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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 Sat, 10 Dec 2022 04:59:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=187286, Retrieved Sat, 10 Dec 2022 04:59:00 +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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- 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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
12.25NANA-0.0796990740740741NA
22.25NANA-0.102893518518519NA
32.45NANA-0.103796296296296NA
42.5NANA-0.0896990740740739NA
52.5NANA-0.0995601851851852NA
62.64NANA-0.0524768518518518NA
72.752.858425925925932.808750.0496759259259259-0.108425925925926
82.933.038287037037042.912916666666670.12537037037037-0.108287037037037
933.170787037037043.0150.155787037037037-0.170787037037037
103.173.275023148148153.117083333333330.157939814814815-0.105023148148148
113.253.291689814814813.221250.0704398148148148-0.0416898148148146
123.393.294745370370373.32583333333333-0.03108796296296290.0952546296296299
133.53.350717592592593.43041666666667-0.07969907407407410.149282407407407
143.53.424189814814813.52708333333333-0.1028935185185190.0758101851851851
153.653.509537037037043.61333333333333-0.1037962962962960.140462962962963
163.753.599884259259263.68958333333333-0.08969907407407390.150115740740741
173.753.655856481481483.75541666666667-0.09956018518518520.0941435185185191
183.93.759606481481483.81208333333333-0.05247685185185180.140393518518519
1943.908009259259263.858333333333330.04967592592592590.0919907407407408
2044.025370370370373.90.12537037037037-0.0253703703703705
2144.09120370370373.935416666666670.155787037037037-0.0912037037037039
2244.118356481481483.960416666666670.157939814814815-0.118356481481482
2344.051689814814823.981250.0704398148148148-0.0516898148148153
2443.964745370370373.99583333333333-0.03108796296296290.035254629629629
2543.927800925925934.0075-0.07969907407407410.0721990740740734
2643.922523148148154.02541666666667-0.1028935185185190.0774768518518512
2743.94245370370374.04625-0.1037962962962960.0575462962962954
2843.965717592592594.05541666666667-0.08969907407407390.0342824074074066
2943.930439814814824.03-0.09956018518518520.0695601851851837
3043.901273148148153.95375-0.05247685185185180.0987268518518509
314.183.880925925925933.831250.04967592592592590.299074074074073
324.253.802870370370373.67750.125370370370370.447129629629629
334.253.65245370370373.496666666666670.1557870370370370.597546296296296
343.973.445023148148153.287083333333330.1579398148148150.524976851851852
353.423.124189814814813.053750.07043981481481480.295810185185185
362.752.776412037037042.8075-0.0310879629629629-0.0264120370370367
372.312.470300925925932.55-0.0796990740740741-0.160300925925926
3822.179189814814812.28208333333333-0.102893518518519-0.179189814814815
391.661.90745370370372.01125-0.103796296296296-0.247453703703704
401.311.662384259259261.75208333333333-0.0896990740740739-0.352384259259259
411.091.427939814814811.5275-0.0995601851851852-0.337939814814815
4211.301273148148151.35375-0.0524768518518518-0.301273148148148
4311.275925925925931.226250.0496759259259259-0.275925925925926
4411.255370370370371.130.12537037037037-0.25537037037037
4511.216620370370371.060833333333330.155787037037037-0.21662037037037
4611.178356481481481.020416666666670.157939814814815-0.178356481481482
4711.074189814814821.003750.0704398148148148-0.0741898148148149
4810.9689120370370371-0.03108796296296290.0310879629629626
4910.9203009259259261-0.07969907407407410.079699074074074
5010.8971064814814821-0.1028935185185190.102893518518518
5110.8962037037037041-0.1037962962962960.103796296296296
5210.9103009259259261-0.08969907407407390.0896990740740737
5310.9004398148148151-0.09956018518518520.0995601851851851
5410.9475231481481481-0.05247685185185180.0524768518518515
5511.0496759259259310.0496759259259259-0.0496759259259261
5611.1253703703703710.12537037037037-0.125370370370371
5711.1557870370370410.155787037037037-0.155787037037037
5811.163773148148151.005833333333330.157939814814815-0.163773148148148
5911.092523148148151.022083333333330.0704398148148148-0.0925231481481482
6011.01182870370371.04291666666667-0.0310879629629629-0.0118287037037041
6110.9903009259259261.07-0.07969907407407410.00969907407407389
6211.004606481481481.1075-0.102893518518519-0.00460648148148146
6311.045370370370371.14916666666667-0.103796296296296-0.0453703703703703
641.141.101134259259261.19083333333333-0.08969907407407390.0388657407407405
651.251.125439814814811.225-0.09956018518518520.124560185185185
661.251.190439814814811.24291666666667-0.05247685185185180.0595601851851852
671.41.297175925925931.24750.04967592592592590.102824074074074
681.51.372870370370371.24750.125370370370370.12712962962963
691.51.403287037037041.24750.1557870370370370.0967129629629628
701.51.399606481481481.241666666666670.1579398148148150.100393518518518
711.321.295856481481481.225416666666670.07043981481481480.0241435185185186
721.111.173495370370371.20458333333333-0.0310879629629629-0.0634953703703702
7311.090717592592591.17041666666667-0.0796990740740741-0.0907175925925925
7411.012523148148151.11541666666667-0.102893518518519-0.0125231481481478
7510.949120370370371.05291666666667-0.1037962962962960.0508796296296299
7610.9007175925925930.990416666666667-0.08969907407407390.0992824074074072
771NANA-0.0995601851851852NA
781NANA-0.0524768518518518NA
790.83NANA0.0496759259259259NA
800.75NANA0.12537037037037NA
810.75NANA0.155787037037037NA
820.75NANA0.157939814814815NA

\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
tObservationsFitTrendSeasonalRandom
12.25NANA-0.0796990740740741NA
22.25NANA-0.102893518518519NA
32.45NANA-0.103796296296296NA
42.5NANA-0.0896990740740739NA
52.5NANA-0.0995601851851852NA
62.64NANA-0.0524768518518518NA
72.752.858425925925932.808750.0496759259259259-0.108425925925926
82.933.038287037037042.912916666666670.12537037037037-0.108287037037037
933.170787037037043.0150.155787037037037-0.170787037037037
103.173.275023148148153.117083333333330.157939814814815-0.105023148148148
113.253.291689814814813.221250.0704398148148148-0.0416898148148146
123.393.294745370370373.32583333333333-0.03108796296296290.0952546296296299
133.53.350717592592593.43041666666667-0.07969907407407410.149282407407407
143.53.424189814814813.52708333333333-0.1028935185185190.0758101851851851
153.653.509537037037043.61333333333333-0.1037962962962960.140462962962963
163.753.599884259259263.68958333333333-0.08969907407407390.150115740740741
173.753.655856481481483.75541666666667-0.09956018518518520.0941435185185191
183.93.759606481481483.81208333333333-0.05247685185185180.140393518518519
1943.908009259259263.858333333333330.04967592592592590.0919907407407408
2044.025370370370373.90.12537037037037-0.0253703703703705
2144.09120370370373.935416666666670.155787037037037-0.0912037037037039
2244.118356481481483.960416666666670.157939814814815-0.118356481481482
2344.051689814814823.981250.0704398148148148-0.0516898148148153
2443.964745370370373.99583333333333-0.03108796296296290.035254629629629
2543.927800925925934.0075-0.07969907407407410.0721990740740734
2643.922523148148154.02541666666667-0.1028935185185190.0774768518518512
2743.94245370370374.04625-0.1037962962962960.0575462962962954
2843.965717592592594.05541666666667-0.08969907407407390.0342824074074066
2943.930439814814824.03-0.09956018518518520.0695601851851837
3043.901273148148153.95375-0.05247685185185180.0987268518518509
314.183.880925925925933.831250.04967592592592590.299074074074073
324.253.802870370370373.67750.125370370370370.447129629629629
334.253.65245370370373.496666666666670.1557870370370370.597546296296296
343.973.445023148148153.287083333333330.1579398148148150.524976851851852
353.423.124189814814813.053750.07043981481481480.295810185185185
362.752.776412037037042.8075-0.0310879629629629-0.0264120370370367
372.312.470300925925932.55-0.0796990740740741-0.160300925925926
3822.179189814814812.28208333333333-0.102893518518519-0.179189814814815
391.661.90745370370372.01125-0.103796296296296-0.247453703703704
401.311.662384259259261.75208333333333-0.0896990740740739-0.352384259259259
411.091.427939814814811.5275-0.0995601851851852-0.337939814814815
4211.301273148148151.35375-0.0524768518518518-0.301273148148148
4311.275925925925931.226250.0496759259259259-0.275925925925926
4411.255370370370371.130.12537037037037-0.25537037037037
4511.216620370370371.060833333333330.155787037037037-0.21662037037037
4611.178356481481481.020416666666670.157939814814815-0.178356481481482
4711.074189814814821.003750.0704398148148148-0.0741898148148149
4810.9689120370370371-0.03108796296296290.0310879629629626
4910.9203009259259261-0.07969907407407410.079699074074074
5010.8971064814814821-0.1028935185185190.102893518518518
5110.8962037037037041-0.1037962962962960.103796296296296
5210.9103009259259261-0.08969907407407390.0896990740740737
5310.9004398148148151-0.09956018518518520.0995601851851851
5410.9475231481481481-0.05247685185185180.0524768518518515
5511.0496759259259310.0496759259259259-0.0496759259259261
5611.1253703703703710.12537037037037-0.125370370370371
5711.1557870370370410.155787037037037-0.155787037037037
5811.163773148148151.005833333333330.157939814814815-0.163773148148148
5911.092523148148151.022083333333330.0704398148148148-0.0925231481481482
6011.01182870370371.04291666666667-0.0310879629629629-0.0118287037037041
6110.9903009259259261.07-0.07969907407407410.00969907407407389
6211.004606481481481.1075-0.102893518518519-0.00460648148148146
6311.045370370370371.14916666666667-0.103796296296296-0.0453703703703703
641.141.101134259259261.19083333333333-0.08969907407407390.0388657407407405
651.251.125439814814811.225-0.09956018518518520.124560185185185
661.251.190439814814811.24291666666667-0.05247685185185180.0595601851851852
671.41.297175925925931.24750.04967592592592590.102824074074074
681.51.372870370370371.24750.125370370370370.12712962962963
691.51.403287037037041.24750.1557870370370370.0967129629629628
701.51.399606481481481.241666666666670.1579398148148150.100393518518518
711.321.295856481481481.225416666666670.07043981481481480.0241435185185186
721.111.173495370370371.20458333333333-0.0310879629629629-0.0634953703703702
7311.090717592592591.17041666666667-0.0796990740740741-0.0907175925925925
7411.012523148148151.11541666666667-0.102893518518519-0.0125231481481478
7510.949120370370371.05291666666667-0.1037962962962960.0508796296296299
7610.9007175925925930.990416666666667-0.08969907407407390.0992824074074072
771NANA-0.0995601851851852NA
781NANA-0.0524768518518518NA
790.83NANA0.0496759259259259NA
800.75NANA0.12537037037037NA
810.75NANA0.155787037037037NA
820.75NANA0.157939814814815NA



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$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')