Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 21 Nov 2014 18:46:08 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/21/t1416595584uskss0l3fu170g1.htm/, Retrieved Sun, 19 May 2024 15:55:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257708, Retrieved Sun, 19 May 2024 15:55:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Gemiddelde consum...] [2014-11-21 18:46:08] [1ab96e54865215824aa8065210e49a0c] [Current]
Feedback Forum

Post a new message
Dataseries X:
48,74
48,79
48,82
48,82
49,20
49,30
49,30
49,34
49,47
49,65
49,70
49,75
49,75
49,70
50,09
50,19
50,53
50,55
50,55
50,55
50,58
50,61
50,94
51,01
51,01
51,04
51,15
51,31
51,31
51,34
51,34
51,34
51,47
51,95
51,97
51,92
51,92
51,91
51,97
52,14
52,33
52,40
52,40
52,41
52,71
53,17
53,33
53,32
53,32
53,30
53,31
53,72
53,87
53,91
53,91
53,96
54,02
54,33
54,48
54,54
52,40
52,45
52,38
52,45
52,83
52,76
52,86
52,88
53,32
53,20
53,22
53,22




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257708&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257708&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257708&T=0

As an alternative you can also use a 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 Maurice George Kendall' @ kendall.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
149.240.3713366519627561.01
250.42083333333330.4125410906990361.31
351.42916666666670.3389410872202730.960000000000001
452.50083333333330.5227803003406331.42
553.88916666666670.4291102493073381.24
652.83083333333330.3523546336842860.939999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 49.24 & 0.371336651962756 & 1.01 \tabularnewline
2 & 50.4208333333333 & 0.412541090699036 & 1.31 \tabularnewline
3 & 51.4291666666667 & 0.338941087220273 & 0.960000000000001 \tabularnewline
4 & 52.5008333333333 & 0.522780300340633 & 1.42 \tabularnewline
5 & 53.8891666666667 & 0.429110249307338 & 1.24 \tabularnewline
6 & 52.8308333333333 & 0.352354633684286 & 0.939999999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257708&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]49.24[/C][C]0.371336651962756[/C][C]1.01[/C][/ROW]
[ROW][C]2[/C][C]50.4208333333333[/C][C]0.412541090699036[/C][C]1.31[/C][/ROW]
[ROW][C]3[/C][C]51.4291666666667[/C][C]0.338941087220273[/C][C]0.960000000000001[/C][/ROW]
[ROW][C]4[/C][C]52.5008333333333[/C][C]0.522780300340633[/C][C]1.42[/C][/ROW]
[ROW][C]5[/C][C]53.8891666666667[/C][C]0.429110249307338[/C][C]1.24[/C][/ROW]
[ROW][C]6[/C][C]52.8308333333333[/C][C]0.352354633684286[/C][C]0.939999999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257708&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257708&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
149.240.3713366519627561.01
250.42083333333330.4125410906990361.31
351.42916666666670.3389410872202730.960000000000001
452.50083333333330.5227803003406331.42
553.88916666666670.4291102493073381.24
652.83083333333330.3523546336842860.939999999999998







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.234052863384088
beta0.0123469140679443
S.D.0.0188512686268961
T-STAT0.654964623989724
p-value0.548243462424941

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.234052863384088 \tabularnewline
beta & 0.0123469140679443 \tabularnewline
S.D. & 0.0188512686268961 \tabularnewline
T-STAT & 0.654964623989724 \tabularnewline
p-value & 0.548243462424941 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257708&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.234052863384088[/C][/ROW]
[ROW][C]beta[/C][C]0.0123469140679443[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0188512686268961[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.654964623989724[/C][/ROW]
[ROW][C]p-value[/C][C]0.548243462424941[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257708&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257708&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.234052863384088
beta0.0123469140679443
S.D.0.0188512686268961
T-STAT0.654964623989724
p-value0.548243462424941







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.7048106256266
beta1.46725530593234
S.D.2.29399436919126
T-STAT0.639607195918973
p-value0.557222364832755
Lambda-0.467255305932337

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -6.7048106256266 \tabularnewline
beta & 1.46725530593234 \tabularnewline
S.D. & 2.29399436919126 \tabularnewline
T-STAT & 0.639607195918973 \tabularnewline
p-value & 0.557222364832755 \tabularnewline
Lambda & -0.467255305932337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257708&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.7048106256266[/C][/ROW]
[ROW][C]beta[/C][C]1.46725530593234[/C][/ROW]
[ROW][C]S.D.[/C][C]2.29399436919126[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.639607195918973[/C][/ROW]
[ROW][C]p-value[/C][C]0.557222364832755[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.467255305932337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257708&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257708&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.7048106256266
beta1.46725530593234
S.D.2.29399436919126
T-STAT0.639607195918973
p-value0.557222364832755
Lambda-0.467255305932337



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- '12'
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')