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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 02 May 2012 06:38:45 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/02/t1335955184izuevro9zr30l3a.htm/, Retrieved Tue, 07 May 2024 13:34:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165894, Retrieved Tue, 07 May 2024 13:34:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact122
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Spreidingsmaten g...] [2012-05-02 10:38:45] [08ac479f43b71ff391b5d339ed1ce3ff] [Current]
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Dataseries X:
73.97	
73.97	
73.97	
73.97	
73.97	
73.97	
73.96	
74.44	
75.43	
75.77	
75.82	
75.85	
75.85	
75.85	
77.95	
82.07	
84.82	
85.08	
85.34	
85.65	
85.65	
85.72	
85.73	
85.73	
85.73	
85.73	
85.74	
86.32	
87.59	
87.81	
87.87	
87.94	
87.96	
88.01	
88.01	
88.01	
88.01	
88.01	
88.59	
89.43	
89.63	
89.73	
89.88	
89.89	
89.90	
89.91	
89.86	
90.07	
90.17	
90.17	
90.28	
90.87	
92.05	
92.10	
92.16	
92.22	
92.25	
92.29	
92.29	
92.29




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165894&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165894&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165894&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
174.59083333333330.8487580052730881.89
282.95333333333334.02322650557389.88000000000001
387.22666666666671.012910597628382.28
489.40916666666670.7581731432539082.05999999999999
591.5950.9227478725868922.12

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 74.5908333333333 & 0.848758005273088 & 1.89 \tabularnewline
2 & 82.9533333333333 & 4.0232265055738 & 9.88000000000001 \tabularnewline
3 & 87.2266666666667 & 1.01291059762838 & 2.28 \tabularnewline
4 & 89.4091666666667 & 0.758173143253908 & 2.05999999999999 \tabularnewline
5 & 91.595 & 0.922747872586892 & 2.12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165894&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]74.5908333333333[/C][C]0.848758005273088[/C][C]1.89[/C][/ROW]
[ROW][C]2[/C][C]82.9533333333333[/C][C]4.0232265055738[/C][C]9.88000000000001[/C][/ROW]
[ROW][C]3[/C][C]87.2266666666667[/C][C]1.01291059762838[/C][C]2.28[/C][/ROW]
[ROW][C]4[/C][C]89.4091666666667[/C][C]0.758173143253908[/C][C]2.05999999999999[/C][/ROW]
[ROW][C]5[/C][C]91.595[/C][C]0.922747872586892[/C][C]2.12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165894&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165894&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
174.59083333333330.8487580052730881.89
282.95333333333334.02322650557389.88000000000001
387.22666666666671.012910597628382.28
489.40916666666670.7581731432539082.05999999999999
591.5950.9227478725868922.12







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4.61023281078058
beta-0.0363697913911968
S.D.0.119093077397437
T-STAT-0.305389634611789
p-value0.780032703240073

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4.61023281078058 \tabularnewline
beta & -0.0363697913911968 \tabularnewline
S.D. & 0.119093077397437 \tabularnewline
T-STAT & -0.305389634611789 \tabularnewline
p-value & 0.780032703240073 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165894&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.61023281078058[/C][/ROW]
[ROW][C]beta[/C][C]-0.0363697913911968[/C][/ROW]
[ROW][C]S.D.[/C][C]0.119093077397437[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.305389634611789[/C][/ROW]
[ROW][C]p-value[/C][C]0.780032703240073[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165894&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165894&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)
alpha4.61023281078058
beta-0.0363697913911968
S.D.0.119093077397437
T-STAT-0.305389634611789
p-value0.780032703240073







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha5.4641062368344
beta-1.19034444926277
S.D.4.83272048052585
T-STAT-0.246309393241225
p-value0.821334164394059
Lambda2.19034444926277

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.4641062368344 \tabularnewline
beta & -1.19034444926277 \tabularnewline
S.D. & 4.83272048052585 \tabularnewline
T-STAT & -0.246309393241225 \tabularnewline
p-value & 0.821334164394059 \tabularnewline
Lambda & 2.19034444926277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165894&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.4641062368344[/C][/ROW]
[ROW][C]beta[/C][C]-1.19034444926277[/C][/ROW]
[ROW][C]S.D.[/C][C]4.83272048052585[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.246309393241225[/C][/ROW]
[ROW][C]p-value[/C][C]0.821334164394059[/C][/ROW]
[ROW][C]Lambda[/C][C]2.19034444926277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165894&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165894&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)
alpha5.4641062368344
beta-1.19034444926277
S.D.4.83272048052585
T-STAT-0.246309393241225
p-value0.821334164394059
Lambda2.19034444926277



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')