Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 27 Nov 2007 03:04:58 -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/2007/Nov/27/t1196157372oi9iavzcbomek18.htm/, Retrieved Sun, 05 May 2024 15:30:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6790, Retrieved Sun, 05 May 2024 15:30:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Totale industriël...] [2007-11-27 10:04:58] [757ef2b8266f339cc1cb96dcaefa4cf0] [Current]
Feedback Forum

Post a new message
Dataseries X:
115,9
103,9
91,9
117,2
109,3
106,1
118,8
105,3
106,0
102,0
112,9
116,5
114,8
100,5
85,4
114,6
109,9
100,7
115,5
100,7
99,0
102,3
108,8
105,9
113,2
95,7
80,9
113,9
98,1
102,8
104,7
95,9
94,6
101,6
103,9
110,3
114,1
96,8
87,4
111,4
97,4
102,9
112,7
97,0
95,1
96,9
98,6
111,7
109,8
89,9
87,4
104,5
98,1
102,7
105,4
97,0
97,4
92,0
101,7
112,6
106,9
92,1
86,0
104,7
102,0
103,1
106,0
96,1
96,2
90,7
102,3
109,4
101,0
94,7
81,0
106,2
101,9
96,4
110,4
100,5
98,8




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6790&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6790&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1108.8166666666677.865671483019611.9
2104.8416666666678.6449626250134125.6
3101.39.213823606654633
4101.8333333333338.609543682695539.6
599.8757.7362341085193515.2
699.6257.297711347339728.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 108.816666666667 & 7.8656714830196 & 11.9 \tabularnewline
2 & 104.841666666667 & 8.64496262501341 & 25.6 \tabularnewline
3 & 101.3 & 9.2138236066546 & 33 \tabularnewline
4 & 101.833333333333 & 8.60954368269553 & 9.6 \tabularnewline
5 & 99.875 & 7.73623410851935 & 15.2 \tabularnewline
6 & 99.625 & 7.29771134733972 & 8.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6790&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]108.816666666667[/C][C]7.8656714830196[/C][C]11.9[/C][/ROW]
[ROW][C]2[/C][C]104.841666666667[/C][C]8.64496262501341[/C][C]25.6[/C][/ROW]
[ROW][C]3[/C][C]101.3[/C][C]9.2138236066546[/C][C]33[/C][/ROW]
[ROW][C]4[/C][C]101.833333333333[/C][C]8.60954368269553[/C][C]9.6[/C][/ROW]
[ROW][C]5[/C][C]99.875[/C][C]7.73623410851935[/C][C]15.2[/C][/ROW]
[ROW][C]6[/C][C]99.625[/C][C]7.29771134733972[/C][C]8.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6790&T=1

As an alternative you can also use a QR Code:  

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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1108.8166666666677.865671483019611.9
2104.8416666666678.6449626250134125.6
3101.39.213823606654633
4101.8333333333338.609543682695539.6
599.8757.7362341085193515.2
699.6257.297711347339728.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.21851135080337
beta0.0195635920466587
S.D.0.100405404917447
T-STAT0.194846005180137
p-value0.855009924832906

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.21851135080337 \tabularnewline
beta & 0.0195635920466587 \tabularnewline
S.D. & 0.100405404917447 \tabularnewline
T-STAT & 0.194846005180137 \tabularnewline
p-value & 0.855009924832906 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6790&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.21851135080337[/C][/ROW]
[ROW][C]beta[/C][C]0.0195635920466587[/C][/ROW]
[ROW][C]S.D.[/C][C]0.100405404917447[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.194846005180137[/C][/ROW]
[ROW][C]p-value[/C][C]0.855009924832906[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6790&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6790&T=2

As an alternative you can also use a QR Code:  

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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.21851135080337
beta0.0195635920466587
S.D.0.100405404917447
T-STAT0.194846005180137
p-value0.855009924832906







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.62030168610453
beta0.320442174157661
S.D.1.26796921796915
T-STAT0.252720783451587
p-value0.812939829085523
Lambda0.679557825842339

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.62030168610453 \tabularnewline
beta & 0.320442174157661 \tabularnewline
S.D. & 1.26796921796915 \tabularnewline
T-STAT & 0.252720783451587 \tabularnewline
p-value & 0.812939829085523 \tabularnewline
Lambda & 0.679557825842339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6790&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.62030168610453[/C][/ROW]
[ROW][C]beta[/C][C]0.320442174157661[/C][/ROW]
[ROW][C]S.D.[/C][C]1.26796921796915[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.252720783451587[/C][/ROW]
[ROW][C]p-value[/C][C]0.812939829085523[/C][/ROW]
[ROW][C]Lambda[/C][C]0.679557825842339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6790&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6790&T=3

As an alternative you can also use a QR Code:  

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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.62030168610453
beta0.320442174157661
S.D.1.26796921796915
T-STAT0.252720783451587
p-value0.812939829085523
Lambda0.679557825842339



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')