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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 01 Dec 2014 18:28:06 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/01/t1417458503aoh5aar4u3wat8h.htm/, Retrieved Sun, 19 May 2024 12:55:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=262170, Retrieved Sun, 19 May 2024 12:55:54 +0000

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Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [] [2014-12-01 18:28:06] [18123dc03e4972c6afb0cd442b9891ee] [Current]
- R PD    [Classical Decomposition] [] [2014-12-31 12:06:31] [71f2a5ac3ba156c8901e0764f5884b00] 

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Dataseries X:

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Boxplots

7,3
7,1
6,8
6,4
6,1
6,5
7,7
7,9
7,5
6,9
6,6
6,9
7,7
8
8
7,7
7,3
7,4
8,1
8,3
8,1
7,9
7,9
8,3
8,6
8,7
8,5
8,3
8
8
8,8
8,7
8,5
8,1
7,8
7,7
7,5
7,2
6,9
6,6
6,5
6,6
7,7
8
7,7
7,3
7
7
7,3
7,3
7,1
7,1
7
7
7,5
7,8
7,9
8,1
8,3
8,4
8,6
8,5
8,4
8,3
8
8
8,7
8,7
8,6
8,5
8,5
8,6

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262170&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]2 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=262170&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262170&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	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	7.3	NA	NA	1.02192	NA
2	7.1	NA	NA	1.02004	NA
3	6.8	NA	NA	0.997249	NA
4	6.4	NA	NA	0.971092	NA
5	6.1	NA	NA	0.937194	NA
6	6.5	NA	NA	0.938823	NA
7	7.7	7.32598	6.99167	1.04782	1.05105
8	7.9	7.53246	7.04583	1.06907	1.04879
9	7.5	7.40758	7.13333	1.03845	1.01248
10	6.9	7.21417	7.2375	0.996777	0.95645
11	6.6	7.14804	7.34167	0.973627	0.92333
12	6.9	7.33961	7.42917	0.987945	0.940105
13	7.7	7.64739	7.48333	1.02192	1.00688
14	8	7.66732	7.51667	1.02004	1.04339
15	8	7.53754	7.55833	0.997249	1.06135
16	7.7	7.40458	7.625	0.971092	1.0399
17	7.3	7.23592	7.72083	0.937194	1.00886
18	7.4	7.35411	7.83333	0.938823	1.00624
19	8.1	8.30831	7.92917	1.04782	0.974928
20	8.3	8.54808	7.99583	1.06907	0.970979
21	8.1	8.35516	8.04583	1.03845	0.969461
22	7.9	8.06559	8.09167	0.996777	0.97947
23	7.9	7.931	8.14583	0.973627	0.996091
24	8.3	8.10115	8.2	0.987945	1.02455
25	8.6	8.43513	8.25417	1.02192	1.01955
26	8.7	8.46635	8.3	1.02004	1.0276
27	8.5	8.31041	8.33333	0.997249	1.02281
28	8.3	8.11671	8.35833	0.971092	1.02258
29	8	7.83729	8.3625	0.937194	1.02076
30	8	7.82352	8.33333	0.938823	1.02256
31	8.8	8.65758	8.2625	1.04782	1.01645
32	8.7	8.71734	8.15417	1.06907	0.99801
33	8.5	8.33352	8.025	1.03845	1.01998
34	8.1	7.86208	7.8875	0.996777	1.03026
35	7.8	7.54966	7.75417	0.973627	1.03316
36	7.7	7.54131	7.63333	0.987945	1.02104
37	7.5	7.69423	7.52917	1.02192	0.974756
38	7.2	7.60357	7.45417	1.02004	0.946924
39	6.9	7.37133	7.39167	0.997249	0.936059
40	6.6	7.11325	7.325	0.971092	0.927846
41	6.5	6.80247	7.25833	0.937194	0.955535
42	6.6	6.75561	7.19583	0.938823	0.976966
43	7.7	7.50062	7.15833	1.04782	1.02658
44	8	7.64828	7.15417	1.06907	1.04599
45	7.7	7.44219	7.16667	1.03845	1.03464
46	7.3	7.17264	7.19583	0.996777	1.01776
47	7	7.04662	7.2375	0.973627	0.993384
48	7	7.1873	7.275	0.987945	0.973941
49	7.3	7.44301	7.28333	1.02192	0.980786
50	7.3	7.41231	7.26667	1.02004	0.984848
51	7.1	7.24667	7.26667	0.997249	0.97976
52	7.1	7.09707	7.30833	0.971092	1.00041
53	7	6.93133	7.39583	0.937194	1.00991
54	7	7.04899	7.50833	0.938823	0.99305
55	7.5	7.98523	7.62083	1.04782	0.939234
56	7.8	8.25854	7.725	1.06907	0.944477
57	7.9	8.13016	7.82917	1.03845	0.971691
58	8.1	7.90777	7.93333	0.996777	1.02431
59	8.3	7.81335	8.025	0.973627	1.06228
60	8.4	8.01058	8.10833	0.987945	1.04861
61	8.6	8.37977	8.2	1.02192	1.02628
62	8.5	8.4536	8.2875	1.02004	1.00549
63	8.4	8.33118	8.35417	0.997249	1.00826
64	8.3	8.15717	8.4	0.971092	1.01751
65	8	7.89586	8.425	0.937194	1.01319
66	8	7.92523	8.44167	0.938823	1.00943
67	8.7	NA	NA	1.04782	NA
68	8.7	NA	NA	1.06907	NA
69	8.6	NA	NA	1.03845	NA
70	8.5	NA	NA	0.996777	NA
71	8.5	NA	NA	0.973627	NA
72	8.6	NA	NA	0.987945	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 7.3 & NA & NA & 1.02192 & NA \tabularnewline
2 & 7.1 & NA & NA & 1.02004 & NA \tabularnewline
3 & 6.8 & NA & NA & 0.997249 & NA \tabularnewline
4 & 6.4 & NA & NA & 0.971092 & NA \tabularnewline
5 & 6.1 & NA & NA & 0.937194 & NA \tabularnewline
6 & 6.5 & NA & NA & 0.938823 & NA \tabularnewline
7 & 7.7 & 7.32598 & 6.99167 & 1.04782 & 1.05105 \tabularnewline
8 & 7.9 & 7.53246 & 7.04583 & 1.06907 & 1.04879 \tabularnewline
9 & 7.5 & 7.40758 & 7.13333 & 1.03845 & 1.01248 \tabularnewline
10 & 6.9 & 7.21417 & 7.2375 & 0.996777 & 0.95645 \tabularnewline
11 & 6.6 & 7.14804 & 7.34167 & 0.973627 & 0.92333 \tabularnewline
12 & 6.9 & 7.33961 & 7.42917 & 0.987945 & 0.940105 \tabularnewline
13 & 7.7 & 7.64739 & 7.48333 & 1.02192 & 1.00688 \tabularnewline
14 & 8 & 7.66732 & 7.51667 & 1.02004 & 1.04339 \tabularnewline
15 & 8 & 7.53754 & 7.55833 & 0.997249 & 1.06135 \tabularnewline
16 & 7.7 & 7.40458 & 7.625 & 0.971092 & 1.0399 \tabularnewline
17 & 7.3 & 7.23592 & 7.72083 & 0.937194 & 1.00886 \tabularnewline
18 & 7.4 & 7.35411 & 7.83333 & 0.938823 & 1.00624 \tabularnewline
19 & 8.1 & 8.30831 & 7.92917 & 1.04782 & 0.974928 \tabularnewline
20 & 8.3 & 8.54808 & 7.99583 & 1.06907 & 0.970979 \tabularnewline
21 & 8.1 & 8.35516 & 8.04583 & 1.03845 & 0.969461 \tabularnewline
22 & 7.9 & 8.06559 & 8.09167 & 0.996777 & 0.97947 \tabularnewline
23 & 7.9 & 7.931 & 8.14583 & 0.973627 & 0.996091 \tabularnewline
24 & 8.3 & 8.10115 & 8.2 & 0.987945 & 1.02455 \tabularnewline
25 & 8.6 & 8.43513 & 8.25417 & 1.02192 & 1.01955 \tabularnewline
26 & 8.7 & 8.46635 & 8.3 & 1.02004 & 1.0276 \tabularnewline
27 & 8.5 & 8.31041 & 8.33333 & 0.997249 & 1.02281 \tabularnewline
28 & 8.3 & 8.11671 & 8.35833 & 0.971092 & 1.02258 \tabularnewline
29 & 8 & 7.83729 & 8.3625 & 0.937194 & 1.02076 \tabularnewline
30 & 8 & 7.82352 & 8.33333 & 0.938823 & 1.02256 \tabularnewline
31 & 8.8 & 8.65758 & 8.2625 & 1.04782 & 1.01645 \tabularnewline
32 & 8.7 & 8.71734 & 8.15417 & 1.06907 & 0.99801 \tabularnewline
33 & 8.5 & 8.33352 & 8.025 & 1.03845 & 1.01998 \tabularnewline
34 & 8.1 & 7.86208 & 7.8875 & 0.996777 & 1.03026 \tabularnewline
35 & 7.8 & 7.54966 & 7.75417 & 0.973627 & 1.03316 \tabularnewline
36 & 7.7 & 7.54131 & 7.63333 & 0.987945 & 1.02104 \tabularnewline
37 & 7.5 & 7.69423 & 7.52917 & 1.02192 & 0.974756 \tabularnewline
38 & 7.2 & 7.60357 & 7.45417 & 1.02004 & 0.946924 \tabularnewline
39 & 6.9 & 7.37133 & 7.39167 & 0.997249 & 0.936059 \tabularnewline
40 & 6.6 & 7.11325 & 7.325 & 0.971092 & 0.927846 \tabularnewline
41 & 6.5 & 6.80247 & 7.25833 & 0.937194 & 0.955535 \tabularnewline
42 & 6.6 & 6.75561 & 7.19583 & 0.938823 & 0.976966 \tabularnewline
43 & 7.7 & 7.50062 & 7.15833 & 1.04782 & 1.02658 \tabularnewline
44 & 8 & 7.64828 & 7.15417 & 1.06907 & 1.04599 \tabularnewline
45 & 7.7 & 7.44219 & 7.16667 & 1.03845 & 1.03464 \tabularnewline
46 & 7.3 & 7.17264 & 7.19583 & 0.996777 & 1.01776 \tabularnewline
47 & 7 & 7.04662 & 7.2375 & 0.973627 & 0.993384 \tabularnewline
48 & 7 & 7.1873 & 7.275 & 0.987945 & 0.973941 \tabularnewline
49 & 7.3 & 7.44301 & 7.28333 & 1.02192 & 0.980786 \tabularnewline
50 & 7.3 & 7.41231 & 7.26667 & 1.02004 & 0.984848 \tabularnewline
51 & 7.1 & 7.24667 & 7.26667 & 0.997249 & 0.97976 \tabularnewline
52 & 7.1 & 7.09707 & 7.30833 & 0.971092 & 1.00041 \tabularnewline
53 & 7 & 6.93133 & 7.39583 & 0.937194 & 1.00991 \tabularnewline
54 & 7 & 7.04899 & 7.50833 & 0.938823 & 0.99305 \tabularnewline
55 & 7.5 & 7.98523 & 7.62083 & 1.04782 & 0.939234 \tabularnewline
56 & 7.8 & 8.25854 & 7.725 & 1.06907 & 0.944477 \tabularnewline
57 & 7.9 & 8.13016 & 7.82917 & 1.03845 & 0.971691 \tabularnewline
58 & 8.1 & 7.90777 & 7.93333 & 0.996777 & 1.02431 \tabularnewline
59 & 8.3 & 7.81335 & 8.025 & 0.973627 & 1.06228 \tabularnewline
60 & 8.4 & 8.01058 & 8.10833 & 0.987945 & 1.04861 \tabularnewline
61 & 8.6 & 8.37977 & 8.2 & 1.02192 & 1.02628 \tabularnewline
62 & 8.5 & 8.4536 & 8.2875 & 1.02004 & 1.00549 \tabularnewline
63 & 8.4 & 8.33118 & 8.35417 & 0.997249 & 1.00826 \tabularnewline
64 & 8.3 & 8.15717 & 8.4 & 0.971092 & 1.01751 \tabularnewline
65 & 8 & 7.89586 & 8.425 & 0.937194 & 1.01319 \tabularnewline
66 & 8 & 7.92523 & 8.44167 & 0.938823 & 1.00943 \tabularnewline
67 & 8.7 & NA & NA & 1.04782 & NA \tabularnewline
68 & 8.7 & NA & NA & 1.06907 & NA \tabularnewline
69 & 8.6 & NA & NA & 1.03845 & NA \tabularnewline
70 & 8.5 & NA & NA & 0.996777 & NA \tabularnewline
71 & 8.5 & NA & NA & 0.973627 & NA \tabularnewline
72 & 8.6 & NA & NA & 0.987945 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262170&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]7.3[/C][C]NA[/C][C]NA[/C][C]1.02192[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]7.1[/C][C]NA[/C][C]NA[/C][C]1.02004[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]6.8[/C][C]NA[/C][C]NA[/C][C]0.997249[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]6.4[/C][C]NA[/C][C]NA[/C][C]0.971092[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]6.1[/C][C]NA[/C][C]NA[/C][C]0.937194[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]6.5[/C][C]NA[/C][C]NA[/C][C]0.938823[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]7.7[/C][C]7.32598[/C][C]6.99167[/C][C]1.04782[/C][C]1.05105[/C][/ROW]
[ROW][C]8[/C][C]7.9[/C][C]7.53246[/C][C]7.04583[/C][C]1.06907[/C][C]1.04879[/C][/ROW]
[ROW][C]9[/C][C]7.5[/C][C]7.40758[/C][C]7.13333[/C][C]1.03845[/C][C]1.01248[/C][/ROW]
[ROW][C]10[/C][C]6.9[/C][C]7.21417[/C][C]7.2375[/C][C]0.996777[/C][C]0.95645[/C][/ROW]
[ROW][C]11[/C][C]6.6[/C][C]7.14804[/C][C]7.34167[/C][C]0.973627[/C][C]0.92333[/C][/ROW]
[ROW][C]12[/C][C]6.9[/C][C]7.33961[/C][C]7.42917[/C][C]0.987945[/C][C]0.940105[/C][/ROW]
[ROW][C]13[/C][C]7.7[/C][C]7.64739[/C][C]7.48333[/C][C]1.02192[/C][C]1.00688[/C][/ROW]
[ROW][C]14[/C][C]8[/C][C]7.66732[/C][C]7.51667[/C][C]1.02004[/C][C]1.04339[/C][/ROW]
[ROW][C]15[/C][C]8[/C][C]7.53754[/C][C]7.55833[/C][C]0.997249[/C][C]1.06135[/C][/ROW]
[ROW][C]16[/C][C]7.7[/C][C]7.40458[/C][C]7.625[/C][C]0.971092[/C][C]1.0399[/C][/ROW]
[ROW][C]17[/C][C]7.3[/C][C]7.23592[/C][C]7.72083[/C][C]0.937194[/C][C]1.00886[/C][/ROW]
[ROW][C]18[/C][C]7.4[/C][C]7.35411[/C][C]7.83333[/C][C]0.938823[/C][C]1.00624[/C][/ROW]
[ROW][C]19[/C][C]8.1[/C][C]8.30831[/C][C]7.92917[/C][C]1.04782[/C][C]0.974928[/C][/ROW]
[ROW][C]20[/C][C]8.3[/C][C]8.54808[/C][C]7.99583[/C][C]1.06907[/C][C]0.970979[/C][/ROW]
[ROW][C]21[/C][C]8.1[/C][C]8.35516[/C][C]8.04583[/C][C]1.03845[/C][C]0.969461[/C][/ROW]
[ROW][C]22[/C][C]7.9[/C][C]8.06559[/C][C]8.09167[/C][C]0.996777[/C][C]0.97947[/C][/ROW]
[ROW][C]23[/C][C]7.9[/C][C]7.931[/C][C]8.14583[/C][C]0.973627[/C][C]0.996091[/C][/ROW]
[ROW][C]24[/C][C]8.3[/C][C]8.10115[/C][C]8.2[/C][C]0.987945[/C][C]1.02455[/C][/ROW]
[ROW][C]25[/C][C]8.6[/C][C]8.43513[/C][C]8.25417[/C][C]1.02192[/C][C]1.01955[/C][/ROW]
[ROW][C]26[/C][C]8.7[/C][C]8.46635[/C][C]8.3[/C][C]1.02004[/C][C]1.0276[/C][/ROW]
[ROW][C]27[/C][C]8.5[/C][C]8.31041[/C][C]8.33333[/C][C]0.997249[/C][C]1.02281[/C][/ROW]
[ROW][C]28[/C][C]8.3[/C][C]8.11671[/C][C]8.35833[/C][C]0.971092[/C][C]1.02258[/C][/ROW]
[ROW][C]29[/C][C]8[/C][C]7.83729[/C][C]8.3625[/C][C]0.937194[/C][C]1.02076[/C][/ROW]
[ROW][C]30[/C][C]8[/C][C]7.82352[/C][C]8.33333[/C][C]0.938823[/C][C]1.02256[/C][/ROW]
[ROW][C]31[/C][C]8.8[/C][C]8.65758[/C][C]8.2625[/C][C]1.04782[/C][C]1.01645[/C][/ROW]
[ROW][C]32[/C][C]8.7[/C][C]8.71734[/C][C]8.15417[/C][C]1.06907[/C][C]0.99801[/C][/ROW]
[ROW][C]33[/C][C]8.5[/C][C]8.33352[/C][C]8.025[/C][C]1.03845[/C][C]1.01998[/C][/ROW]
[ROW][C]34[/C][C]8.1[/C][C]7.86208[/C][C]7.8875[/C][C]0.996777[/C][C]1.03026[/C][/ROW]
[ROW][C]35[/C][C]7.8[/C][C]7.54966[/C][C]7.75417[/C][C]0.973627[/C][C]1.03316[/C][/ROW]
[ROW][C]36[/C][C]7.7[/C][C]7.54131[/C][C]7.63333[/C][C]0.987945[/C][C]1.02104[/C][/ROW]
[ROW][C]37[/C][C]7.5[/C][C]7.69423[/C][C]7.52917[/C][C]1.02192[/C][C]0.974756[/C][/ROW]
[ROW][C]38[/C][C]7.2[/C][C]7.60357[/C][C]7.45417[/C][C]1.02004[/C][C]0.946924[/C][/ROW]
[ROW][C]39[/C][C]6.9[/C][C]7.37133[/C][C]7.39167[/C][C]0.997249[/C][C]0.936059[/C][/ROW]
[ROW][C]40[/C][C]6.6[/C][C]7.11325[/C][C]7.325[/C][C]0.971092[/C][C]0.927846[/C][/ROW]
[ROW][C]41[/C][C]6.5[/C][C]6.80247[/C][C]7.25833[/C][C]0.937194[/C][C]0.955535[/C][/ROW]
[ROW][C]42[/C][C]6.6[/C][C]6.75561[/C][C]7.19583[/C][C]0.938823[/C][C]0.976966[/C][/ROW]
[ROW][C]43[/C][C]7.7[/C][C]7.50062[/C][C]7.15833[/C][C]1.04782[/C][C]1.02658[/C][/ROW]
[ROW][C]44[/C][C]8[/C][C]7.64828[/C][C]7.15417[/C][C]1.06907[/C][C]1.04599[/C][/ROW]
[ROW][C]45[/C][C]7.7[/C][C]7.44219[/C][C]7.16667[/C][C]1.03845[/C][C]1.03464[/C][/ROW]
[ROW][C]46[/C][C]7.3[/C][C]7.17264[/C][C]7.19583[/C][C]0.996777[/C][C]1.01776[/C][/ROW]
[ROW][C]47[/C][C]7[/C][C]7.04662[/C][C]7.2375[/C][C]0.973627[/C][C]0.993384[/C][/ROW]
[ROW][C]48[/C][C]7[/C][C]7.1873[/C][C]7.275[/C][C]0.987945[/C][C]0.973941[/C][/ROW]
[ROW][C]49[/C][C]7.3[/C][C]7.44301[/C][C]7.28333[/C][C]1.02192[/C][C]0.980786[/C][/ROW]
[ROW][C]50[/C][C]7.3[/C][C]7.41231[/C][C]7.26667[/C][C]1.02004[/C][C]0.984848[/C][/ROW]
[ROW][C]51[/C][C]7.1[/C][C]7.24667[/C][C]7.26667[/C][C]0.997249[/C][C]0.97976[/C][/ROW]
[ROW][C]52[/C][C]7.1[/C][C]7.09707[/C][C]7.30833[/C][C]0.971092[/C][C]1.00041[/C][/ROW]
[ROW][C]53[/C][C]7[/C][C]6.93133[/C][C]7.39583[/C][C]0.937194[/C][C]1.00991[/C][/ROW]
[ROW][C]54[/C][C]7[/C][C]7.04899[/C][C]7.50833[/C][C]0.938823[/C][C]0.99305[/C][/ROW]
[ROW][C]55[/C][C]7.5[/C][C]7.98523[/C][C]7.62083[/C][C]1.04782[/C][C]0.939234[/C][/ROW]
[ROW][C]56[/C][C]7.8[/C][C]8.25854[/C][C]7.725[/C][C]1.06907[/C][C]0.944477[/C][/ROW]
[ROW][C]57[/C][C]7.9[/C][C]8.13016[/C][C]7.82917[/C][C]1.03845[/C][C]0.971691[/C][/ROW]
[ROW][C]58[/C][C]8.1[/C][C]7.90777[/C][C]7.93333[/C][C]0.996777[/C][C]1.02431[/C][/ROW]
[ROW][C]59[/C][C]8.3[/C][C]7.81335[/C][C]8.025[/C][C]0.973627[/C][C]1.06228[/C][/ROW]
[ROW][C]60[/C][C]8.4[/C][C]8.01058[/C][C]8.10833[/C][C]0.987945[/C][C]1.04861[/C][/ROW]
[ROW][C]61[/C][C]8.6[/C][C]8.37977[/C][C]8.2[/C][C]1.02192[/C][C]1.02628[/C][/ROW]
[ROW][C]62[/C][C]8.5[/C][C]8.4536[/C][C]8.2875[/C][C]1.02004[/C][C]1.00549[/C][/ROW]
[ROW][C]63[/C][C]8.4[/C][C]8.33118[/C][C]8.35417[/C][C]0.997249[/C][C]1.00826[/C][/ROW]
[ROW][C]64[/C][C]8.3[/C][C]8.15717[/C][C]8.4[/C][C]0.971092[/C][C]1.01751[/C][/ROW]
[ROW][C]65[/C][C]8[/C][C]7.89586[/C][C]8.425[/C][C]0.937194[/C][C]1.01319[/C][/ROW]
[ROW][C]66[/C][C]8[/C][C]7.92523[/C][C]8.44167[/C][C]0.938823[/C][C]1.00943[/C][/ROW]
[ROW][C]67[/C][C]8.7[/C][C]NA[/C][C]NA[/C][C]1.04782[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]8.7[/C][C]NA[/C][C]NA[/C][C]1.06907[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]8.6[/C][C]NA[/C][C]NA[/C][C]1.03845[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]8.5[/C][C]NA[/C][C]NA[/C][C]0.996777[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]8.5[/C][C]NA[/C][C]NA[/C][C]0.973627[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]8.6[/C][C]NA[/C][C]NA[/C][C]0.987945[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262170&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262170&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	7.3	NA	NA	1.02192	NA
2	7.1	NA	NA	1.02004	NA
3	6.8	NA	NA	0.997249	NA
4	6.4	NA	NA	0.971092	NA
5	6.1	NA	NA	0.937194	NA
6	6.5	NA	NA	0.938823	NA
7	7.7	7.32598	6.99167	1.04782	1.05105
8	7.9	7.53246	7.04583	1.06907	1.04879
9	7.5	7.40758	7.13333	1.03845	1.01248
10	6.9	7.21417	7.2375	0.996777	0.95645
11	6.6	7.14804	7.34167	0.973627	0.92333
12	6.9	7.33961	7.42917	0.987945	0.940105
13	7.7	7.64739	7.48333	1.02192	1.00688
14	8	7.66732	7.51667	1.02004	1.04339
15	8	7.53754	7.55833	0.997249	1.06135
16	7.7	7.40458	7.625	0.971092	1.0399
17	7.3	7.23592	7.72083	0.937194	1.00886
18	7.4	7.35411	7.83333	0.938823	1.00624
19	8.1	8.30831	7.92917	1.04782	0.974928
20	8.3	8.54808	7.99583	1.06907	0.970979
21	8.1	8.35516	8.04583	1.03845	0.969461
22	7.9	8.06559	8.09167	0.996777	0.97947
23	7.9	7.931	8.14583	0.973627	0.996091
24	8.3	8.10115	8.2	0.987945	1.02455
25	8.6	8.43513	8.25417	1.02192	1.01955
26	8.7	8.46635	8.3	1.02004	1.0276
27	8.5	8.31041	8.33333	0.997249	1.02281
28	8.3	8.11671	8.35833	0.971092	1.02258
29	8	7.83729	8.3625	0.937194	1.02076
30	8	7.82352	8.33333	0.938823	1.02256
31	8.8	8.65758	8.2625	1.04782	1.01645
32	8.7	8.71734	8.15417	1.06907	0.99801
33	8.5	8.33352	8.025	1.03845	1.01998
34	8.1	7.86208	7.8875	0.996777	1.03026
35	7.8	7.54966	7.75417	0.973627	1.03316
36	7.7	7.54131	7.63333	0.987945	1.02104
37	7.5	7.69423	7.52917	1.02192	0.974756
38	7.2	7.60357	7.45417	1.02004	0.946924
39	6.9	7.37133	7.39167	0.997249	0.936059
40	6.6	7.11325	7.325	0.971092	0.927846
41	6.5	6.80247	7.25833	0.937194	0.955535
42	6.6	6.75561	7.19583	0.938823	0.976966
43	7.7	7.50062	7.15833	1.04782	1.02658
44	8	7.64828	7.15417	1.06907	1.04599
45	7.7	7.44219	7.16667	1.03845	1.03464
46	7.3	7.17264	7.19583	0.996777	1.01776
47	7	7.04662	7.2375	0.973627	0.993384
48	7	7.1873	7.275	0.987945	0.973941
49	7.3	7.44301	7.28333	1.02192	0.980786
50	7.3	7.41231	7.26667	1.02004	0.984848
51	7.1	7.24667	7.26667	0.997249	0.97976
52	7.1	7.09707	7.30833	0.971092	1.00041
53	7	6.93133	7.39583	0.937194	1.00991
54	7	7.04899	7.50833	0.938823	0.99305
55	7.5	7.98523	7.62083	1.04782	0.939234
56	7.8	8.25854	7.725	1.06907	0.944477
57	7.9	8.13016	7.82917	1.03845	0.971691
58	8.1	7.90777	7.93333	0.996777	1.02431
59	8.3	7.81335	8.025	0.973627	1.06228
60	8.4	8.01058	8.10833	0.987945	1.04861
61	8.6	8.37977	8.2	1.02192	1.02628
62	8.5	8.4536	8.2875	1.02004	1.00549
63	8.4	8.33118	8.35417	0.997249	1.00826
64	8.3	8.15717	8.4	0.971092	1.01751
65	8	7.89586	8.425	0.937194	1.01319
66	8	7.92523	8.44167	0.938823	1.00943
67	8.7	NA	NA	1.04782	NA
68	8.7	NA	NA	1.06907	NA
69	8.6	NA	NA	1.03845	NA
70	8.5	NA	NA	0.996777	NA
71	8.5	NA	NA	0.973627	NA
72	8.6	NA	NA	0.987945	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code