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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 computationWed, 26 May 2010 16:23:39 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/26/t1274891117ue342o3hc3qkom5.htm/, Retrieved Fri, 03 May 2024 06:49:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76514, Retrieved Fri, 03 May 2024 06:49:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact118

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] [Energieverbruik ] [2010-05-26 16:23:39] [dd2ef098fd65ce7e9f689caa343b799f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5.074
4.643
5.451
5.397
5.635
5.708
5.578
5.574
5.352
5.302
4.923
4.982
5.101
4.763
5.505
5.385
5.794
5.695
5.798
5.705
5.422
5.311
4.968
5.053
5.236
4.782
5.531
5.566
5.961
5.868
5.872
5.908
5.594
5.526
5.111
5.177
5.835
5.348
6.038
6.039
6.408
6.214
6.138
6.529
6.058
6.026
5.678
5.733
6.488
5.936
6.84
6.694
7.193
6.991
7.209
7.104
6.83
6.848
6.396
6.414
7.151
6.882
7.698
7.626
7.936
8.054
8.128
8.062
7.708
7.574
7.039
7.146
7.07
6.607
7.699
7.663
7.988
7.723
8.087
8.028
7.362

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76514&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76514&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76514&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
15.301583333333330.3291745760461331.065
25.3750.3448383020278561.035
35.5110.3701400226449941.179
46.003666666666670.3226721762615011.181
56.745250.3798023708576491.273
67.583666666666670.4336547292978881.246

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5.30158333333333 & 0.329174576046133 & 1.065 \tabularnewline
2 & 5.375 & 0.344838302027856 & 1.035 \tabularnewline
3 & 5.511 & 0.370140022644994 & 1.179 \tabularnewline
4 & 6.00366666666667 & 0.322672176261501 & 1.181 \tabularnewline
5 & 6.74525 & 0.379802370857649 & 1.273 \tabularnewline
6 & 7.58366666666667 & 0.433654729297888 & 1.246 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76514&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]5.30158333333333[/C][C]0.329174576046133[/C][C]1.065[/C][/ROW]
[ROW][C]2[/C][C]5.375[/C][C]0.344838302027856[/C][C]1.035[/C][/ROW]
[ROW][C]3[/C][C]5.511[/C][C]0.370140022644994[/C][C]1.179[/C][/ROW]
[ROW][C]4[/C][C]6.00366666666667[/C][C]0.322672176261501[/C][C]1.181[/C][/ROW]
[ROW][C]5[/C][C]6.74525[/C][C]0.379802370857649[/C][C]1.273[/C][/ROW]
[ROW][C]6[/C][C]7.58366666666667[/C][C]0.433654729297888[/C][C]1.246[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76514&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76514&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
15.301583333333330.3291745760461331.065
25.3750.3448383020278561.035
35.5110.3701400226449941.179
46.003666666666670.3226721762615011.181
56.745250.3798023708576491.273
67.583666666666670.4336547292978881.246






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.134453316553611
beta0.0376110626863063
S.D.0.0124743945810363
T-STAT3.01506116725561
p-value0.039353875444527

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.134453316553611 \tabularnewline
beta & 0.0376110626863063 \tabularnewline
S.D. & 0.0124743945810363 \tabularnewline
T-STAT & 3.01506116725561 \tabularnewline
p-value & 0.039353875444527 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76514&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.134453316553611[/C][/ROW]
[ROW][C]beta[/C][C]0.0376110626863063[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0124743945810363[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.01506116725561[/C][/ROW]
[ROW][C]p-value[/C][C]0.039353875444527[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76514&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76514&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)
alpha0.134453316553611
beta0.0376110626863063
S.D.0.0124743945810363
T-STAT3.01506116725561
p-value0.039353875444527






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.11833056726488
beta0.61254706331226
S.D.0.227700896772525
T-STAT2.69013900250116
p-value0.0546501769198837
Lambda0.38745293668774

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.11833056726488 \tabularnewline
beta & 0.61254706331226 \tabularnewline
S.D. & 0.227700896772525 \tabularnewline
T-STAT & 2.69013900250116 \tabularnewline
p-value & 0.0546501769198837 \tabularnewline
Lambda & 0.38745293668774 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76514&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.11833056726488[/C][/ROW]
[ROW][C]beta[/C][C]0.61254706331226[/C][/ROW]
[ROW][C]S.D.[/C][C]0.227700896772525[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.69013900250116[/C][/ROW]
[ROW][C]p-value[/C][C]0.0546501769198837[/C][/ROW]
[ROW][C]Lambda[/C][C]0.38745293668774[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76514&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76514&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-2.11833056726488
beta0.61254706331226
S.D.0.227700896772525
T-STAT2.69013900250116
p-value0.0546501769198837
Lambda0.38745293668774


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')