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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, 20 May 2008 12:25:25 -0600
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/May/20/t1211308009prnus9tx7qd3g2h.htm/, Retrieved Tue, 14 May 2024 14:29:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12968, Retrieved Tue, 14 May 2024 14:29:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact229

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 deviatoi...] [2008-05-20 18:25:25] [2d679ee92688abc2a19dfb46633cb8da] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
113000
110000
107000
103000
98000
98000
137000
148000
147000
139000
130000
128000
127000
123000
118000
114000
108000
111000
151000
159000
158000
148000
138000
137000
136000
133000
126000
120000
114000
116000
153000
162000
161000
149000
139000
135000
130000
127000
122000
117000
112000
113000
149000
157000
157000
147000
137000
132000
125000
123000
117000
114000
111000
112000
144000
150000
149000
134000
123000
116000
117000
111000
105000
102000
95000
93000
124000
130000
124000
115000
106000
105000

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=12968&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=12968&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12968&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
112150018768.929838238750000
2132666.66666666718391.368199305551000
313700016530.96268439148000
4133333.33333333316188.286075449945000
512650014317.821063276439000
6110583.33333333311704.376285920837000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 121500 & 18768.9298382387 & 50000 \tabularnewline
2 & 132666.666666667 & 18391.3681993055 & 51000 \tabularnewline
3 & 137000 & 16530.962684391 & 48000 \tabularnewline
4 & 133333.333333333 & 16188.2860754499 & 45000 \tabularnewline
5 & 126500 & 14317.8210632764 & 39000 \tabularnewline
6 & 110583.333333333 & 11704.3762859208 & 37000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12968&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]121500[/C][C]18768.9298382387[/C][C]50000[/C][/ROW]
[ROW][C]2[/C][C]132666.666666667[/C][C]18391.3681993055[/C][C]51000[/C][/ROW]
[ROW][C]3[/C][C]137000[/C][C]16530.962684391[/C][C]48000[/C][/ROW]
[ROW][C]4[/C][C]133333.333333333[/C][C]16188.2860754499[/C][C]45000[/C][/ROW]
[ROW][C]5[/C][C]126500[/C][C]14317.8210632764[/C][C]39000[/C][/ROW]
[ROW][C]6[/C][C]110583.333333333[/C][C]11704.3762859208[/C][C]37000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12968&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12968&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
112150018768.929838238750000
2132666.66666666718391.368199305551000
313700016530.96268439148000
4133333.33333333316188.286075449945000
512650014317.821063276439000
6110583.33333333311704.376285920837000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-4493.572607789
beta0.161325982877754
S.D.0.109613019828151
T-STAT1.47177756009896
p-value0.215054518047368

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4493.572607789 \tabularnewline
beta & 0.161325982877754 \tabularnewline
S.D. & 0.109613019828151 \tabularnewline
T-STAT & 1.47177756009896 \tabularnewline
p-value & 0.215054518047368 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12968&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4493.572607789[/C][/ROW]
[ROW][C]beta[/C][C]0.161325982877754[/C][/ROW]
[ROW][C]S.D.[/C][C]0.109613019828151[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.47177756009896[/C][/ROW]
[ROW][C]p-value[/C][C]0.215054518047368[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12968&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12968&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-4493.572607789
beta0.161325982877754
S.D.0.109613019828151
T-STAT1.47177756009896
p-value0.215054518047368






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-7.53157409421959
beta1.46384549222123
S.D.0.843228146359444
T-STAT1.73600169603119
p-value0.157572798180596
Lambda-0.463845492221231

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.53157409421959 \tabularnewline
beta & 1.46384549222123 \tabularnewline
S.D. & 0.843228146359444 \tabularnewline
T-STAT & 1.73600169603119 \tabularnewline
p-value & 0.157572798180596 \tabularnewline
Lambda & -0.463845492221231 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12968&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.53157409421959[/C][/ROW]
[ROW][C]beta[/C][C]1.46384549222123[/C][/ROW]
[ROW][C]S.D.[/C][C]0.843228146359444[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.73600169603119[/C][/ROW]
[ROW][C]p-value[/C][C]0.157572798180596[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.463845492221231[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12968&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12968&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-7.53157409421959
beta1.46384549222123
S.D.0.843228146359444
T-STAT1.73600169603119
p-value0.157572798180596
Lambda-0.463845492221231


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')