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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 19 Dec 2010 10:46:58 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/19/t12927555933mhglf6n1uns6qv.htm/, Retrieved Sun, 05 May 2024 04:35:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112270, Retrieved Sun, 05 May 2024 04:35:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- R PD    [Standard Deviation-Mean Plot] [tutorial] [2010-12-13 19:55:01] [2db53827eae1799a3d605fb62e1e92dc]
-    D      [Standard Deviation-Mean Plot] [tutorial9SMP] [2010-12-15 16:56:05] [8b2514d8f13517d765015fc185a22b4b]
-    D          [Standard Deviation-Mean Plot] [SMP] [2010-12-19 10:46:58] [109f5cd2d2b7c934778912c55604f6f1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
126,64
126,81
125,84
126,77
124,34
124,4
120,48
118,54
117,66
116,97
120,11
119,16
116,9
116,11
114,98
113,65
115,82
117,59
118,57
118,07
114,98
114,04
115,02
114,28
115,04
116,7
119,21
118,39
116,5
115,46
117,59
117,33
116,2
116,83
118,99
118,62
121,09
122,4
123,76
125,33
123,23
122,52
123,64
124,67
124,71
122,53
124,4
125,45
125,35
124,3
127,03
128,51
128,1
128,94
129,67
129,87
131,12
132,68
132,24
133,63
129,91
127,93
131,17
130,86
133,48
134,08
136,02
132,8
132,37
133,05
132,57
130,7
130,5
129,67
127,8
126,82
126,85
128,28
128,3
126,82
125,08
128,53
130,34
131,52
132,59
131,17
132,72
133,36
132,82
132,9
130,9
129,41
128,67
129,28
130,91
131,06
130,84
131,41
133,22
132,06
132,48
134,38
135,22
134,89
136,09
136,33
136,32
137,48
136,53
136,8
138,03
137,39
137,55
136,08
134,78
133,28
133,57
134,84
133,02
133,49
133,77
134,34
134,5
134,03
135,51
136,53
135,95
134,32
132,44
133,61
131,02
130,05
128,21
129,03
130,34
131,57
132,63
132,06
134,44
134,1
132,49
134,23
134,92
135,61
134,53
133,86
133,89
135,33
135,86
136,22
137,38
137,31
136,89
138,01
136,72
135,77
137,52
135,61
132,94
134,12
132,55
134,11
134,19
135,57
135,05
134,32
133,61
134,75
133,1
133,26
131,63
132,47
132,45
133,33
133,57
134,13
133,92
132,62
132,3
133,26
132,6
134,38
134,17
135,46
135,09
134,96
133,85
132,59
131,15
130,91
131,07
130,78
129,95
131,41
131,21
130,68
130,46
131,12
132,99
133,02
133,39
134,07
135,6
135,66
135,53
135,82
136,9
137,97
138,09
136,91
134,76
135,13
134,66
132,95
132,25
134,3
134,3
134,76
134,81
134,51
135,11
134,32
133,51
134,02
132,76
133,39
132,05
131,87
133,03
132,57
132,1
130,7
129,2
129,77
131,02
131,55
133,17
133,08
133,24
130,74
129,91
130,03
131,13
129,55
130,22
130,61
129,27
129,68
130,1
130,83
130,95
131,73
131,86
132,44
132,35
133,16
133,62
132,54
132,69
133,5
133,36
134,23
132,41
133,02
132,88
130,76
130,33
129,79
128,65
129,14
127,35
127,74
126,31
125,95
126,36
126,15
125,6
126,2
126,73
125,68
122,49
122,07
123,4
123,01
123,03
122,33
122,42
122,68
124,69
123,3
124,17
124,38
123,19
122,16
120,66
120,92
120,67
120,68
121,1
120,86
121,48
123,48
121,72
123,16
123,84
124,57
124,3
124,22
124,43
123,33
122,86
121,25
122,16
122,62
123,44
124
124,75
124,8
125,93
126,28
126,04
125,04
123,76
125,34
126,99
126,34
127,42
126,18
125,3
123,5
125,32
124,65
124,03
125,11
125,46
124,7
124,48
124,76
125,81
124,95
123,66
122,66
119,34
117,84
120,97
117,38
118,06
116,99
115,55
114,17
115,32
112,49
111,93
112,08
111,63
109,53
111,35
110,79
113,06
112,62
110,65
112,36
113,74
111,73
109,86
109,32
109,99
109,84
111,13
112,43
111,77
112,15
112,89
112,12
113,1
111,09
110,76
109,59
109,99
110,25
108,31
108,79
108,14
109,88
109,93
110,46
109,56
111,49
111,85
111,35
110,95
112,49
113,11
112,54
112,84
111,5
111,52
111,57
112,48
112,31
113,79
114,01
113,64
112,62
113,27
113,51
112,92
113,66
113,14
113,48
113,23
110,56
109,5
109,78
109,49
109,66
109,93
109,82
108,54
108,23
106,19
106,49
107,15
107,74
107,54
107,07
107,54
107,81
108,38
108,42
106,86
106,41
106,46
106,84
107,69
107,04
111,04
111,93
111,98
112,07
112,05
113,14
112,49
113,2
113,52
113,22
113,85
113,68
114,26
114,1
114,8
114,98
115,1
114,21
114,24
113,35
114,23
114,43
114,28
113
113,16
112,59
113,65
113,18
113,21
113,11
112,78
112,57
111,87
111,94
113,18
113,67
115,15
114,41
112,88
112,44
113,48
112,78
112,59
113,31
113,21
112,5
113,72
114,09
113,97
112,5
111,28
111,35
110,92
110,73
109

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 11 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112270&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112270&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112270&T=0

As an alternative you can also use a QR Code:  
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 time11 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1126.081.049738062566082.47
2119.612.984040884438427.43
3117.4522.132995546174445.13
4116.742.014621552550254.91999999999999
5114.6720.4755207671595421
6117.2521.517422156158273.75
7117.3881.040826594587202.78999999999999
8122.242.564712459516666.70999999999999
9123.7540.9438379098129082.1900
10124.4061.173852631295772.92
11128.450.983742852578862.63999999999999
12131.9081.453089811401893.75999999999999
13130.672.016643250552755.54999999999998
14133.6641.459599260071073.65000000000001
15130.2481.73106036867584.77
16127.4140.7997999749937551.48000000000002
17129.6122.947400549636927.51
18132.5940.832934571259962.19000000000003
19129.8341.016823485173322.24000000000001
20131.7180.9580814161646172.38000000000000
21134.6121.344496188168643.61000000000001
22136.6920.4817364424662051.16000000000000
23136.7661.324435728904953.25
24133.640.7038110541899711.81999999999999
25134.430.6661456297237051.73999999999998
26134.571.678317609989244.09
27129.731.111193052534082.81
28132.961.259067114970442.87000000000000
29134.3561.163907212796623.12000000000000
30135.0321.102664953646402.35999999999999
31137.2620.5019661343158511.28999999999999
32135.1921.74277652038354.58000000000001
33134.2941.149556436196153.01999999999998
34133.8080.7053864189222821.65000000000001
35132.690.7767882594375411.94000000000000
36133.2460.794153637528651.82999999999998
37134.341.103970108290992.86000000000001
38132.6921.735546023590274.05000000000001
39130.8840.5702455611401151.46000000000001
40131.6541.256017515801432.56
41134.851.051308708229892.27000000000001
42137.1380.9279385755533642.27000000000001
43133.951.269113864079972.88000000000000
44134.5360.2435775030662660.509999999999991
45133.9440.879903403789312.35000000000002
46132.5820.6410304204949951.51999999999998
47130.5581.126552262436152.90000000000001
48132.3561.143385324376692.5
49130.1680.5906945064921421.57999999999998
50130.0980.643871105113441.56000000000000
51131.8660.5960956299118491.49000000000001
52133.1020.4784558495828051.08000000000001
53133.180.6788593374182881.81999999999999
54129.7340.8571639283124322.10999999999999
55126.7420.7624762291376661.78999999999999
56126.0720.4560372791779221.13000000000001
57122.80.5210566188045271.33000000000001
58123.0840.974489610001052.36
59122.9121.537195498302023.72
60120.8460.1793878479719250.429999999999993
61122.7361.067932582141782.36
62124.170.4880061475022631.23999999999999
63122.4660.8215716645551992.1900
64125.1520.9341145540028822.28
65125.4341.199449873900533.22999999999999
66125.7481.465168932239563.92
67124.9140.5814894668005571.42999999999999
68124.940.5144414446756791.33000000000000
69120.8942.372610376779135.81999999999999
70116.431.561649768674143.89
71112.691.502514558997683.69
72111.471.422234157936033.53
73111.6681.506741517314763.88000000000000
74110.5421.245098389686543.11000000000001
75112.4060.5629653630553111.33000000000000
76110.3360.5983142986758731.5
77109.010.8512637664085081.79000000000001
78110.9420.9264825956271362.28999999999999
79112.3860.8406723499675712.16000000000000
80111.8760.4782572529507560.980000000000004
81113.4660.544362011900171.39
82113.3420.3030181512715030.739999999999995
83110.5121.580686559694873.74000000000001
84109.2360.7903986336020551.70000000000000
85107.0220.6662356940302751.55000000000000
86107.8440.5726517266192441.35000000000001
87106.8520.5127084941757851.28
88110.8122.149225441874355.02999999999999
89112.880.5959446283003161.47
90113.8220.4038811706430501.04000000000001
91114.6660.4166293316606520.89
92113.8580.6398984294401761.43000000000001
93113.1580.3767890656587591.06000000000000
94112.4540.5374290650867321.23999999999999
95113.8580.9254026150816752.27000000000001
96112.920.4540374433898611.04000000000001
97113.4980.6522039558297711.59000000000000
98111.3560.6885709839951131.77000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 126.08 & 1.04973806256608 & 2.47 \tabularnewline
2 & 119.61 & 2.98404088443842 & 7.43 \tabularnewline
3 & 117.452 & 2.13299554617444 & 5.13 \tabularnewline
4 & 116.74 & 2.01462155255025 & 4.91999999999999 \tabularnewline
5 & 114.672 & 0.475520767159542 & 1 \tabularnewline
6 & 117.252 & 1.51742215615827 & 3.75 \tabularnewline
7 & 117.388 & 1.04082659458720 & 2.78999999999999 \tabularnewline
8 & 122.24 & 2.56471245951666 & 6.70999999999999 \tabularnewline
9 & 123.754 & 0.943837909812908 & 2.1900 \tabularnewline
10 & 124.406 & 1.17385263129577 & 2.92 \tabularnewline
11 & 128.45 & 0.98374285257886 & 2.63999999999999 \tabularnewline
12 & 131.908 & 1.45308981140189 & 3.75999999999999 \tabularnewline
13 & 130.67 & 2.01664325055275 & 5.54999999999998 \tabularnewline
14 & 133.664 & 1.45959926007107 & 3.65000000000001 \tabularnewline
15 & 130.248 & 1.7310603686758 & 4.77 \tabularnewline
16 & 127.414 & 0.799799974993755 & 1.48000000000002 \tabularnewline
17 & 129.612 & 2.94740054963692 & 7.51 \tabularnewline
18 & 132.594 & 0.83293457125996 & 2.19000000000003 \tabularnewline
19 & 129.834 & 1.01682348517332 & 2.24000000000001 \tabularnewline
20 & 131.718 & 0.958081416164617 & 2.38000000000000 \tabularnewline
21 & 134.612 & 1.34449618816864 & 3.61000000000001 \tabularnewline
22 & 136.692 & 0.481736442466205 & 1.16000000000000 \tabularnewline
23 & 136.766 & 1.32443572890495 & 3.25 \tabularnewline
24 & 133.64 & 0.703811054189971 & 1.81999999999999 \tabularnewline
25 & 134.43 & 0.666145629723705 & 1.73999999999998 \tabularnewline
26 & 134.57 & 1.67831760998924 & 4.09 \tabularnewline
27 & 129.73 & 1.11119305253408 & 2.81 \tabularnewline
28 & 132.96 & 1.25906711497044 & 2.87000000000000 \tabularnewline
29 & 134.356 & 1.16390721279662 & 3.12000000000000 \tabularnewline
30 & 135.032 & 1.10266495364640 & 2.35999999999999 \tabularnewline
31 & 137.262 & 0.501966134315851 & 1.28999999999999 \tabularnewline
32 & 135.192 & 1.7427765203835 & 4.58000000000001 \tabularnewline
33 & 134.294 & 1.14955643619615 & 3.01999999999998 \tabularnewline
34 & 133.808 & 0.705386418922282 & 1.65000000000001 \tabularnewline
35 & 132.69 & 0.776788259437541 & 1.94000000000000 \tabularnewline
36 & 133.246 & 0.79415363752865 & 1.82999999999998 \tabularnewline
37 & 134.34 & 1.10397010829099 & 2.86000000000001 \tabularnewline
38 & 132.692 & 1.73554602359027 & 4.05000000000001 \tabularnewline
39 & 130.884 & 0.570245561140115 & 1.46000000000001 \tabularnewline
40 & 131.654 & 1.25601751580143 & 2.56 \tabularnewline
41 & 134.85 & 1.05130870822989 & 2.27000000000001 \tabularnewline
42 & 137.138 & 0.927938575553364 & 2.27000000000001 \tabularnewline
43 & 133.95 & 1.26911386407997 & 2.88000000000000 \tabularnewline
44 & 134.536 & 0.243577503066266 & 0.509999999999991 \tabularnewline
45 & 133.944 & 0.87990340378931 & 2.35000000000002 \tabularnewline
46 & 132.582 & 0.641030420494995 & 1.51999999999998 \tabularnewline
47 & 130.558 & 1.12655226243615 & 2.90000000000001 \tabularnewline
48 & 132.356 & 1.14338532437669 & 2.5 \tabularnewline
49 & 130.168 & 0.590694506492142 & 1.57999999999998 \tabularnewline
50 & 130.098 & 0.64387110511344 & 1.56000000000000 \tabularnewline
51 & 131.866 & 0.596095629911849 & 1.49000000000001 \tabularnewline
52 & 133.102 & 0.478455849582805 & 1.08000000000001 \tabularnewline
53 & 133.18 & 0.678859337418288 & 1.81999999999999 \tabularnewline
54 & 129.734 & 0.857163928312432 & 2.10999999999999 \tabularnewline
55 & 126.742 & 0.762476229137666 & 1.78999999999999 \tabularnewline
56 & 126.072 & 0.456037279177922 & 1.13000000000001 \tabularnewline
57 & 122.8 & 0.521056618804527 & 1.33000000000001 \tabularnewline
58 & 123.084 & 0.97448961000105 & 2.36 \tabularnewline
59 & 122.912 & 1.53719549830202 & 3.72 \tabularnewline
60 & 120.846 & 0.179387847971925 & 0.429999999999993 \tabularnewline
61 & 122.736 & 1.06793258214178 & 2.36 \tabularnewline
62 & 124.17 & 0.488006147502263 & 1.23999999999999 \tabularnewline
63 & 122.466 & 0.821571664555199 & 2.1900 \tabularnewline
64 & 125.152 & 0.934114554002882 & 2.28 \tabularnewline
65 & 125.434 & 1.19944987390053 & 3.22999999999999 \tabularnewline
66 & 125.748 & 1.46516893223956 & 3.92 \tabularnewline
67 & 124.914 & 0.581489466800557 & 1.42999999999999 \tabularnewline
68 & 124.94 & 0.514441444675679 & 1.33000000000000 \tabularnewline
69 & 120.894 & 2.37261037677913 & 5.81999999999999 \tabularnewline
70 & 116.43 & 1.56164976867414 & 3.89 \tabularnewline
71 & 112.69 & 1.50251455899768 & 3.69 \tabularnewline
72 & 111.47 & 1.42223415793603 & 3.53 \tabularnewline
73 & 111.668 & 1.50674151731476 & 3.88000000000000 \tabularnewline
74 & 110.542 & 1.24509838968654 & 3.11000000000001 \tabularnewline
75 & 112.406 & 0.562965363055311 & 1.33000000000000 \tabularnewline
76 & 110.336 & 0.598314298675873 & 1.5 \tabularnewline
77 & 109.01 & 0.851263766408508 & 1.79000000000001 \tabularnewline
78 & 110.942 & 0.926482595627136 & 2.28999999999999 \tabularnewline
79 & 112.386 & 0.840672349967571 & 2.16000000000000 \tabularnewline
80 & 111.876 & 0.478257252950756 & 0.980000000000004 \tabularnewline
81 & 113.466 & 0.54436201190017 & 1.39 \tabularnewline
82 & 113.342 & 0.303018151271503 & 0.739999999999995 \tabularnewline
83 & 110.512 & 1.58068655969487 & 3.74000000000001 \tabularnewline
84 & 109.236 & 0.790398633602055 & 1.70000000000000 \tabularnewline
85 & 107.022 & 0.666235694030275 & 1.55000000000000 \tabularnewline
86 & 107.844 & 0.572651726619244 & 1.35000000000001 \tabularnewline
87 & 106.852 & 0.512708494175785 & 1.28 \tabularnewline
88 & 110.812 & 2.14922544187435 & 5.02999999999999 \tabularnewline
89 & 112.88 & 0.595944628300316 & 1.47 \tabularnewline
90 & 113.822 & 0.403881170643050 & 1.04000000000001 \tabularnewline
91 & 114.666 & 0.416629331660652 & 0.89 \tabularnewline
92 & 113.858 & 0.639898429440176 & 1.43000000000001 \tabularnewline
93 & 113.158 & 0.376789065658759 & 1.06000000000000 \tabularnewline
94 & 112.454 & 0.537429065086732 & 1.23999999999999 \tabularnewline
95 & 113.858 & 0.925402615081675 & 2.27000000000001 \tabularnewline
96 & 112.92 & 0.454037443389861 & 1.04000000000001 \tabularnewline
97 & 113.498 & 0.652203955829771 & 1.59000000000000 \tabularnewline
98 & 111.356 & 0.688570983995113 & 1.77000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112270&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]126.08[/C][C]1.04973806256608[/C][C]2.47[/C][/ROW]
[ROW][C]2[/C][C]119.61[/C][C]2.98404088443842[/C][C]7.43[/C][/ROW]
[ROW][C]3[/C][C]117.452[/C][C]2.13299554617444[/C][C]5.13[/C][/ROW]
[ROW][C]4[/C][C]116.74[/C][C]2.01462155255025[/C][C]4.91999999999999[/C][/ROW]
[ROW][C]5[/C][C]114.672[/C][C]0.475520767159542[/C][C]1[/C][/ROW]
[ROW][C]6[/C][C]117.252[/C][C]1.51742215615827[/C][C]3.75[/C][/ROW]
[ROW][C]7[/C][C]117.388[/C][C]1.04082659458720[/C][C]2.78999999999999[/C][/ROW]
[ROW][C]8[/C][C]122.24[/C][C]2.56471245951666[/C][C]6.70999999999999[/C][/ROW]
[ROW][C]9[/C][C]123.754[/C][C]0.943837909812908[/C][C]2.1900[/C][/ROW]
[ROW][C]10[/C][C]124.406[/C][C]1.17385263129577[/C][C]2.92[/C][/ROW]
[ROW][C]11[/C][C]128.45[/C][C]0.98374285257886[/C][C]2.63999999999999[/C][/ROW]
[ROW][C]12[/C][C]131.908[/C][C]1.45308981140189[/C][C]3.75999999999999[/C][/ROW]
[ROW][C]13[/C][C]130.67[/C][C]2.01664325055275[/C][C]5.54999999999998[/C][/ROW]
[ROW][C]14[/C][C]133.664[/C][C]1.45959926007107[/C][C]3.65000000000001[/C][/ROW]
[ROW][C]15[/C][C]130.248[/C][C]1.7310603686758[/C][C]4.77[/C][/ROW]
[ROW][C]16[/C][C]127.414[/C][C]0.799799974993755[/C][C]1.48000000000002[/C][/ROW]
[ROW][C]17[/C][C]129.612[/C][C]2.94740054963692[/C][C]7.51[/C][/ROW]
[ROW][C]18[/C][C]132.594[/C][C]0.83293457125996[/C][C]2.19000000000003[/C][/ROW]
[ROW][C]19[/C][C]129.834[/C][C]1.01682348517332[/C][C]2.24000000000001[/C][/ROW]
[ROW][C]20[/C][C]131.718[/C][C]0.958081416164617[/C][C]2.38000000000000[/C][/ROW]
[ROW][C]21[/C][C]134.612[/C][C]1.34449618816864[/C][C]3.61000000000001[/C][/ROW]
[ROW][C]22[/C][C]136.692[/C][C]0.481736442466205[/C][C]1.16000000000000[/C][/ROW]
[ROW][C]23[/C][C]136.766[/C][C]1.32443572890495[/C][C]3.25[/C][/ROW]
[ROW][C]24[/C][C]133.64[/C][C]0.703811054189971[/C][C]1.81999999999999[/C][/ROW]
[ROW][C]25[/C][C]134.43[/C][C]0.666145629723705[/C][C]1.73999999999998[/C][/ROW]
[ROW][C]26[/C][C]134.57[/C][C]1.67831760998924[/C][C]4.09[/C][/ROW]
[ROW][C]27[/C][C]129.73[/C][C]1.11119305253408[/C][C]2.81[/C][/ROW]
[ROW][C]28[/C][C]132.96[/C][C]1.25906711497044[/C][C]2.87000000000000[/C][/ROW]
[ROW][C]29[/C][C]134.356[/C][C]1.16390721279662[/C][C]3.12000000000000[/C][/ROW]
[ROW][C]30[/C][C]135.032[/C][C]1.10266495364640[/C][C]2.35999999999999[/C][/ROW]
[ROW][C]31[/C][C]137.262[/C][C]0.501966134315851[/C][C]1.28999999999999[/C][/ROW]
[ROW][C]32[/C][C]135.192[/C][C]1.7427765203835[/C][C]4.58000000000001[/C][/ROW]
[ROW][C]33[/C][C]134.294[/C][C]1.14955643619615[/C][C]3.01999999999998[/C][/ROW]
[ROW][C]34[/C][C]133.808[/C][C]0.705386418922282[/C][C]1.65000000000001[/C][/ROW]
[ROW][C]35[/C][C]132.69[/C][C]0.776788259437541[/C][C]1.94000000000000[/C][/ROW]
[ROW][C]36[/C][C]133.246[/C][C]0.79415363752865[/C][C]1.82999999999998[/C][/ROW]
[ROW][C]37[/C][C]134.34[/C][C]1.10397010829099[/C][C]2.86000000000001[/C][/ROW]
[ROW][C]38[/C][C]132.692[/C][C]1.73554602359027[/C][C]4.05000000000001[/C][/ROW]
[ROW][C]39[/C][C]130.884[/C][C]0.570245561140115[/C][C]1.46000000000001[/C][/ROW]
[ROW][C]40[/C][C]131.654[/C][C]1.25601751580143[/C][C]2.56[/C][/ROW]
[ROW][C]41[/C][C]134.85[/C][C]1.05130870822989[/C][C]2.27000000000001[/C][/ROW]
[ROW][C]42[/C][C]137.138[/C][C]0.927938575553364[/C][C]2.27000000000001[/C][/ROW]
[ROW][C]43[/C][C]133.95[/C][C]1.26911386407997[/C][C]2.88000000000000[/C][/ROW]
[ROW][C]44[/C][C]134.536[/C][C]0.243577503066266[/C][C]0.509999999999991[/C][/ROW]
[ROW][C]45[/C][C]133.944[/C][C]0.87990340378931[/C][C]2.35000000000002[/C][/ROW]
[ROW][C]46[/C][C]132.582[/C][C]0.641030420494995[/C][C]1.51999999999998[/C][/ROW]
[ROW][C]47[/C][C]130.558[/C][C]1.12655226243615[/C][C]2.90000000000001[/C][/ROW]
[ROW][C]48[/C][C]132.356[/C][C]1.14338532437669[/C][C]2.5[/C][/ROW]
[ROW][C]49[/C][C]130.168[/C][C]0.590694506492142[/C][C]1.57999999999998[/C][/ROW]
[ROW][C]50[/C][C]130.098[/C][C]0.64387110511344[/C][C]1.56000000000000[/C][/ROW]
[ROW][C]51[/C][C]131.866[/C][C]0.596095629911849[/C][C]1.49000000000001[/C][/ROW]
[ROW][C]52[/C][C]133.102[/C][C]0.478455849582805[/C][C]1.08000000000001[/C][/ROW]
[ROW][C]53[/C][C]133.18[/C][C]0.678859337418288[/C][C]1.81999999999999[/C][/ROW]
[ROW][C]54[/C][C]129.734[/C][C]0.857163928312432[/C][C]2.10999999999999[/C][/ROW]
[ROW][C]55[/C][C]126.742[/C][C]0.762476229137666[/C][C]1.78999999999999[/C][/ROW]
[ROW][C]56[/C][C]126.072[/C][C]0.456037279177922[/C][C]1.13000000000001[/C][/ROW]
[ROW][C]57[/C][C]122.8[/C][C]0.521056618804527[/C][C]1.33000000000001[/C][/ROW]
[ROW][C]58[/C][C]123.084[/C][C]0.97448961000105[/C][C]2.36[/C][/ROW]
[ROW][C]59[/C][C]122.912[/C][C]1.53719549830202[/C][C]3.72[/C][/ROW]
[ROW][C]60[/C][C]120.846[/C][C]0.179387847971925[/C][C]0.429999999999993[/C][/ROW]
[ROW][C]61[/C][C]122.736[/C][C]1.06793258214178[/C][C]2.36[/C][/ROW]
[ROW][C]62[/C][C]124.17[/C][C]0.488006147502263[/C][C]1.23999999999999[/C][/ROW]
[ROW][C]63[/C][C]122.466[/C][C]0.821571664555199[/C][C]2.1900[/C][/ROW]
[ROW][C]64[/C][C]125.152[/C][C]0.934114554002882[/C][C]2.28[/C][/ROW]
[ROW][C]65[/C][C]125.434[/C][C]1.19944987390053[/C][C]3.22999999999999[/C][/ROW]
[ROW][C]66[/C][C]125.748[/C][C]1.46516893223956[/C][C]3.92[/C][/ROW]
[ROW][C]67[/C][C]124.914[/C][C]0.581489466800557[/C][C]1.42999999999999[/C][/ROW]
[ROW][C]68[/C][C]124.94[/C][C]0.514441444675679[/C][C]1.33000000000000[/C][/ROW]
[ROW][C]69[/C][C]120.894[/C][C]2.37261037677913[/C][C]5.81999999999999[/C][/ROW]
[ROW][C]70[/C][C]116.43[/C][C]1.56164976867414[/C][C]3.89[/C][/ROW]
[ROW][C]71[/C][C]112.69[/C][C]1.50251455899768[/C][C]3.69[/C][/ROW]
[ROW][C]72[/C][C]111.47[/C][C]1.42223415793603[/C][C]3.53[/C][/ROW]
[ROW][C]73[/C][C]111.668[/C][C]1.50674151731476[/C][C]3.88000000000000[/C][/ROW]
[ROW][C]74[/C][C]110.542[/C][C]1.24509838968654[/C][C]3.11000000000001[/C][/ROW]
[ROW][C]75[/C][C]112.406[/C][C]0.562965363055311[/C][C]1.33000000000000[/C][/ROW]
[ROW][C]76[/C][C]110.336[/C][C]0.598314298675873[/C][C]1.5[/C][/ROW]
[ROW][C]77[/C][C]109.01[/C][C]0.851263766408508[/C][C]1.79000000000001[/C][/ROW]
[ROW][C]78[/C][C]110.942[/C][C]0.926482595627136[/C][C]2.28999999999999[/C][/ROW]
[ROW][C]79[/C][C]112.386[/C][C]0.840672349967571[/C][C]2.16000000000000[/C][/ROW]
[ROW][C]80[/C][C]111.876[/C][C]0.478257252950756[/C][C]0.980000000000004[/C][/ROW]
[ROW][C]81[/C][C]113.466[/C][C]0.54436201190017[/C][C]1.39[/C][/ROW]
[ROW][C]82[/C][C]113.342[/C][C]0.303018151271503[/C][C]0.739999999999995[/C][/ROW]
[ROW][C]83[/C][C]110.512[/C][C]1.58068655969487[/C][C]3.74000000000001[/C][/ROW]
[ROW][C]84[/C][C]109.236[/C][C]0.790398633602055[/C][C]1.70000000000000[/C][/ROW]
[ROW][C]85[/C][C]107.022[/C][C]0.666235694030275[/C][C]1.55000000000000[/C][/ROW]
[ROW][C]86[/C][C]107.844[/C][C]0.572651726619244[/C][C]1.35000000000001[/C][/ROW]
[ROW][C]87[/C][C]106.852[/C][C]0.512708494175785[/C][C]1.28[/C][/ROW]
[ROW][C]88[/C][C]110.812[/C][C]2.14922544187435[/C][C]5.02999999999999[/C][/ROW]
[ROW][C]89[/C][C]112.88[/C][C]0.595944628300316[/C][C]1.47[/C][/ROW]
[ROW][C]90[/C][C]113.822[/C][C]0.403881170643050[/C][C]1.04000000000001[/C][/ROW]
[ROW][C]91[/C][C]114.666[/C][C]0.416629331660652[/C][C]0.89[/C][/ROW]
[ROW][C]92[/C][C]113.858[/C][C]0.639898429440176[/C][C]1.43000000000001[/C][/ROW]
[ROW][C]93[/C][C]113.158[/C][C]0.376789065658759[/C][C]1.06000000000000[/C][/ROW]
[ROW][C]94[/C][C]112.454[/C][C]0.537429065086732[/C][C]1.23999999999999[/C][/ROW]
[ROW][C]95[/C][C]113.858[/C][C]0.925402615081675[/C][C]2.27000000000001[/C][/ROW]
[ROW][C]96[/C][C]112.92[/C][C]0.454037443389861[/C][C]1.04000000000001[/C][/ROW]
[ROW][C]97[/C][C]113.498[/C][C]0.652203955829771[/C][C]1.59000000000000[/C][/ROW]
[ROW][C]98[/C][C]111.356[/C][C]0.688570983995113[/C][C]1.77000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112270&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112270&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1126.081.049738062566082.47
2119.612.984040884438427.43
3117.4522.132995546174445.13
4116.742.014621552550254.91999999999999
5114.6720.4755207671595421
6117.2521.517422156158273.75
7117.3881.040826594587202.78999999999999
8122.242.564712459516666.70999999999999
9123.7540.9438379098129082.1900
10124.4061.173852631295772.92
11128.450.983742852578862.63999999999999
12131.9081.453089811401893.75999999999999
13130.672.016643250552755.54999999999998
14133.6641.459599260071073.65000000000001
15130.2481.73106036867584.77
16127.4140.7997999749937551.48000000000002
17129.6122.947400549636927.51
18132.5940.832934571259962.19000000000003
19129.8341.016823485173322.24000000000001
20131.7180.9580814161646172.38000000000000
21134.6121.344496188168643.61000000000001
22136.6920.4817364424662051.16000000000000
23136.7661.324435728904953.25
24133.640.7038110541899711.81999999999999
25134.430.6661456297237051.73999999999998
26134.571.678317609989244.09
27129.731.111193052534082.81
28132.961.259067114970442.87000000000000
29134.3561.163907212796623.12000000000000
30135.0321.102664953646402.35999999999999
31137.2620.5019661343158511.28999999999999
32135.1921.74277652038354.58000000000001
33134.2941.149556436196153.01999999999998
34133.8080.7053864189222821.65000000000001
35132.690.7767882594375411.94000000000000
36133.2460.794153637528651.82999999999998
37134.341.103970108290992.86000000000001
38132.6921.735546023590274.05000000000001
39130.8840.5702455611401151.46000000000001
40131.6541.256017515801432.56
41134.851.051308708229892.27000000000001
42137.1380.9279385755533642.27000000000001
43133.951.269113864079972.88000000000000
44134.5360.2435775030662660.509999999999991
45133.9440.879903403789312.35000000000002
46132.5820.6410304204949951.51999999999998
47130.5581.126552262436152.90000000000001
48132.3561.143385324376692.5
49130.1680.5906945064921421.57999999999998
50130.0980.643871105113441.56000000000000
51131.8660.5960956299118491.49000000000001
52133.1020.4784558495828051.08000000000001
53133.180.6788593374182881.81999999999999
54129.7340.8571639283124322.10999999999999
55126.7420.7624762291376661.78999999999999
56126.0720.4560372791779221.13000000000001
57122.80.5210566188045271.33000000000001
58123.0840.974489610001052.36
59122.9121.537195498302023.72
60120.8460.1793878479719250.429999999999993
61122.7361.067932582141782.36
62124.170.4880061475022631.23999999999999
63122.4660.8215716645551992.1900
64125.1520.9341145540028822.28
65125.4341.199449873900533.22999999999999
66125.7481.465168932239563.92
67124.9140.5814894668005571.42999999999999
68124.940.5144414446756791.33000000000000
69120.8942.372610376779135.81999999999999
70116.431.561649768674143.89
71112.691.502514558997683.69
72111.471.422234157936033.53
73111.6681.506741517314763.88000000000000
74110.5421.245098389686543.11000000000001
75112.4060.5629653630553111.33000000000000
76110.3360.5983142986758731.5
77109.010.8512637664085081.79000000000001
78110.9420.9264825956271362.28999999999999
79112.3860.8406723499675712.16000000000000
80111.8760.4782572529507560.980000000000004
81113.4660.544362011900171.39
82113.3420.3030181512715030.739999999999995
83110.5121.580686559694873.74000000000001
84109.2360.7903986336020551.70000000000000
85107.0220.6662356940302751.55000000000000
86107.8440.5726517266192441.35000000000001
87106.8520.5127084941757851.28
88110.8122.149225441874355.02999999999999
89112.880.5959446283003161.47
90113.8220.4038811706430501.04000000000001
91114.6660.4166293316606520.89
92113.8580.6398984294401761.43000000000001
93113.1580.3767890656587591.06000000000000
94112.4540.5374290650867321.23999999999999
95113.8580.9254026150816752.27000000000001
96112.920.4540374433898611.04000000000001
97113.4980.6522039558297711.59000000000000
98111.3560.6885709839951131.77000000000000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.39503392231562
beta0.00509479226336126
S.D.0.00615492106038591
T-STAT0.827759156190024
p-value0.409859921355814

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.39503392231562 \tabularnewline
beta & 0.00509479226336126 \tabularnewline
S.D. & 0.00615492106038591 \tabularnewline
T-STAT & 0.827759156190024 \tabularnewline
p-value & 0.409859921355814 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112270&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.39503392231562[/C][/ROW]
[ROW][C]beta[/C][C]0.00509479226336126[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00615492106038591[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.827759156190024[/C][/ROW]
[ROW][C]p-value[/C][C]0.409859921355814[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112270&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112270&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.39503392231562
beta0.00509479226336126
S.D.0.00615492106038591
T-STAT0.827759156190024
p-value0.409859921355814






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.98853624860361
beta1.01199045231827
S.D.0.711076172882997
T-STAT1.42318149715978
p-value0.157925288958149
Lambda-0.0119904523182686

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.98853624860361 \tabularnewline
beta & 1.01199045231827 \tabularnewline
S.D. & 0.711076172882997 \tabularnewline
T-STAT & 1.42318149715978 \tabularnewline
p-value & 0.157925288958149 \tabularnewline
Lambda & -0.0119904523182686 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112270&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.98853624860361[/C][/ROW]
[ROW][C]beta[/C][C]1.01199045231827[/C][/ROW]
[ROW][C]S.D.[/C][C]0.711076172882997[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.42318149715978[/C][/ROW]
[ROW][C]p-value[/C][C]0.157925288958149[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0119904523182686[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112270&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112270&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.98853624860361
beta1.01199045231827
S.D.0.711076172882997
T-STAT1.42318149715978
p-value0.157925288958149
Lambda-0.0119904523182686


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
R code (references can be found in the software module):
par1 <- 5
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')