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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 computationThu, 04 Dec 2008 10:58:37 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/04/t1228413604rm99j5qc3x0c0sc.htm/, Retrieved Sun, 19 May 2024 06:06:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28986, Retrieved Sun, 19 May 2024 06:06:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167

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] [Standard Deviatio...] [2008-12-04 17:58:37] [b72e060d4eaf5aae1831b15bc791ef7e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.8
105.3
116.1
112.8
114.5
117.2
77.1
80.1
120.3
133.4
109.4
93.2
91.2
99.2
108.2
101.5
106.9
104.4
77.9
60
99.5
95
105.6
102.5
93.3
97.3
127
111.7
96.4
133
72.2
95.8
124.1
127.6
110.7
104.6
112.7
115.3
139.4
119
97.4
154
81.5
88.8
127.7
105.1
114.9
106.4
104.5
121.6
141.4
99
126.7
134.1
81.3
88.6
132.7
132.9
134.4
103.7
119.7
115
132.9
108.5
113.9
142
97.7
92.2
128.8
134.9
128.2
114.8
117.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28986&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28986&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28986&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1106.68333333333316.526938523807056.3
295.991666666666714.055116074895648.2
3107.80833333333317.982539932507960.8
4113.51666666666720.367212213097172.5
5116.74166666666720.321214098184360.1
6119.0515.069505632236249.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 106.683333333333 & 16.5269385238070 & 56.3 \tabularnewline
2 & 95.9916666666667 & 14.0551160748956 & 48.2 \tabularnewline
3 & 107.808333333333 & 17.9825399325079 & 60.8 \tabularnewline
4 & 113.516666666667 & 20.3672122130971 & 72.5 \tabularnewline
5 & 116.741666666667 & 20.3212140981843 & 60.1 \tabularnewline
6 & 119.05 & 15.0695056322362 & 49.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28986&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]106.683333333333[/C][C]16.5269385238070[/C][C]56.3[/C][/ROW]
[ROW][C]2[/C][C]95.9916666666667[/C][C]14.0551160748956[/C][C]48.2[/C][/ROW]
[ROW][C]3[/C][C]107.808333333333[/C][C]17.9825399325079[/C][C]60.8[/C][/ROW]
[ROW][C]4[/C][C]113.516666666667[/C][C]20.3672122130971[/C][C]72.5[/C][/ROW]
[ROW][C]5[/C][C]116.741666666667[/C][C]20.3212140981843[/C][C]60.1[/C][/ROW]
[ROW][C]6[/C][C]119.05[/C][C]15.0695056322362[/C][C]49.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28986&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28986&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
1106.68333333333316.526938523807056.3
295.991666666666714.055116074895648.2
3107.80833333333317.982539932507960.8
4113.51666666666720.367212213097172.5
5116.74166666666720.321214098184360.1
6119.0515.069505632236249.8






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.591932713896937
beta0.163497249522869
S.D.0.135033208749154
T-STAT1.21079289337330
p-value0.292620902968245

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.591932713896937 \tabularnewline
beta & 0.163497249522869 \tabularnewline
S.D. & 0.135033208749154 \tabularnewline
T-STAT & 1.21079289337330 \tabularnewline
p-value & 0.292620902968245 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28986&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.591932713896937[/C][/ROW]
[ROW][C]beta[/C][C]0.163497249522869[/C][/ROW]
[ROW][C]S.D.[/C][C]0.135033208749154[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.21079289337330[/C][/ROW]
[ROW][C]p-value[/C][C]0.292620902968245[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28986&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28986&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)
alpha-0.591932713896937
beta0.163497249522869
S.D.0.135033208749154
T-STAT1.21079289337330
p-value0.292620902968245






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.15895196342776
beta1.06540204932714
S.D.0.82521648329859
T-STAT1.29105764473883
p-value0.266244786852219
Lambda-0.0654020493271392

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.15895196342776 \tabularnewline
beta & 1.06540204932714 \tabularnewline
S.D. & 0.82521648329859 \tabularnewline
T-STAT & 1.29105764473883 \tabularnewline
p-value & 0.266244786852219 \tabularnewline
Lambda & -0.0654020493271392 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28986&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.15895196342776[/C][/ROW]
[ROW][C]beta[/C][C]1.06540204932714[/C][/ROW]
[ROW][C]S.D.[/C][C]0.82521648329859[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.29105764473883[/C][/ROW]
[ROW][C]p-value[/C][C]0.266244786852219[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0654020493271392[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28986&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28986&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-2.15895196342776
beta1.06540204932714
S.D.0.82521648329859
T-STAT1.29105764473883
p-value0.266244786852219
Lambda-0.0654020493271392


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
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')