FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 30 Nov 2013 10:21:17 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/30/t1385824890n1318npec9u8f9w.htm/, Retrieved Fri, 03 May 2024 07:33:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=229694, Retrieved Fri, 03 May 2024 07:33:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

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] [] [2013-11-30 15:21:17] [6db2c0c963bf82ed406b79886f98dcae] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4309
4303
4177
4117
4065
3983
4091
4067
4024
3868
3800
3804
3862
3792
3674
3560
3489
3412
3674
3672
3463
3429
3400
3533
3578
3544
3435
3352
3213
3235
3460
3385
3283
3295
3331
3520
3668
3714
3691
3604
3581
3675
3833
3810
3663
3704
3810
4053
4152
4139
4055
3928
3821
3811
3999
3954
3724
3731
3697
3818
3897
3888
3754
3647
3564
3498
3704
3678
3599
3507
3484
2612
2926
2918
2833
2791
2762
2728
2831
2839
2775
2540
2625
2669

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229694&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229694&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229694&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14050.66666666667169.277251510024509
23580153.329117201588462
33385.91666666667121.902687220238365
43733.83333333333127.724727678731472
53902.41666666667159.462995612452455
63569.33333333333332.0244605812081285
72769.75114.855739556589386

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4050.66666666667 & 169.277251510024 & 509 \tabularnewline
2 & 3580 & 153.329117201588 & 462 \tabularnewline
3 & 3385.91666666667 & 121.902687220238 & 365 \tabularnewline
4 & 3733.83333333333 & 127.724727678731 & 472 \tabularnewline
5 & 3902.41666666667 & 159.462995612452 & 455 \tabularnewline
6 & 3569.33333333333 & 332.024460581208 & 1285 \tabularnewline
7 & 2769.75 & 114.855739556589 & 386 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229694&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]4050.66666666667[/C][C]169.277251510024[/C][C]509[/C][/ROW]
[ROW][C]2[/C][C]3580[/C][C]153.329117201588[/C][C]462[/C][/ROW]
[ROW][C]3[/C][C]3385.91666666667[/C][C]121.902687220238[/C][C]365[/C][/ROW]
[ROW][C]4[/C][C]3733.83333333333[/C][C]127.724727678731[/C][C]472[/C][/ROW]
[ROW][C]5[/C][C]3902.41666666667[/C][C]159.462995612452[/C][C]455[/C][/ROW]
[ROW][C]6[/C][C]3569.33333333333[/C][C]332.024460581208[/C][C]1285[/C][/ROW]
[ROW][C]7[/C][C]2769.75[/C][C]114.855739556589[/C][C]386[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229694&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229694&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
14050.66666666667169.277251510024509
23580153.329117201588462
33385.91666666667121.902687220238365
43733.83333333333127.724727678731472
53902.41666666667159.462995612452455
63569.33333333333332.0244605812081285
72769.75114.855739556589386






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha24.7883205707599
beta0.0402153523785561
S.D.0.0784373342257117
T-STAT0.512706771278486
p-value0.629995712264891

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 24.7883205707599 \tabularnewline
beta & 0.0402153523785561 \tabularnewline
S.D. & 0.0784373342257117 \tabularnewline
T-STAT & 0.512706771278486 \tabularnewline
p-value & 0.629995712264891 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229694&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]24.7883205707599[/C][/ROW]
[ROW][C]beta[/C][C]0.0402153523785561[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0784373342257117[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.512706771278486[/C][/ROW]
[ROW][C]p-value[/C][C]0.629995712264891[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229694&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229694&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)
alpha24.7883205707599
beta0.0402153523785561
S.D.0.0784373342257117
T-STAT0.512706771278486
p-value0.629995712264891






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.25117691437492
beta1.01708959004681
S.D.1.2061599378294
T-STAT0.843246039059435
p-value0.43755942730493
Lambda-0.0170895900468147

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.25117691437492 \tabularnewline
beta & 1.01708959004681 \tabularnewline
S.D. & 1.2061599378294 \tabularnewline
T-STAT & 0.843246039059435 \tabularnewline
p-value & 0.43755942730493 \tabularnewline
Lambda & -0.0170895900468147 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229694&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.25117691437492[/C][/ROW]
[ROW][C]beta[/C][C]1.01708959004681[/C][/ROW]
[ROW][C]S.D.[/C][C]1.2061599378294[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.843246039059435[/C][/ROW]
[ROW][C]p-value[/C][C]0.43755942730493[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0170895900468147[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229694&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229694&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-3.25117691437492
beta1.01708959004681
S.D.1.2061599378294
T-STAT0.843246039059435
p-value0.43755942730493
Lambda-0.0170895900468147


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')