FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 23 Nov 2007 07:57:06 -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/23/t1195829498qrenucj7ze1boas.htm/, Retrieved Sun, 28 Apr 2024 19:48:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6184, Retrieved Sun, 28 Apr 2024 19:48:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsStandard Deviation Meanplot
Estimated Impact213

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] [Workshop 7 Q1] [2007-11-23 14:57:06] [a2659e9a411aa0bcc5ca303430cc5df1] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,6
96,1
110
108,2
106,9
117,2
105,2
106,3
95,9
107,5
113
111,4
95,5
90,3
110,8
107,1
101,4
112,9
98,5
100,1
93,4
104,4
101,8
107,9
91,3
86,6
111,4
98,4
102,2
103
95,8
96
95,7
106,4
112
116,2
93,9
100,5
112,5
101,2
107,8
114,3
99,6
98,6
93,6
99,6
113,1
110,7
88,1
93,1
107,4
99,5
105,6
108,3
99,2
99,3
107,1
106,9
115,4
99
100,1
96,2
96,9
96,2
91
99
99
107,2
110,8
111,1
104,6
94,3
90,7
88,8
90,9
90,5
95,5
103,1
100,6
103,1

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6184&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]1 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=6184&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6184&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1106.5256.4251105402588629.1
2102.0083333333336.9556332086542226.3
3101.258.956409589074919.3
4103.7833333333337.4957968020064218.1
5102.4083333333337.4601314067555624.4
6100.5333333333336.4907393238133512.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 106.525 & 6.42511054025886 & 29.1 \tabularnewline
2 & 102.008333333333 & 6.95563320865422 & 26.3 \tabularnewline
3 & 101.25 & 8.9564095890749 & 19.3 \tabularnewline
4 & 103.783333333333 & 7.49579680200642 & 18.1 \tabularnewline
5 & 102.408333333333 & 7.46013140675556 & 24.4 \tabularnewline
6 & 100.533333333333 & 6.49073932381335 & 12.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6184&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]106.525[/C][C]6.42511054025886[/C][C]29.1[/C][/ROW]
[ROW][C]2[/C][C]102.008333333333[/C][C]6.95563320865422[/C][C]26.3[/C][/ROW]
[ROW][C]3[/C][C]101.25[/C][C]8.9564095890749[/C][C]19.3[/C][/ROW]
[ROW][C]4[/C][C]103.783333333333[/C][C]7.49579680200642[/C][C]18.1[/C][/ROW]
[ROW][C]5[/C][C]102.408333333333[/C][C]7.46013140675556[/C][C]24.4[/C][/ROW]
[ROW][C]6[/C][C]100.533333333333[/C][C]6.49073932381335[/C][C]12.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6184&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6184&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
1106.5256.4251105402588629.1
2102.0083333333336.9556332086542226.3
3101.258.956409589074919.3
4103.7833333333337.4957968020064218.1
5102.4083333333337.4601314067555624.4
6100.5333333333336.4907393238133512.1






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha23.2342267200190
beta-0.155101779293954
S.D.0.202304885131130
T-STAT-0.766673425574574
p-value0.486021441081079

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 23.2342267200190 \tabularnewline
beta & -0.155101779293954 \tabularnewline
S.D. & 0.202304885131130 \tabularnewline
T-STAT & -0.766673425574574 \tabularnewline
p-value & 0.486021441081079 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6184&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]23.2342267200190[/C][/ROW]
[ROW][C]beta[/C][C]-0.155101779293954[/C][/ROW]
[ROW][C]S.D.[/C][C]0.202304885131130[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.766673425574574[/C][/ROW]
[ROW][C]p-value[/C][C]0.486021441081079[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6184&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6184&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)
alpha23.2342267200190
beta-0.155101779293954
S.D.0.202304885131130
T-STAT-0.766673425574574
p-value0.486021441081079






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha11.6757681257492
beta-2.09292346147028
S.D.2.75930333761410
T-STAT-0.758497057188348
p-value0.490389049826822
Lambda3.09292346147028

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 11.6757681257492 \tabularnewline
beta & -2.09292346147028 \tabularnewline
S.D. & 2.75930333761410 \tabularnewline
T-STAT & -0.758497057188348 \tabularnewline
p-value & 0.490389049826822 \tabularnewline
Lambda & 3.09292346147028 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6184&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]11.6757681257492[/C][/ROW]
[ROW][C]beta[/C][C]-2.09292346147028[/C][/ROW]
[ROW][C]S.D.[/C][C]2.75930333761410[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.758497057188348[/C][/ROW]
[ROW][C]p-value[/C][C]0.490389049826822[/C][/ROW]
[ROW][C]Lambda[/C][C]3.09292346147028[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6184&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6184&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)
alpha11.6757681257492
beta-2.09292346147028
S.D.2.75930333761410
T-STAT-0.758497057188348
p-value0.490389049826822
Lambda3.09292346147028


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')