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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 computationThu, 20 Nov 2014 21:38:40 +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/20/t14165195363pom65cy8wxvejg.htm/, Retrieved Sun, 19 May 2024 13:04:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257464, Retrieved Sun, 19 May 2024 13:04:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact55

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] [] [2014-11-20 21:38:40] [d67845bcf6d8dd3cd224f69460cf281c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11201
7804
8918
7874
8374
9099
7860
8000
7930
9079
8620
2513
13991
10095
11445
8792
8716
9607
7843
7221
8242
8839
6874
2478
11351
6480
6809
5464
4791
5179
4605
3809
5366
4402
4225
1719
7064
4820
6150
4971
4295
5713
4588
4253
5275
5114
5450
2088
9228
6060
7322
6147
6102
5988
5095
4971
5883
6211
6352
2581
9787
6187
7456
5127
5615
6243
5161
5439
4939
5349
4959
3080
7695
4965
6179
5166
5012
5094
4855
4272
4658
5146
5346
6009

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257464&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257464&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257464&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
181062000.831009174128688
28678.583333333332755.1626072564611513
353502297.246414930089632
44981.751210.403848834234976
559951536.012133001326647
65778.51625.232151249346707
75366.41666666667899.8373043180773423

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8106 & 2000.83100917412 & 8688 \tabularnewline
2 & 8678.58333333333 & 2755.16260725646 & 11513 \tabularnewline
3 & 5350 & 2297.24641493008 & 9632 \tabularnewline
4 & 4981.75 & 1210.40384883423 & 4976 \tabularnewline
5 & 5995 & 1536.01213300132 & 6647 \tabularnewline
6 & 5778.5 & 1625.23215124934 & 6707 \tabularnewline
7 & 5366.41666666667 & 899.837304318077 & 3423 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257464&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]8106[/C][C]2000.83100917412[/C][C]8688[/C][/ROW]
[ROW][C]2[/C][C]8678.58333333333[/C][C]2755.16260725646[/C][C]11513[/C][/ROW]
[ROW][C]3[/C][C]5350[/C][C]2297.24641493008[/C][C]9632[/C][/ROW]
[ROW][C]4[/C][C]4981.75[/C][C]1210.40384883423[/C][C]4976[/C][/ROW]
[ROW][C]5[/C][C]5995[/C][C]1536.01213300132[/C][C]6647[/C][/ROW]
[ROW][C]6[/C][C]5778.5[/C][C]1625.23215124934[/C][C]6707[/C][/ROW]
[ROW][C]7[/C][C]5366.41666666667[/C][C]899.837304318077[/C][C]3423[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257464&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257464&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
181062000.831009174128688
28678.583333333332755.1626072564611513
353502297.246414930089632
44981.751210.403848834234976
559951536.012133001326647
65778.51625.232151249346707
75366.41666666667899.8373043180773423






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-195.262070348978
beta0.309370088093918
S.D.0.138268671217998
T-STAT2.23745614511734
p-value0.0754552015941549

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -195.262070348978 \tabularnewline
beta & 0.309370088093918 \tabularnewline
S.D. & 0.138268671217998 \tabularnewline
T-STAT & 2.23745614511734 \tabularnewline
p-value & 0.0754552015941549 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257464&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-195.262070348978[/C][/ROW]
[ROW][C]beta[/C][C]0.309370088093918[/C][/ROW]
[ROW][C]S.D.[/C][C]0.138268671217998[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.23745614511734[/C][/ROW]
[ROW][C]p-value[/C][C]0.0754552015941549[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257464&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257464&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-195.262070348978
beta0.309370088093918
S.D.0.138268671217998
T-STAT2.23745614511734
p-value0.0754552015941549






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.95127460391771
beta1.18712581133335
S.D.0.585013515492465
T-STAT2.02922800908972
p-value0.0982077824377758
Lambda-0.187125811333354

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.95127460391771 \tabularnewline
beta & 1.18712581133335 \tabularnewline
S.D. & 0.585013515492465 \tabularnewline
T-STAT & 2.02922800908972 \tabularnewline
p-value & 0.0982077824377758 \tabularnewline
Lambda & -0.187125811333354 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257464&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.95127460391771[/C][/ROW]
[ROW][C]beta[/C][C]1.18712581133335[/C][/ROW]
[ROW][C]S.D.[/C][C]0.585013515492465[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.02922800908972[/C][/ROW]
[ROW][C]p-value[/C][C]0.0982077824377758[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.187125811333354[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257464&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257464&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-2.95127460391771
beta1.18712581133335
S.D.0.585013515492465
T-STAT2.02922800908972
p-value0.0982077824377758
Lambda-0.187125811333354


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 <- '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')