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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 computationMon, 18 Aug 2008 09:06:14 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Aug/18/t1219072243xam5g47i4oylgdy.htm/, Retrieved Mon, 13 May 2024 22:25:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=14238, Retrieved Mon, 13 May 2024 22:25:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsAfzetprijsindexen van de verwerking en conservering van groenten en fruit
Estimated Impact232

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] [Sanne Seghers - 2...] [2008-08-18 15:06:14] [084e0343a0486ff05530df6c705c8bb4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
115.6
118.5
118.1
117.7
117.9
118.5
117
115.6
113.7
112.1
113.5
113.5
112.2
112.7
111.9
111.5
110.8
111.2
110.9
114.1
121.3
121.5
122.5
122.4
122.5
122.8
122.9
123.6
123.4
122.9
121
119
119
114.3
113.4
113.7
113.5
114.4
114.6
111.6
111.8
110.8
112.6
115.3
115.4
115.3
115.5
115
116.3
117
116.9
117.2
117.1
116.7
117.4
126.7
128.6
129.2
131.1
131.1
131.5
133.2
133.7
135.7
134.9
135.7
131.2
127.4
127.5
124.1
124.1
124.1
124.5
123.7
125.9
126
125.5
125.3

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14238&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14238&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14238&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1115.9752.290742237791066.4
2115.255.0171523977071111.7
3119.8753.9770077833832410.2000000000000
4113.8166666666671.699108500646654.7
5122.1083333333336.4861332273107214.8
6130.2583333333334.6048311257818911.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 115.975 & 2.29074223779106 & 6.4 \tabularnewline
2 & 115.25 & 5.01715239770711 & 11.7 \tabularnewline
3 & 119.875 & 3.97700778338324 & 10.2000000000000 \tabularnewline
4 & 113.816666666667 & 1.69910850064665 & 4.7 \tabularnewline
5 & 122.108333333333 & 6.48613322731072 & 14.8 \tabularnewline
6 & 130.258333333333 & 4.60483112578189 & 11.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14238&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]115.975[/C][C]2.29074223779106[/C][C]6.4[/C][/ROW]
[ROW][C]2[/C][C]115.25[/C][C]5.01715239770711[/C][C]11.7[/C][/ROW]
[ROW][C]3[/C][C]119.875[/C][C]3.97700778338324[/C][C]10.2000000000000[/C][/ROW]
[ROW][C]4[/C][C]113.816666666667[/C][C]1.69910850064665[/C][C]4.7[/C][/ROW]
[ROW][C]5[/C][C]122.108333333333[/C][C]6.48613322731072[/C][C]14.8[/C][/ROW]
[ROW][C]6[/C][C]130.258333333333[/C][C]4.60483112578189[/C][C]11.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14238&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14238&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
1115.9752.290742237791066.4
2115.255.0171523977071111.7
3119.8753.9770077833832410.2000000000000
4113.8166666666671.699108500646654.7
5122.1083333333336.4861332273107214.8
6130.2583333333334.6048311257818911.6






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-13.8804783326283
beta0.149672856288854
S.D.0.125272260394561
T-STAT1.19478051898673
p-value0.298171476035111

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -13.8804783326283 \tabularnewline
beta & 0.149672856288854 \tabularnewline
S.D. & 0.125272260394561 \tabularnewline
T-STAT & 1.19478051898673 \tabularnewline
p-value & 0.298171476035111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14238&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.8804783326283[/C][/ROW]
[ROW][C]beta[/C][C]0.149672856288854[/C][/ROW]
[ROW][C]S.D.[/C][C]0.125272260394561[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.19478051898673[/C][/ROW]
[ROW][C]p-value[/C][C]0.298171476035111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14238&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14238&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-13.8804783326283
beta0.149672856288854
S.D.0.125272260394561
T-STAT1.19478051898673
p-value0.298171476035111






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-26.434680241941
beta5.79723808147611
S.D.4.18572541898656
T-STAT1.38500200112977
p-value0.238288127686155
Lambda-4.79723808147611

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -26.434680241941 \tabularnewline
beta & 5.79723808147611 \tabularnewline
S.D. & 4.18572541898656 \tabularnewline
T-STAT & 1.38500200112977 \tabularnewline
p-value & 0.238288127686155 \tabularnewline
Lambda & -4.79723808147611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14238&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-26.434680241941[/C][/ROW]
[ROW][C]beta[/C][C]5.79723808147611[/C][/ROW]
[ROW][C]S.D.[/C][C]4.18572541898656[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.38500200112977[/C][/ROW]
[ROW][C]p-value[/C][C]0.238288127686155[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.79723808147611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14238&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14238&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-26.434680241941
beta5.79723808147611
S.D.4.18572541898656
T-STAT1.38500200112977
p-value0.238288127686155
Lambda-4.79723808147611


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')