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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 computationTue, 22 Mar 2016 08:08:56 +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/2016/Mar/22/t1458634204p6w16k5dbpx67cb.htm/, Retrieved Mon, 29 Apr 2024 09:13:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294426, Retrieved Mon, 29 Apr 2024 09:13:58 +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] [range-mean plot -...] [2016-03-22 08:08:56] [544b481aaa38f6ceeb4c090a83033a19] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.9
2
2
1.8
1.6
1.4
0.2
0.3
0.4
0.7
1
1.1
0.8
0.8
1
1.1
1
0.8
1.6
1.5
1.6
1.6
1.6
1.9
2
1.9
2
2.1
2.3
2.3
2.6
2.6
2.7
2.6
2.6
2.4
2.5
2.5
2.5
2.4
2.1
2.1
2.3
2.3
2.3
2.9
2.8
2.9
3
3
2.9
2.6
2.8
2.9
3.1
2.8
2.4
1.6
1.5
1.7
1.4
1.1
0.8
1.2
0.8
0.9
0.9
1
0.9
1.1
1
0.7
0
0.2
0.4
0.6
1.1
1
1
0.8
0.6
0.6
0.7
0.7

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'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=294426&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=294426&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294426&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 Maurice George Kendall' @ kendall.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.20.6795720578556641.8
21.2750.3957156922474891.1
32.341666666666670.2843120351538660.8
42.466666666666670.2774341308665840.8
52.5250.589491306127581.6
60.9833333333333330.1946247360403810.7
70.6416666666666670.3260182184907441.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.2 & 0.679572057855664 & 1.8 \tabularnewline
2 & 1.275 & 0.395715692247489 & 1.1 \tabularnewline
3 & 2.34166666666667 & 0.284312035153866 & 0.8 \tabularnewline
4 & 2.46666666666667 & 0.277434130866584 & 0.8 \tabularnewline
5 & 2.525 & 0.58949130612758 & 1.6 \tabularnewline
6 & 0.983333333333333 & 0.194624736040381 & 0.7 \tabularnewline
7 & 0.641666666666667 & 0.326018218490744 & 1.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294426&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]1.2[/C][C]0.679572057855664[/C][C]1.8[/C][/ROW]
[ROW][C]2[/C][C]1.275[/C][C]0.395715692247489[/C][C]1.1[/C][/ROW]
[ROW][C]3[/C][C]2.34166666666667[/C][C]0.284312035153866[/C][C]0.8[/C][/ROW]
[ROW][C]4[/C][C]2.46666666666667[/C][C]0.277434130866584[/C][C]0.8[/C][/ROW]
[ROW][C]5[/C][C]2.525[/C][C]0.58949130612758[/C][C]1.6[/C][/ROW]
[ROW][C]6[/C][C]0.983333333333333[/C][C]0.194624736040381[/C][C]0.7[/C][/ROW]
[ROW][C]7[/C][C]0.641666666666667[/C][C]0.326018218490744[/C][C]1.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294426&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294426&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
11.20.6795720578556641.8
21.2750.3957156922474891.1
32.341666666666670.2843120351538660.8
42.466666666666670.2774341308665840.8
52.5250.589491306127581.6
60.9833333333333330.1946247360403810.7
70.6416666666666670.3260182184907441.1






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.360727638159738
beta0.0194234439939481
S.D.0.100718578044692
T-STAT0.192848671724986
p-value0.854666112951204

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.360727638159738 \tabularnewline
beta & 0.0194234439939481 \tabularnewline
S.D. & 0.100718578044692 \tabularnewline
T-STAT & 0.192848671724986 \tabularnewline
p-value & 0.854666112951204 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294426&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.360727638159738[/C][/ROW]
[ROW][C]beta[/C][C]0.0194234439939481[/C][/ROW]
[ROW][C]S.D.[/C][C]0.100718578044692[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.192848671724986[/C][/ROW]
[ROW][C]p-value[/C][C]0.854666112951204[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294426&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294426&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)
alpha0.360727638159738
beta0.0194234439939481
S.D.0.100718578044692
T-STAT0.192848671724986
p-value0.854666112951204






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.06673195633991
beta0.123996186986681
S.D.0.367853589613829
T-STAT0.337080269127865
p-value0.749745331450271
Lambda0.876003813013319

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.06673195633991 \tabularnewline
beta & 0.123996186986681 \tabularnewline
S.D. & 0.367853589613829 \tabularnewline
T-STAT & 0.337080269127865 \tabularnewline
p-value & 0.749745331450271 \tabularnewline
Lambda & 0.876003813013319 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294426&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.06673195633991[/C][/ROW]
[ROW][C]beta[/C][C]0.123996186986681[/C][/ROW]
[ROW][C]S.D.[/C][C]0.367853589613829[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.337080269127865[/C][/ROW]
[ROW][C]p-value[/C][C]0.749745331450271[/C][/ROW]
[ROW][C]Lambda[/C][C]0.876003813013319[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294426&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294426&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-1.06673195633991
beta0.123996186986681
S.D.0.367853589613829
T-STAT0.337080269127865
p-value0.749745331450271
Lambda0.876003813013319


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')