FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSun, 18 Dec 2016 14:59:34 +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/18/t1482072838cgepp63g5w0pxm6.htm/, Retrieved Wed, 08 May 2024 13:13:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301115, Retrieved Wed, 08 May 2024 13:13:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81

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] [] [2016-12-18 13:59:34] [94ac3c9a028ddd47e8862e80eac9f626] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
295
520
550
610
775
885
965
475
875
1330
1635
920
1700
1465
1190
1390
1580
1775
1975
2440
2160
2670
3340
3230
2175
2035
3520
3945
2920
2495
2630
3610
5020
5755
7040
5345
4260
4785
3735
2980
2910

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=301115&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=301115&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301115&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
1819.583333333333377.3439372372331340
22076.25709.6033623216442150
33874.166666666671591.646993373585005

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 819.583333333333 & 377.343937237233 & 1340 \tabularnewline
2 & 2076.25 & 709.603362321644 & 2150 \tabularnewline
3 & 3874.16666666667 & 1591.64699337358 & 5005 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301115&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]819.583333333333[/C][C]377.343937237233[/C][C]1340[/C][/ROW]
[ROW][C]2[/C][C]2076.25[/C][C]709.603362321644[/C][C]2150[/C][/ROW]
[ROW][C]3[/C][C]3874.16666666667[/C][C]1591.64699337358[/C][C]5005[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301115&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301115&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
1819.583333333333377.3439372372331340
22076.25709.6033623216442150
33874.166666666671591.646993373585005






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-18.688701376945
beta0.403938020245685
S.D.0.0625915583044952
T-STAT6.45355430009601
p-value0.0978680450821244

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -18.688701376945 \tabularnewline
beta & 0.403938020245685 \tabularnewline
S.D. & 0.0625915583044952 \tabularnewline
T-STAT & 6.45355430009601 \tabularnewline
p-value & 0.0978680450821244 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301115&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-18.688701376945[/C][/ROW]
[ROW][C]beta[/C][C]0.403938020245685[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0625915583044952[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.45355430009601[/C][/ROW]
[ROW][C]p-value[/C][C]0.0978680450821244[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301115&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301115&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-18.688701376945
beta0.403938020245685
S.D.0.0625915583044952
T-STAT6.45355430009601
p-value0.0978680450821244






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.215748428482079
beta0.90749042778826
S.D.0.168652736682881
T-STAT5.38082242622972
p-value0.116978163297479
Lambda0.0925095722117399

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.215748428482079 \tabularnewline
beta & 0.90749042778826 \tabularnewline
S.D. & 0.168652736682881 \tabularnewline
T-STAT & 5.38082242622972 \tabularnewline
p-value & 0.116978163297479 \tabularnewline
Lambda & 0.0925095722117399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301115&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.215748428482079[/C][/ROW]
[ROW][C]beta[/C][C]0.90749042778826[/C][/ROW]
[ROW][C]S.D.[/C][C]0.168652736682881[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.38082242622972[/C][/ROW]
[ROW][C]p-value[/C][C]0.116978163297479[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0925095722117399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301115&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301115&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-0.215748428482079
beta0.90749042778826
S.D.0.168652736682881
T-STAT5.38082242622972
p-value0.116978163297479
Lambda0.0925095722117399


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 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')