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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 14 Dec 2016 14:36:13 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/14/t1481722854h94o569warbfo7z.htm/, Retrieved Fri, 17 May 2024 01:15:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299428, Retrieved Fri, 17 May 2024 01:15:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76

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 Deviatio...] [2016-12-14 13:36:13] [3b055ff671ad33431c4331443bac114d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9137.8
9009.4
8926.6
9145
9186.2
9152.2
9093.6
9199.2
9310.6
9282
9248.4
9341.6
9478.8
9438
9374.6
9488.8
9631.8
9588.4
9514.6
9623.2
9744.6
9685.8
9598
9703.4
9817.8
9762.6
9669.6
9789.2
9917.4
9864.4
9779.2
9898.8
10048.8
9983.4
9913.4
10031.6
10184.6
10125
10065.4
10188.6
10350.4
10320.6
10232.6
10357.2
10520.2
10473.8
10407
10536
10700.2
10664.2
10606
10716.6
10882.8
10849.4
10794
10907.8

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299428&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299428&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299428&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
19169.38333333333121.306357723915415
29572.5114.006618627644370
39873.01666666667114.81943004192379.199999999999
410313.45155.457404279933470.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9169.38333333333 & 121.306357723915 & 415 \tabularnewline
2 & 9572.5 & 114.006618627644 & 370 \tabularnewline
3 & 9873.01666666667 & 114.81943004192 & 379.199999999999 \tabularnewline
4 & 10313.45 & 155.457404279933 & 470.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299428&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]9169.38333333333[/C][C]121.306357723915[/C][C]415[/C][/ROW]
[ROW][C]2[/C][C]9572.5[/C][C]114.006618627644[/C][C]370[/C][/ROW]
[ROW][C]3[/C][C]9873.01666666667[/C][C]114.81943004192[/C][C]379.199999999999[/C][/ROW]
[ROW][C]4[/C][C]10313.45[/C][C]155.457404279933[/C][C]470.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299428&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299428&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
19169.38333333333121.306357723915415
29572.5114.006618627644370
39873.01666666667114.81943004192379.199999999999
410313.45155.457404279933470.6






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-153.141391805532
beta0.028723420794756
S.D.0.0203635840263007
T-STAT1.41052875356608
p-value0.293816223542784

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -153.141391805532 \tabularnewline
beta & 0.028723420794756 \tabularnewline
S.D. & 0.0203635840263007 \tabularnewline
T-STAT & 1.41052875356608 \tabularnewline
p-value & 0.293816223542784 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299428&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-153.141391805532[/C][/ROW]
[ROW][C]beta[/C][C]0.028723420794756[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0203635840263007[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.41052875356608[/C][/ROW]
[ROW][C]p-value[/C][C]0.293816223542784[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299428&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299428&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-153.141391805532
beta0.028723420794756
S.D.0.0203635840263007
T-STAT1.41052875356608
p-value0.293816223542784






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-13.4945497124339
beta1.99576431419064
S.D.1.5316470459304
T-STAT1.30301842026425
p-value0.322396721299174
Lambda-0.99576431419064

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -13.4945497124339 \tabularnewline
beta & 1.99576431419064 \tabularnewline
S.D. & 1.5316470459304 \tabularnewline
T-STAT & 1.30301842026425 \tabularnewline
p-value & 0.322396721299174 \tabularnewline
Lambda & -0.99576431419064 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299428&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.4945497124339[/C][/ROW]
[ROW][C]beta[/C][C]1.99576431419064[/C][/ROW]
[ROW][C]S.D.[/C][C]1.5316470459304[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.30301842026425[/C][/ROW]
[ROW][C]p-value[/C][C]0.322396721299174[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.99576431419064[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299428&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299428&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-13.4945497124339
beta1.99576431419064
S.D.1.5316470459304
T-STAT1.30301842026425
p-value0.322396721299174
Lambda-0.99576431419064


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 1 ;
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')