26 4 3.92252314814815 4.02541666666667 -0.102893518518519 0.0774768518518512 27 4 3.9424537037037 4.04625 -0.103796296296296 0.0575462962962954 28 4 3.96571759259259 4.05541666666667 -0.0896990740740739 0.0342824074074066 29 4 3.93043981481482 4.03 -0.0995601851851852 0.0695601851851837 30 4 3.90127314814815 3.95375 -0.0524768518518518 0.0987268518518509 31 4.18 3.88092592592593 3.83125 0.0496759259259259 0.299074074074073 32 4.25 3.80287037037037 3.6775 0.12537037037037 0.447129629629629 33 4.25 3.6524537037037 3.49666666666667 0.155787037037037 0.597546296296296 34 3.97 3.44502314814815 3.28708333333333 0.157939814814815 0.524976851851852 35 3.42 3.12418981481481 3.05375 0.0704398148148148 0.295810185185185 36 2.75 2.77641203703704 2.8075 -0.0310879629629629 -0.0264120370370367 37 2.31 2.47030092592593 2.55 -0.0796990740740741 -0.160300925925926 38 2 2.17918981481481 2.28208333333333 -0.102893518518519 -0.179189814814815 39 1.66 1.9074537037037 2.01125 -0.103796296296296 -0.247453703703704 40 1.31 1.66238425925926 1.75208333333333 -0.0896990740740739 -0.352384259259259 41 1.09 1.42793981481481 1.5275 -0.0995601851851852 -0.337939814814815 42 1 1.30127314814815 1.35375 -0.0524768518518518 -0.301273148148148 43 1 1.27592592592593 1.22625 0.0496759259259259 -0.275925925925926 44 1 1.25537037037037 1.13 0.12537037037037 -0.25537037037037 45 1 1.21662037037037 1.06083333333333 0.155787037037037 -0.21662037037037 46 1 1.17835648148148 1.02041666666667 0.157939814814815 -0.178356481481482 47 1 1.07418981481482 1.00375 0.0704398148148148 -0.0741898148148149 48 1 0.968912037037037 1 -0.0310879629629629 0.0310879629629626 49 1 0.920300925925926 1 -0.0796990740740741 0.079699074074074 50 1 0.897106481481482 1 -0.102893518518519 0.102893518518518 51 1 0.896203703703704 1 -0.103796296296296 0.103796296296296 52 1 0.910300925925926 1 -0.0896990740740739 0.0896990740740737 53 1 0.900439814814815 1 -0.0995601851851852 0.0995601851851851 54 1 0.947523148148148 1 -0.0524768518518518 0.0524768518518515 55 1 1.04967592592593 1 0.0496759259259259 -0.0496759259259261 56 1 1.12537037037037 1 0.12537037037037 -0.125370370370371 57 1 1.15578703703704 1 0.155787037037037 -0.155787037037037 58 1 1.16377314814815 1.00583333333333 0.157939814814815 -0.163773148148148 59 1 1.09252314814815 1.02208333333333 0.0704398148148148 -0.0925231481481482 60 1 1.0118287037037 1.04291666666667 -0.0310879629629629 -0.0118287037037041 61 1 0.990300925925926 1.07 -0.0796990740740741 0.00969907407407389 62 1 1.00460648148148 1.1075 -0.102893518518519 -0.00460648148148146 63 1 1.04537037037037 1.14916666666667 -0.103796296296296 -0.0453703703703703 64 1.14 1.10113425925926 1.19083333333333 -0.0896990740740739 0.0388657407407405 65 1.25 1.12543981481481 1.225 -0.0995601851851852 0.124560185185185 66 1.25 1.19043981481481 1.24291666666667 -0.0524768518518518 0.0595601851851852 67 1.4 1.29717592592593 1.2475 0.0496759259259259 0.102824074074074 68 1.5 1.37287037037037 1.2475 0.12537037037037 0.12712962962963 69 1.5 1.40328703703704 1.2475 0.155787037037037 0.0967129629629628 70 1.5 1.39960648148148 1.24166666666667 0.157939814814815 0.100393518518518 71 1.32 1.29585648148148 1.22541666666667 0.0704398148148148 0.0241435185185186 72 1.11 1.17349537037037 1.20458333333333 -0.0310879629629629 -0.0634953703703702 73 1 1.09071759259259 1.17041666666667 -0.0796990740740741 -0.0907175925925925 74 1 1.01252314814815 1.11541666666667 -0.102893518518519 -0.0125231481481478 75 1 0.94912037037037 1.05291666666667 -0.103796296296296 0.0508796296296299 76 1 0.900717592592593 0.990416666666667 -0.0896990740740739 0.0992824074074072 77 1 NA NA -0.0995601851851852 NA 78 1 NA NA -0.0524768518518518 NA 79 0.83 NA NA 0.0496759259259259 NA 80 0.75 NA NA 0.12537037037037 NA 81 0.75 NA NA 0.155787037037037 NA 82 0.75 NA NA 0.157939814814815 NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.25 & NA & NA & -0.0796990740740741 & NA \tabularnewline
2 & 2.25 & NA & NA & -0.102893518518519 & NA \tabularnewline
3 & 2.45 & NA & NA & -0.103796296296296 & NA \tabularnewline
4 & 2.5 & NA & NA & -0.0896990740740739 & NA \tabularnewline
5 & 2.5 & NA & NA & -0.0995601851851852 & NA \tabularnewline
6 & 2.64 & NA & NA & -0.0524768518518518 & NA \tabularnewline
7 & 2.75 & 2.85842592592593 & 2.80875 & 0.0496759259259259 & -0.108425925925926 \tabularnewline
8 & 2.93 & 3.03828703703704 & 2.91291666666667 & 0.12537037037037 & -0.108287037037037 \tabularnewline
9 & 3 & 3.17078703703704 & 3.015 & 0.155787037037037 & -0.170787037037037 \tabularnewline
10 & 3.17 & 3.27502314814815 & 3.11708333333333 & 0.157939814814815 & -0.105023148148148 \tabularnewline
11 & 3.25 & 3.29168981481481 & 3.22125 & 0.0704398148148148 & -0.0416898148148146 \tabularnewline
12 & 3.39 & 3.29474537037037 & 3.32583333333333 & -0.0310879629629629 & 0.0952546296296299 \tabularnewline
13 & 3.5 & 3.35071759259259 & 3.43041666666667 & -0.0796990740740741 & 0.149282407407407 \tabularnewline
14 & 3.5 & 3.42418981481481 & 3.52708333333333 & -0.102893518518519 & 0.0758101851851851 \tabularnewline
15 & 3.65 & 3.50953703703704 & 3.61333333333333 & -0.103796296296296 & 0.140462962962963 \tabularnewline
16 & 3.75 & 3.59988425925926 & 3.68958333333333 & -0.0896990740740739 & 0.150115740740741 \tabularnewline
17 & 3.75 & 3.65585648148148 & 3.75541666666667 & -0.0995601851851852 & 0.0941435185185191 \tabularnewline
18 & 3.9 & 3.75960648148148 & 3.81208333333333 & -0.0524768518518518 & 0.140393518518519 \tabularnewline
19 & 4 & 3.90800925925926 & 3.85833333333333 & 0.0496759259259259 & 0.0919907407407408 \tabularnewline
20 & 4 & 4.02537037037037 & 3.9 & 0.12537037037037 & -0.0253703703703705 \tabularnewline
21 & 4 & 4.0912037037037 & 3.93541666666667 & 0.155787037037037 & -0.0912037037037039 \tabularnewline
22 & 4 & 4.11835648148148 & 3.96041666666667 & 0.157939814814815 & -0.118356481481482 \tabularnewline
23 & 4 & 4.05168981481482 & 3.98125 & 0.0704398148148148 & -0.0516898148148153 \tabularnewline
24 & 4 & 3.96474537037037 & 3.99583333333333 & -0.0310879629629629 & 0.035254629629629 \tabularnewline
25 & 4 & 3.92780092592593 & 4.0075 & -0.0796990740740741 & 0.0721990740740734 \tabularnewline
26 & 4 & 3.92252314814815 & 4.02541666666667 & -0.102893518518519 & 0.0774768518518512 \tabularnewline
27 & 4 & 3.9424537037037 & 4.04625 & -0.103796296296296 & 0.0575462962962954 \tabularnewline
28 & 4 & 3.96571759259259 & 4.05541666666667 & -0.0896990740740739 & 0.0342824074074066 \tabularnewline
29 & 4 & 3.93043981481482 & 4.03 & -0.0995601851851852 & 0.0695601851851837 \tabularnewline
30 & 4 & 3.90127314814815 & 3.95375 & -0.0524768518518518 & 0.0987268518518509 \tabularnewline
31 & 4.18 & 3.88092592592593 & 3.83125 & 0.0496759259259259 & 0.299074074074073 \tabularnewline
32 & 4.25 & 3.80287037037037 & 3.6775 & 0.12537037037037 & 0.447129629629629 \tabularnewline
33 & 4.25 & 3.6524537037037 & 3.49666666666667 & 0.155787037037037 & 0.597546296296296 \tabularnewline
34 & 3.97 & 3.44502314814815 & 3.28708333333333 & 0.157939814814815 & 0.524976851851852 \tabularnewline
35 & 3.42 & 3.12418981481481 & 3.05375 & 0.0704398148148148 & 0.295810185185185 \tabularnewline
36 & 2.75 & 2.77641203703704 & 2.8075 & -0.0310879629629629 & -0.0264120370370367 \tabularnewline
37 & 2.31 & 2.47030092592593 & 2.55 & -0.0796990740740741 & -0.160300925925926 \tabularnewline
38 & 2 & 2.17918981481481 & 2.28208333333333 & -0.102893518518519 & -0.179189814814815 \tabularnewline
39 & 1.66 & 1.9074537037037 & 2.01125 & -0.103796296296296 & -0.247453703703704 \tabularnewline
40 & 1.31 & 1.66238425925926 & 1.75208333333333 & -0.0896990740740739 & -0.352384259259259 \tabularnewline
41 & 1.09 & 1.42793981481481 & 1.5275 & -0.0995601851851852 & -0.337939814814815 \tabularnewline
42 & 1 & 1.30127314814815 & 1.35375 & -0.0524768518518518 & -0.301273148148148 \tabularnewline
43 & 1 & 1.27592592592593 & 1.22625 & 0.0496759259259259 & -0.275925925925926 \tabularnewline
44 & 1 & 1.25537037037037 & 1.13 & 0.12537037037037 & -0.25537037037037 \tabularnewline
45 & 1 & 1.21662037037037 & 1.06083333333333 & 0.155787037037037 & -0.21662037037037 \tabularnewline
46 & 1 & 1.17835648148148 & 1.02041666666667 & 0.157939814814815 & -0.178356481481482 \tabularnewline
47 & 1 & 1.07418981481482 & 1.00375 & 0.0704398148148148 & -0.0741898148148149 \tabularnewline
48 & 1 & 0.968912037037037 & 1 & -0.0310879629629629 & 0.0310879629629626 \tabularnewline
49 & 1 & 0.920300925925926 & 1 & -0.0796990740740741 & 0.079699074074074 \tabularnewline
50 & 1 & 0.897106481481482 & 1 & -0.102893518518519 & 0.102893518518518 \tabularnewline
51 & 1 & 0.896203703703704 & 1 & -0.103796296296296 & 0.103796296296296 \tabularnewline
52 & 1 & 0.910300925925926 & 1 & -0.0896990740740739 & 0.0896990740740737 \tabularnewline
53 & 1 & 0.900439814814815 & 1 & -0.0995601851851852 & 0.0995601851851851 \tabularnewline
54 & 1 & 0.947523148148148 & 1 & -0.0524768518518518 & 0.0524768518518515 \tabularnewline
55 & 1 & 1.04967592592593 & 1 & 0.0496759259259259 & -0.0496759259259261 \tabularnewline
56 & 1 & 1.12537037037037 & 1 & 0.12537037037037 & -0.125370370370371 \tabularnewline
57 & 1 & 1.15578703703704 & 1 & 0.155787037037037 & -0.155787037037037 \tabularnewline
58 & 1 & 1.16377314814815 & 1.00583333333333 & 0.157939814814815 & -0.163773148148148 \tabularnewline
59 & 1 & 1.09252314814815 & 1.02208333333333 & 0.0704398148148148 & -0.0925231481481482 \tabularnewline
60 & 1 & 1.0118287037037 & 1.04291666666667 & -0.0310879629629629 & -0.0118287037037041 \tabularnewline
61 & 1 & 0.990300925925926 & 1.07 & -0.0796990740740741 & 0.00969907407407389 \tabularnewline
62 & 1 & 1.00460648148148 & 1.1075 & -0.102893518518519 & -0.00460648148148146 \tabularnewline
63 & 1 & 1.04537037037037 & 1.14916666666667 & -0.103796296296296 & -0.0453703703703703 \tabularnewline
64 & 1.14 & 1.10113425925926 & 1.19083333333333 & -0.0896990740740739 & 0.0388657407407405 \tabularnewline
65 & 1.25 & 1.12543981481481 & 1.225 & -0.0995601851851852 & 0.124560185185185 \tabularnewline
66 & 1.25 & 1.19043981481481 & 1.24291666666667 & -0.0524768518518518 & 0.0595601851851852 \tabularnewline
67 & 1.4 & 1.29717592592593 & 1.2475 & 0.0496759259259259 & 0.102824074074074 \tabularnewline
68 & 1.5 & 1.37287037037037 & 1.2475 & 0.12537037037037 & 0.12712962962963 \tabularnewline
69 & 1.5 & 1.40328703703704 & 1.2475 & 0.155787037037037 & 0.0967129629629628 \tabularnewline
70 & 1.5 & 1.39960648148148 & 1.24166666666667 & 0.157939814814815 & 0.100393518518518 \tabularnewline
71 & 1.32 & 1.29585648148148 & 1.22541666666667 & 0.0704398148148148 & 0.0241435185185186 \tabularnewline
72 & 1.11 & 1.17349537037037 & 1.20458333333333 & -0.0310879629629629 & -0.0634953703703702 \tabularnewline
73 & 1 & 1.09071759259259 & 1.17041666666667 & -0.0796990740740741 & -0.0907175925925925 \tabularnewline
74 & 1 & 1.01252314814815 & 1.11541666666667 & -0.102893518518519 & -0.0125231481481478 \tabularnewline
75 & 1 & 0.94912037037037 & 1.05291666666667 & -0.103796296296296 & 0.0508796296296299 \tabularnewline
76 & 1 & 0.900717592592593 & 0.990416666666667 & -0.0896990740740739 & 0.0992824074074072 \tabularnewline
77 & 1 & NA & NA & -0.0995601851851852 & NA \tabularnewline
78 & 1 & NA & NA & -0.0524768518518518 & NA \tabularnewline
79 & 0.83 & NA & NA & 0.0496759259259259 & NA \tabularnewline
80 & 0.75 & NA & NA & 0.12537037037037 & NA \tabularnewline
81 & 0.75 & NA & NA & 0.155787037037037 & NA \tabularnewline
82 & 0.75 & NA & NA & 0.157939814814815 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187286&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]2.25[/C][C]NA[/C][C]NA[/C][C]-0.0796990740740741[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.25[/C][C]NA[/C][C]NA[/C][C]-0.102893518518519[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2.45[/C][C]NA[/C][C]NA[/C][C]-0.103796296296296[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2.5[/C][C]NA[/C][C]NA[/C][C]-0.0896990740740739[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.5[/C][C]NA[/C][C]NA[/C][C]-0.0995601851851852[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]2.64[/C][C]NA[/C][C]NA[/C][C]-0.0524768518518518[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]2.75[/C][C]2.85842592592593[/C][C]2.80875[/C][C]0.0496759259259259[/C][C]-0.108425925925926[/C][/ROW]
[ROW][C]8[/C][C]2.93[/C][C]3.03828703703704[/C][C]2.91291666666667[/C][C]0.12537037037037[/C][C]-0.108287037037037[/C][/ROW]
[ROW][C]9[/C][C]3[/C][C]3.17078703703704[/C][C]3.015[/C][C]0.155787037037037[/C][C]-0.170787037037037[/C][/ROW]
[ROW][C]10[/C][C]3.17[/C][C]3.27502314814815[/C][C]3.11708333333333[/C][C]0.157939814814815[/C][C]-0.105023148148148[/C][/ROW]
[ROW][C]11[/C][C]3.25[/C][C]3.29168981481481[/C][C]3.22125[/C][C]0.0704398148148148[/C][C]-0.0416898148148146[/C][/ROW]
[ROW][C]12[/C][C]3.39[/C][C]3.29474537037037[/C][C]3.32583333333333[/C][C]-0.0310879629629629[/C][C]0.0952546296296299[/C][/ROW]
[ROW][C]13[/C][C]3.5[/C][C]3.35071759259259[/C][C]3.43041666666667[/C][C]-0.0796990740740741[/C][C]0.149282407407407[/C][/ROW]
[ROW][C]14[/C][C]3.5[/C][C]3.42418981481481[/C][C]3.52708333333333[/C][C]-0.102893518518519[/C][C]0.0758101851851851[/C][/ROW]
[ROW][C]15[/C][C]3.65[/C][C]3.50953703703704[/C][C]3.61333333333333[/C][C]-0.103796296296296[/C][C]0.140462962962963[/C][/ROW]
[ROW][C]16[/C][C]3.75[/C][C]3.59988425925926[/C][C]3.68958333333333[/C][C]-0.0896990740740739[/C][C]0.150115740740741[/C][/ROW]
[ROW][C]17[/C][C]3.75[/C][C]3.65585648148148[/C][C]3.75541666666667[/C][C]-0.0995601851851852[/C][C]0.0941435185185191[/C][/ROW]
[ROW][C]18[/C][C]3.9[/C][C]3.75960648148148[/C][C]3.81208333333333[/C][C]-0.0524768518518518[/C][C]0.140393518518519[/C][/ROW]
[ROW][C]19[/C][C]4[/C][C]3.90800925925926[/C][C]3.85833333333333[/C][C]0.0496759259259259[/C][C]0.0919907407407408[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]4.02537037037037[/C][C]3.9[/C][C]0.12537037037037[/C][C]-0.0253703703703705[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]4.0912037037037[/C][C]3.93541666666667[/C][C]0.155787037037037[/C][C]-0.0912037037037039[/C][/ROW]
[ROW][C]22[/C][C]4[/C][C]4.11835648148148[/C][C]3.96041666666667[/C][C]0.157939814814815[/C][C]-0.118356481481482[/C][/ROW]
[ROW][C]23[/C][C]4[/C][C]4.05168981481482[/C][C]3.98125[/C][C]0.0704398148148148[/C][C]-0.0516898148148153[/C][/ROW]
[ROW][C]24[/C][C]4[/C][C]3.96474537037037[/C][C]3.99583333333333[/C][C]-0.0310879629629629[/C][C]0.035254629629629[/C][/ROW]
[ROW][C]25[/C][C]4[/C][C]3.92780092592593[/C][C]4.0075[/C][C]-0.0796990740740741[/C][C]0.0721990740740734[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]3.92252314814815[/C][C]4.02541666666667[/C][C]-0.102893518518519[/C][C]0.0774768518518512[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]3.9424537037037[/C][C]4.04625[/C][C]-0.103796296296296[/C][C]0.0575462962962954[/C][/ROW]
[ROW][C]28[/C][C]4[/C][C]3.96571759259259[/C][C]4.05541666666667[/C][C]-0.0896990740740739[/C][C]0.0342824074074066[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]3.93043981481482[/C][C]4.03[/C][C]-0.0995601851851852[/C][C]0.0695601851851837[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]3.90127314814815[/C][C]3.95375[/C][C]-0.0524768518518518[/C][C]0.0987268518518509[/C][/ROW]
[ROW][C]31[/C][C]4.18[/C][C]3.88092592592593[/C][C]3.83125[/C][C]0.0496759259259259[/C][C]0.299074074074073[/C][/ROW]
[ROW][C]32[/C][C]4.25[/C][C]3.80287037037037[/C][C]3.6775[/C][C]0.12537037037037[/C][C]0.447129629629629[/C][/ROW]
[ROW][C]33[/C][C]4.25[/C][C]3.6524537037037[/C][C]3.49666666666667[/C][C]0.155787037037037[/C][C]0.597546296296296[/C][/ROW]
[ROW][C]34[/C][C]3.97[/C][C]3.44502314814815[/C][C]3.28708333333333[/C][C]0.157939814814815[/C][C]0.524976851851852[/C][/ROW]
[ROW][C]35[/C][C]3.42[/C][C]3.12418981481481[/C][C]3.05375[/C][C]0.0704398148148148[/C][C]0.295810185185185[/C][/ROW]
[ROW][C]36[/C][C]2.75[/C][C]2.77641203703704[/C][C]2.8075[/C][C]-0.0310879629629629[/C][C]-0.0264120370370367[/C][/ROW]
[ROW][C]37[/C][C]2.31[/C][C]2.47030092592593[/C][C]2.55[/C][C]-0.0796990740740741[/C][C]-0.160300925925926[/C][/ROW]
[ROW][C]38[/C][C]2[/C][C]2.17918981481481[/C][C]2.28208333333333[/C][C]-0.102893518518519[/C][C]-0.179189814814815[/C][/ROW]
[ROW][C]39[/C][C]1.66[/C][C]1.9074537037037[/C][C]2.01125[/C][C]-0.103796296296296[/C][C]-0.247453703703704[/C][/ROW]
[ROW][C]40[/C][C]1.31[/C][C]1.66238425925926[/C][C]1.75208333333333[/C][C]-0.0896990740740739[/C][C]-0.352384259259259[/C][/ROW]
[ROW][C]41[/C][C]1.09[/C][C]1.42793981481481[/C][C]1.5275[/C][C]-0.0995601851851852[/C][C]-0.337939814814815[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]1.30127314814815[/C][C]1.35375[/C][C]-0.0524768518518518[/C][C]-0.301273148148148[/C][/ROW]
[ROW][C]43[/C][C]1[/C][C]1.27592592592593[/C][C]1.22625[/C][C]0.0496759259259259[/C][C]-0.275925925925926[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]1.25537037037037[/C][C]1.13[/C][C]0.12537037037037[/C][C]-0.25537037037037[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]1.21662037037037[/C][C]1.06083333333333[/C][C]0.155787037037037[/C][C]-0.21662037037037[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]1.17835648148148[/C][C]1.02041666666667[/C][C]0.157939814814815[/C][C]-0.178356481481482[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]1.07418981481482[/C][C]1.00375[/C][C]0.0704398148148148[/C][C]-0.0741898148148149[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.968912037037037[/C][C]1[/C][C]-0.0310879629629629[/C][C]0.0310879629629626[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]0.920300925925926[/C][C]1[/C][C]-0.0796990740740741[/C][C]0.079699074074074[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.897106481481482[/C][C]1[/C][C]-0.102893518518519[/C][C]0.102893518518518[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.896203703703704[/C][C]1[/C][C]-0.103796296296296[/C][C]0.103796296296296[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]0.910300925925926[/C][C]1[/C][C]-0.0896990740740739[/C][C]0.0896990740740737[/C][/ROW]
[ROW][C]53[/C][C]1[/C][C]0.900439814814815[/C][C]1[/C][C]-0.0995601851851852[/C][C]0.0995601851851851[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.947523148148148[/C][C]1[/C][C]-0.0524768518518518[/C][C]0.0524768518518515[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]1.04967592592593[/C][C]1[/C][C]0.0496759259259259[/C][C]-0.0496759259259261[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]1.12537037037037[/C][C]1[/C][C]0.12537037037037[/C][C]-0.125370370370371[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]1.15578703703704[/C][C]1[/C][C]0.155787037037037[/C][C]-0.155787037037037[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]1.16377314814815[/C][C]1.00583333333333[/C][C]0.157939814814815[/C][C]-0.163773148148148[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]1.09252314814815[/C][C]1.02208333333333[/C][C]0.0704398148148148[/C][C]-0.0925231481481482[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]1.0118287037037[/C][C]1.04291666666667[/C][C]-0.0310879629629629[/C][C]-0.0118287037037041[/C][/ROW]
[ROW][C]61[/C][C]1[/C][C]0.990300925925926[/C][C]1.07[/C][C]-0.0796990740740741[/C][C]0.00969907407407389[/C][/ROW]
[ROW][C]62[/C][C]1[/C][C]1.00460648148148[/C][C]1.1075[/C][C]-0.102893518518519[/C][C]-0.00460648148148146[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]1.04537037037037[/C][C]1.14916666666667[/C][C]-0.103796296296296[/C][C]-0.0453703703703703[/C][/ROW]
[ROW][C]64[/C][C]1.14[/C][C]1.10113425925926[/C][C]1.19083333333333[/C][C]-0.0896990740740739[/C][C]0.0388657407407405[/C][/ROW]
[ROW][C]65[/C][C]1.25[/C][C]1.12543981481481[/C][C]1.225[/C][C]-0.0995601851851852[/C][C]0.124560185185185[/C][/ROW]
[ROW][C]66[/C][C]1.25[/C][C]1.19043981481481[/C][C]1.24291666666667[/C][C]-0.0524768518518518[/C][C]0.0595601851851852[/C][/ROW]
[ROW][C]67[/C][C]1.4[/C][C]1.29717592592593[/C][C]1.2475[/C][C]0.0496759259259259[/C][C]0.102824074074074[/C][/ROW]
[ROW][C]68[/C][C]1.5[/C][C]1.37287037037037[/C][C]1.2475[/C][C]0.12537037037037[/C][C]0.12712962962963[/C][/ROW]
[ROW][C]69[/C][C]1.5[/C][C]1.40328703703704[/C][C]1.2475[/C][C]0.155787037037037[/C][C]0.0967129629629628[/C][/ROW]
[ROW][C]70[/C][C]1.5[/C][C]1.39960648148148[/C][C]1.24166666666667[/C][C]0.157939814814815[/C][C]0.100393518518518[/C][/ROW]
[ROW][C]71[/C][C]1.32[/C][C]1.29585648148148[/C][C]1.22541666666667[/C][C]0.0704398148148148[/C][C]0.0241435185185186[/C][/ROW]
[ROW][C]72[/C][C]1.11[/C][C]1.17349537037037[/C][C]1.20458333333333[/C][C]-0.0310879629629629[/C][C]-0.0634953703703702[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]1.09071759259259[/C][C]1.17041666666667[/C][C]-0.0796990740740741[/C][C]-0.0907175925925925[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]1.01252314814815[/C][C]1.11541666666667[/C][C]-0.102893518518519[/C][C]-0.0125231481481478[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.94912037037037[/C][C]1.05291666666667[/C][C]-0.103796296296296[/C][C]0.0508796296296299[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.900717592592593[/C][C]0.990416666666667[/C][C]-0.0896990740740739[/C][C]0.0992824074074072[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]NA[/C][C]NA[/C][C]-0.0995601851851852[/C][C]NA[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]NA[/C][C]NA[/C][C]-0.0524768518518518[/C][C]NA[/C][/ROW]
[ROW][C]79[/C][C]0.83[/C][C]NA[/C][C]NA[/C][C]0.0496759259259259[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]0.75[/C][C]NA[/C][C]NA[/C][C]0.12537037037037[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]0.75[/C][C]NA[/C][C]NA[/C][C]0.155787037037037[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]0.75[/C][C]NA[/C][C]NA[/C][C]0.157939814814815[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187286&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187286&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 2.25 NA NA -0.0796990740740741 NA 2 2.25 NA NA -0.102893518518519 NA 3 2.45 NA NA -0.103796296296296 NA 4 2.5 NA NA -0.0896990740740739 NA 5 2.5 NA NA -0.0995601851851852 NA 6 2.64 NA NA -0.0524768518518518 NA 7 2.75 2.85842592592593 2.80875 0.0496759259259259 -0.108425925925926 8 2.93 3.03828703703704 2.91291666666667 0.12537037037037 -0.108287037037037 9 3 3.17078703703704 3.015 0.155787037037037 -0.170787037037037 10 3.17 3.27502314814815 3.11708333333333 0.157939814814815 -0.105023148148148 11 3.25 3.29168981481481 3.22125 0.0704398148148148 -0.0416898148148146 12 3.39 3.29474537037037 3.32583333333333 -0.0310879629629629 0.0952546296296299 13 3.5 3.35071759259259 3.43041666666667 -0.0796990740740741 0.149282407407407 14 3.5 3.42418981481481 3.52708333333333 -0.102893518518519 0.0758101851851851 15 3.65 3.50953703703704 3.61333333333333 -0.103796296296296 0.140462962962963 16 3.75 3.59988425925926 3.68958333333333 -0.0896990740740739 0.150115740740741 17 3.75 3.65585648148148 3.75541666666667 -0.0995601851851852 0.0941435185185191 18 3.9 3.75960648148148 3.81208333333333 -0.0524768518518518 0.140393518518519 19 4 3.90800925925926 3.85833333333333 0.0496759259259259 0.0919907407407408 20 4 4.02537037037037 3.9 0.12537037037037 -0.0253703703703705 21 4 4.0912037037037 3.93541666666667 0.155787037037037 -0.0912037037037039 22 4 4.11835648148148 3.96041666666667 0.157939814814815 -0.118356481481482 23 4 4.05168981481482 3.98125 0.0704398148148148 -0.0516898148148153 24 4 3.96474537037037 3.99583333333333 -0.0310879629629629 0.035254629629629 25 4 3.92780092592593 4.0075 -0.0796990740740741 0.0721990740740734 26 4 3.92252314814815 4.02541666666667 -0.102893518518519 0.0774768518518512 27 4 3.9424537037037 4.04625 -0.103796296296296 0.0575462962962954 28 4 3.96571759259259 4.05541666666667 -0.0896990740740739 0.0342824074074066 29 4 3.93043981481482 4.03 -0.0995601851851852 0.0695601851851837 30 4 3.90127314814815 3.95375 -0.0524768518518518 0.0987268518518509 31 4.18 3.88092592592593 3.83125 0.0496759259259259 0.299074074074073 32 4.25 3.80287037037037 3.6775 0.12537037037037 0.447129629629629 33 4.25 3.6524537037037 3.49666666666667 0.155787037037037 0.597546296296296 34 3.97 3.44502314814815 3.28708333333333 0.157939814814815 0.524976851851852 35 3.42 3.12418981481481 3.05375 0.0704398148148148 0.295810185185185 36 2.75 2.77641203703704 2.8075 -0.0310879629629629 -0.0264120370370367 37 2.31 2.47030092592593 2.55 -0.0796990740740741 -0.160300925925926 38 2 2.17918981481481 2.28208333333333 -0.102893518518519 -0.179189814814815 39 1.66 1.9074537037037 2.01125 -0.103796296296296 -0.247453703703704 40 1.31 1.66238425925926 1.75208333333333 -0.0896990740740739 -0.352384259259259 41 1.09 1.42793981481481 1.5275 -0.0995601851851852 -0.337939814814815 42 1 1.30127314814815 1.35375 -0.0524768518518518 -0.301273148148148 43 1 1.27592592592593 1.22625 0.0496759259259259 -0.275925925925926 44 1 1.25537037037037 1.13 0.12537037037037 -0.25537037037037 45 1 1.21662037037037 1.06083333333333 0.155787037037037 -0.21662037037037 46 1 1.17835648148148 1.02041666666667 0.157939814814815 -0.178356481481482 47 1 1.07418981481482 1.00375 0.0704398148148148 -0.0741898148148149 48 1 0.968912037037037 1 -0.0310879629629629 0.0310879629629626 49 1 0.920300925925926 1 -0.0796990740740741 0.079699074074074 50 1 0.897106481481482 1 -0.102893518518519 0.102893518518518 51 1 0.896203703703704 1 -0.103796296296296 0.103796296296296 52 1 0.910300925925926 1 -0.0896990740740739 0.0896990740740737 53 1 0.900439814814815 1 -0.0995601851851852 0.0995601851851851 54 1 0.947523148148148 1 -0.0524768518518518 0.0524768518518515 55 1 1.04967592592593 1 0.0496759259259259 -0.0496759259259261 56 1 1.12537037037037 1 0.12537037037037 -0.125370370370371 57 1 1.15578703703704 1 0.155787037037037 -0.155787037037037 58 1 1.16377314814815 1.00583333333333 0.157939814814815 -0.163773148148148 59 1 1.09252314814815 1.02208333333333 0.0704398148148148 -0.0925231481481482 60 1 1.0118287037037 1.04291666666667 -0.0310879629629629 -0.0118287037037041 61 1 0.990300925925926 1.07 -0.0796990740740741 0.00969907407407389 62 1 1.00460648148148 1.1075 -0.102893518518519 -0.00460648148148146 63 1 1.04537037037037 1.14916666666667 -0.103796296296296 -0.0453703703703703 64 1.14 1.10113425925926 1.19083333333333 -0.0896990740740739 0.0388657407407405 65 1.25 1.12543981481481 1.225 -0.0995601851851852 0.124560185185185 66 1.25 1.19043981481481 1.24291666666667 -0.0524768518518518 0.0595601851851852 67 1.4 1.29717592592593 1.2475 0.0496759259259259 0.102824074074074 68 1.5 1.37287037037037 1.2475 0.12537037037037 0.12712962962963 69 1.5 1.40328703703704 1.2475 0.155787037037037 0.0967129629629628 70 1.5 1.39960648148148 1.24166666666667 0.157939814814815 0.100393518518518 71 1.32 1.29585648148148 1.22541666666667 0.0704398148148148 0.0241435185185186 72 1.11 1.17349537037037 1.20458333333333 -0.0310879629629629 -0.0634953703703702 73 1 1.09071759259259 1.17041666666667 -0.0796990740740741 -0.0907175925925925 74 1 1.01252314814815 1.11541666666667 -0.102893518518519 -0.0125231481481478 75 1 0.94912037037037 1.05291666666667 -0.103796296296296 0.0508796296296299 76 1 0.900717592592593 0.990416666666667 -0.0896990740740739 0.0992824074074072 77 1 NA NA -0.0995601851851852 NA 78 1 NA NA -0.0524768518518518 NA 79 0.83 NA NA 0.0496759259259259 NA 80 0.75 NA NA 0.12537037037037 NA 81 0.75 NA NA 0.155787037037037 NA 82 0.75 NA NA 0.157939814814815 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$trend)) {a<-table.row.start(a)a<-table.element(a,i,header=TRUE)a<-table.element(a,x[i])if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])a<-table.element(a,m$trend[i])a<-table.element(a,m$seasonal[i])a<-table.element(a,m$random[i])a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable.tab')