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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, 17 May 2010 16:51:24 +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/2010/May/17/t1274115307ckotuq9g5pu6djc.htm/, Retrieved Sun, 05 May 2024 18:43:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76108, Retrieved Sun, 05 May 2024 18:43:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords KDGP2W83
Estimated Impact111

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] [opgave 8 oef 3 st...] [2010-05-17 16:51:24] [de7054811a4039cd82332eb5d7e753fd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14861
14583,3
15305,8
17903,9
16379,4
15420,3
17870,5
15912,8
13866,5
17823,2
17872
17420,4
16704,4
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22160
20664,3
17877,4
20906,5
21164,1
21374,4
22952,3
21343,5
23899,3
22392,9
18274,1
22786,7
22321,5
17842,2
16373,5
16087,1
16555,9
17880,2
16764,5
16049
18288,3
17570,4
15133,4
19334,2
19291,8
20176,7

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'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76108&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76108&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76108&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
116268.25833333331474.995517070744037.4
217456.30833333331359.559741880594060.5
318656.9251471.374171017144907
419622.3251460.992261895384816.6
521094.5752054.609302442156057.1
617458.751563.615751159065043.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 16268.2583333333 & 1474.99551707074 & 4037.4 \tabularnewline
2 & 17456.3083333333 & 1359.55974188059 & 4060.5 \tabularnewline
3 & 18656.925 & 1471.37417101714 & 4907 \tabularnewline
4 & 19622.325 & 1460.99226189538 & 4816.6 \tabularnewline
5 & 21094.575 & 2054.60930244215 & 6057.1 \tabularnewline
6 & 17458.75 & 1563.61575115906 & 5043.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76108&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]16268.2583333333[/C][C]1474.99551707074[/C][C]4037.4[/C][/ROW]
[ROW][C]2[/C][C]17456.3083333333[/C][C]1359.55974188059[/C][C]4060.5[/C][/ROW]
[ROW][C]3[/C][C]18656.925[/C][C]1471.37417101714[/C][C]4907[/C][/ROW]
[ROW][C]4[/C][C]19622.325[/C][C]1460.99226189538[/C][C]4816.6[/C][/ROW]
[ROW][C]5[/C][C]21094.575[/C][C]2054.60930244215[/C][C]6057.1[/C][/ROW]
[ROW][C]6[/C][C]17458.75[/C][C]1563.61575115906[/C][C]5043.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76108&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76108&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
116268.25833333331474.995517070744037.4
217456.30833333331359.559741880594060.5
318656.9251471.374171017144907
419622.3251460.992261895384816.6
521094.5752054.609302442156057.1
617458.751563.615751159065043.3






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-328.965676064233
beta0.102742714135085
S.D.0.0497411966724328
T-STAT2.06554568463019
p-value0.107772759021202

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -328.965676064233 \tabularnewline
beta & 0.102742714135085 \tabularnewline
S.D. & 0.0497411966724328 \tabularnewline
T-STAT & 2.06554568463019 \tabularnewline
p-value & 0.107772759021202 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76108&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-328.965676064233[/C][/ROW]
[ROW][C]beta[/C][C]0.102742714135085[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0497411966724328[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.06554568463019[/C][/ROW]
[ROW][C]p-value[/C][C]0.107772759021202[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76108&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76108&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-328.965676064233
beta0.102742714135085
S.D.0.0497411966724328
T-STAT2.06554568463019
p-value0.107772759021202






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.11746939964891
beta1.06573683648856
S.D.0.565006439077867
T-STAT1.88623839088971
p-value0.132324083791023
Lambda-0.0657368364885582

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.11746939964891 \tabularnewline
beta & 1.06573683648856 \tabularnewline
S.D. & 0.565006439077867 \tabularnewline
T-STAT & 1.88623839088971 \tabularnewline
p-value & 0.132324083791023 \tabularnewline
Lambda & -0.0657368364885582 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76108&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.11746939964891[/C][/ROW]
[ROW][C]beta[/C][C]1.06573683648856[/C][/ROW]
[ROW][C]S.D.[/C][C]0.565006439077867[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.88623839088971[/C][/ROW]
[ROW][C]p-value[/C][C]0.132324083791023[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0657368364885582[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76108&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76108&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-3.11746939964891
beta1.06573683648856
S.D.0.565006439077867
T-STAT1.88623839088971
p-value0.132324083791023
Lambda-0.0657368364885582


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')