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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 computationSat, 28 May 2016 08:57:27 +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/May/28/t1464422509wwalitop1cjb5q4.htm/, Retrieved Fri, 03 May 2024 06:38:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295626, Retrieved Fri, 03 May 2024 06:38:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

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] [] [2016-05-28 07:57:27] [f8975010d6e80ebfdd11eb899305ce74] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
38552
33618
31499
33892
37134
32710
32520
33419
35003
34417
32359
35703
38632
33577
33277
35001
38296
34179
32791
35261
36789
35036
33004
35548
38485
34675
33081
36114
37524
34600
33795
36017
37009
32877
32505
34162
38591
33550
30753
33508
36327
33230
32971
32844
35124
32243
30840
34815
36308
33138
31425
34265
37612
31846
31065
33712
36031
32909
32204
34914
34888
33242
32316
35295
37800
34540
32614
35859
39866
34609
32375
34395
35348
33221
33892
36762

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'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295626&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295626&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
134235.52072.652560455727053
235115.91666666671953.910738555485841
335070.33333333331944.74617803195980
4337332228.179893178217838
533785.752088.488018769916547
634816.58333333332247.42788167577550

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 34235.5 & 2072.65256045572 & 7053 \tabularnewline
2 & 35115.9166666667 & 1953.91073855548 & 5841 \tabularnewline
3 & 35070.3333333333 & 1944.7461780319 & 5980 \tabularnewline
4 & 33733 & 2228.17989317821 & 7838 \tabularnewline
5 & 33785.75 & 2088.48801876991 & 6547 \tabularnewline
6 & 34816.5833333333 & 2247.4278816757 & 7550 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295626&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]34235.5[/C][C]2072.65256045572[/C][C]7053[/C][/ROW]
[ROW][C]2[/C][C]35115.9166666667[/C][C]1953.91073855548[/C][C]5841[/C][/ROW]
[ROW][C]3[/C][C]35070.3333333333[/C][C]1944.7461780319[/C][C]5980[/C][/ROW]
[ROW][C]4[/C][C]33733[/C][C]2228.17989317821[/C][C]7838[/C][/ROW]
[ROW][C]5[/C][C]33785.75[/C][C]2088.48801876991[/C][C]6547[/C][/ROW]
[ROW][C]6[/C][C]34816.5833333333[/C][C]2247.4278816757[/C][C]7550[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295626&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
134235.52072.652560455727053
235115.91666666671953.910738555485841
335070.33333333331944.74617803195980
4337332228.179893178217838
533785.752088.488018769916547
634816.58333333332247.42788167577550






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5903.44796337573
beta-0.110686812469162
S.D.0.087216440471764
T-STAT-1.26910490580037
p-value0.273223545520154

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5903.44796337573 \tabularnewline
beta & -0.110686812469162 \tabularnewline
S.D. & 0.087216440471764 \tabularnewline
T-STAT & -1.26910490580037 \tabularnewline
p-value & 0.273223545520154 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295626&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5903.44796337573[/C][/ROW]
[ROW][C]beta[/C][C]-0.110686812469162[/C][/ROW]
[ROW][C]S.D.[/C][C]0.087216440471764[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.26910490580037[/C][/ROW]
[ROW][C]p-value[/C][C]0.273223545520154[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295626&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295626&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)
alpha5903.44796337573
beta-0.110686812469162
S.D.0.087216440471764
T-STAT-1.26910490580037
p-value0.273223545520154






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha27.0868686503559
beta-1.86112410923253
S.D.1.42173437075971
T-STAT-1.30905192102659
p-value0.260653093620231
Lambda2.86112410923253

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 27.0868686503559 \tabularnewline
beta & -1.86112410923253 \tabularnewline
S.D. & 1.42173437075971 \tabularnewline
T-STAT & -1.30905192102659 \tabularnewline
p-value & 0.260653093620231 \tabularnewline
Lambda & 2.86112410923253 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295626&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]27.0868686503559[/C][/ROW]
[ROW][C]beta[/C][C]-1.86112410923253[/C][/ROW]
[ROW][C]S.D.[/C][C]1.42173437075971[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.30905192102659[/C][/ROW]
[ROW][C]p-value[/C][C]0.260653093620231[/C][/ROW]
[ROW][C]Lambda[/C][C]2.86112410923253[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295626&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295626&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)
alpha27.0868686503559
beta-1.86112410923253
S.D.1.42173437075971
T-STAT-1.30905192102659
p-value0.260653093620231
Lambda2.86112410923253


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')