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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 07 Dec 2010 19:46:09 +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/07/t12917511951bsfh5uh11t6t11.htm/, Retrieved Fri, 03 May 2024 20:16:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106687, Retrieved Fri, 03 May 2024 20:16:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact105

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [detailhandelverko...] [2010-12-07 19:46:09] [d83d17ce80f1d5ae1d2c83db1cba10f4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
75.9
76.9
77.9
78.9
79.9
80.9
81.9
82.9
83.9
84.9
85.9
86.9
87.9
88.9
89.9
90.9
91.9
92.9
93.9
94.9
95.9
96.9
97.9
98.9
99.9
100.9
101.9
102.9
103.9
104.9
105.9
106.9
107.9
108.9
109.9
110.9
111.9
112.9
113.9
114.9
115.9
116.9
117.9
118.9
119.9
120.9
121.9
122.9
123.9
124.9
125.9
126.9
127.9
128.9
129.9
130.9
131.9
132.9
133.9
134.9
135.9
136.9
137.9
138.9
139.9
140.9
141.9
142.9
143.9
144.9
145.9
146.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106687&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106687&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106687&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
177.41.290994448735813
281.41.290994448735813
385.41.290994448735813
489.41.290994448735813
593.41.290994448735813
697.41.290994448735813
7101.41.290994448735813
8105.41.290994448735813
9109.41.290994448735813
10113.41.290994448735813
11117.41.290994448735813
12121.41.290994448735813
13125.41.290994448735813
14129.41.290994448735813
15133.41.290994448735813
16137.41.290994448735813
17141.41.290994448735813
18145.41.290994448735813

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 77.4 & 1.29099444873581 & 3 \tabularnewline
2 & 81.4 & 1.29099444873581 & 3 \tabularnewline
3 & 85.4 & 1.29099444873581 & 3 \tabularnewline
4 & 89.4 & 1.29099444873581 & 3 \tabularnewline
5 & 93.4 & 1.29099444873581 & 3 \tabularnewline
6 & 97.4 & 1.29099444873581 & 3 \tabularnewline
7 & 101.4 & 1.29099444873581 & 3 \tabularnewline
8 & 105.4 & 1.29099444873581 & 3 \tabularnewline
9 & 109.4 & 1.29099444873581 & 3 \tabularnewline
10 & 113.4 & 1.29099444873581 & 3 \tabularnewline
11 & 117.4 & 1.29099444873581 & 3 \tabularnewline
12 & 121.4 & 1.29099444873581 & 3 \tabularnewline
13 & 125.4 & 1.29099444873581 & 3 \tabularnewline
14 & 129.4 & 1.29099444873581 & 3 \tabularnewline
15 & 133.4 & 1.29099444873581 & 3 \tabularnewline
16 & 137.4 & 1.29099444873581 & 3 \tabularnewline
17 & 141.4 & 1.29099444873581 & 3 \tabularnewline
18 & 145.4 & 1.29099444873581 & 3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106687&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]77.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]2[/C][C]81.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]3[/C][C]85.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]4[/C][C]89.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]5[/C][C]93.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]6[/C][C]97.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]7[/C][C]101.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]8[/C][C]105.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]9[/C][C]109.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]10[/C][C]113.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]11[/C][C]117.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]12[/C][C]121.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]13[/C][C]125.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]14[/C][C]129.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]15[/C][C]133.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]16[/C][C]137.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]17[/C][C]141.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]18[/C][C]145.4[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106687&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106687&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
177.41.290994448735813
281.41.290994448735813
385.41.290994448735813
489.41.290994448735813
593.41.290994448735813
697.41.290994448735813
7101.41.290994448735813
8105.41.290994448735813
9109.41.290994448735813
10113.41.290994448735813
11117.41.290994448735813
12121.41.290994448735813
13125.41.290994448735813
14129.41.290994448735813
15133.41.290994448735813
16137.41.290994448735813
17141.41.290994448735813
18145.41.290994448735813






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.29099444873581
beta-1.23954667790824e-17
S.D.7.15652608163432e-18
T-STAT-1.73205080756887
p-value0.102494766923602

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.29099444873581 \tabularnewline
beta & -1.23954667790824e-17 \tabularnewline
S.D. & 7.15652608163432e-18 \tabularnewline
T-STAT & -1.73205080756887 \tabularnewline
p-value & 0.102494766923602 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106687&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.29099444873581[/C][/ROW]
[ROW][C]beta[/C][C]-1.23954667790824e-17[/C][/ROW]
[ROW][C]S.D.[/C][C]7.15652608163432e-18[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.73205080756887[/C][/ROW]
[ROW][C]p-value[/C][C]0.102494766923602[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106687&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106687&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)
alpha1.29099444873581
beta-1.23954667790824e-17
S.D.7.15652608163432e-18
T-STAT-1.73205080756887
p-value0.102494766923602






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.255412811882995
beta0
S.D.0
T-STATNaN
p-valueNaN
Lambda1

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.255412811882995 \tabularnewline
beta & 0 \tabularnewline
S.D. & 0 \tabularnewline
T-STAT & NaN \tabularnewline
p-value & NaN \tabularnewline
Lambda & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106687&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.255412811882995[/C][/ROW]
[ROW][C]beta[/C][C]0[/C][/ROW]
[ROW][C]S.D.[/C][C]0[/C][/ROW]
[ROW][C]T-STAT[/C][C]NaN[/C][/ROW]
[ROW][C]p-value[/C][C]NaN[/C][/ROW]
[ROW][C]Lambda[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106687&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106687&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)
alpha0.255412811882995
beta0
S.D.0
T-STATNaN
p-valueNaN
Lambda1


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 <- as.numeric(par1)
(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')