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 computationTue, 20 Dec 2016 16:24:30 +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/20/t1482247702d4tr1leynglbpu5.htm/, Retrieved Sat, 27 Apr 2024 18:21:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301715, Retrieved Sat, 27 Apr 2024 18:21:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58

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] [] [2016-12-20 15:24:30] [672675941468e072e71d9fb024f2b817] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5133
5155
5174
5201
5221
5205
5235
5255
5272
5299
5318
5340
5385
5430
5454
5493
5536
5565
5586
5594
5576
5544
5530
5536
5544
5564
5596
5596
5599
5591
5566
5532
5498
5484
5442
5447
5490
5544
5583
5628
5679
5691
5707
5724
5726
5745
5767
5789
5785
5785
5806
5827
5856
5896
5914
5938

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=301715&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=301715&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301715&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
1523465.0482338520634207
25519.0833333333365.7688214793901209
35538.2557.8416726150713157
45672.7592.7637517372149299

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5234 & 65.0482338520634 & 207 \tabularnewline
2 & 5519.08333333333 & 65.7688214793901 & 209 \tabularnewline
3 & 5538.25 & 57.8416726150713 & 157 \tabularnewline
4 & 5672.75 & 92.7637517372149 & 299 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301715&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]5234[/C][C]65.0482338520634[/C][C]207[/C][/ROW]
[ROW][C]2[/C][C]5519.08333333333[/C][C]65.7688214793901[/C][C]209[/C][/ROW]
[ROW][C]3[/C][C]5538.25[/C][C]57.8416726150713[/C][C]157[/C][/ROW]
[ROW][C]4[/C][C]5672.75[/C][C]92.7637517372149[/C][C]299[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301715&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301715&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
1523465.0482338520634207
25519.0833333333365.7688214793901209
35538.2557.8416726150713157
45672.7592.7637517372149299






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-183.297665673297
beta0.0461941947213942
S.D.0.0489875904501007
T-STAT0.942977482602416
p-value0.445231200351056

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -183.297665673297 \tabularnewline
beta & 0.0461941947213942 \tabularnewline
S.D. & 0.0489875904501007 \tabularnewline
T-STAT & 0.942977482602416 \tabularnewline
p-value & 0.445231200351056 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301715&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-183.297665673297[/C][/ROW]
[ROW][C]beta[/C][C]0.0461941947213942[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0489875904501007[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.942977482602416[/C][/ROW]
[ROW][C]p-value[/C][C]0.445231200351056[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301715&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301715&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-183.297665673297
beta0.0461941947213942
S.D.0.0489875904501007
T-STAT0.942977482602416
p-value0.445231200351056






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-22.4485713484246
beta3.09924120673233
S.D.3.63271556384382
T-STAT0.85314722616295
p-value0.483449329962066
Lambda-2.09924120673233

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -22.4485713484246 \tabularnewline
beta & 3.09924120673233 \tabularnewline
S.D. & 3.63271556384382 \tabularnewline
T-STAT & 0.85314722616295 \tabularnewline
p-value & 0.483449329962066 \tabularnewline
Lambda & -2.09924120673233 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301715&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-22.4485713484246[/C][/ROW]
[ROW][C]beta[/C][C]3.09924120673233[/C][/ROW]
[ROW][C]S.D.[/C][C]3.63271556384382[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.85314722616295[/C][/ROW]
[ROW][C]p-value[/C][C]0.483449329962066[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.09924120673233[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301715&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301715&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-22.4485713484246
beta3.09924120673233
S.D.3.63271556384382
T-STAT0.85314722616295
p-value0.483449329962066
Lambda-2.09924120673233


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')