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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 computationFri, 21 Nov 2014 18:10:40 +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/21/t1416593464i754pi5kgi9dq0y.htm/, Retrieved Sun, 19 May 2024 13:56:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257697, Retrieved Sun, 19 May 2024 13:56:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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] [] [2014-11-21 18:10:40] [12470bd120139be5e23c611c04d9c0dc] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
790
766
1040
2596
949
758
1023
2730
921
775
907
2603
835
871
836
2542
10471
789
811
996
2596
778
603
990
2371
735
800
706
2241
766
870
647
2283
9491
726
784
884
2394
696
893
674
2263
703
799
793
2295
799
1022
758
2579
9531
1021
944
915
2880
864
1022
891
2777
1087
822
890
2799
1092
967
833
2892
11348
1104
1063
1103
3270
1039
1185
1047
3271
1155
878
879
2912
1133
920
943
2996
12449

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=257697&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=257697&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257697&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
11321.5803.2345406372461972
21926.52774.592631851989868
31868.333333333332497.808433346518844
41184.58333333333690.3568850876181720
52105.752475.313207913848773
62348.583333333332974.6285469658610526
71529.83333333333931.6341296427222393

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1321.5 & 803.234540637246 & 1972 \tabularnewline
2 & 1926.5 & 2774.59263185198 & 9868 \tabularnewline
3 & 1868.33333333333 & 2497.80843334651 & 8844 \tabularnewline
4 & 1184.58333333333 & 690.356885087618 & 1720 \tabularnewline
5 & 2105.75 & 2475.31320791384 & 8773 \tabularnewline
6 & 2348.58333333333 & 2974.62854696586 & 10526 \tabularnewline
7 & 1529.83333333333 & 931.634129642722 & 2393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257697&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]1321.5[/C][C]803.234540637246[/C][C]1972[/C][/ROW]
[ROW][C]2[/C][C]1926.5[/C][C]2774.59263185198[/C][C]9868[/C][/ROW]
[ROW][C]3[/C][C]1868.33333333333[/C][C]2497.80843334651[/C][C]8844[/C][/ROW]
[ROW][C]4[/C][C]1184.58333333333[/C][C]690.356885087618[/C][C]1720[/C][/ROW]
[ROW][C]5[/C][C]2105.75[/C][C]2475.31320791384[/C][C]8773[/C][/ROW]
[ROW][C]6[/C][C]2348.58333333333[/C][C]2974.62854696586[/C][C]10526[/C][/ROW]
[ROW][C]7[/C][C]1529.83333333333[/C][C]931.634129642722[/C][C]2393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257697&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257697&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
11321.5803.2345406372461972
21926.52774.592631851989868
31868.333333333332497.808433346518844
41184.58333333333690.3568850876181720
52105.752475.313207913848773
62348.583333333332974.6285469658610526
71529.83333333333931.6341296427222393






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2082.33900814767
beta2.25671578126423
S.D.0.359822893180199
T-STAT6.27174041462133
p-value0.0015128316143675

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2082.33900814767 \tabularnewline
beta & 2.25671578126423 \tabularnewline
S.D. & 0.359822893180199 \tabularnewline
T-STAT & 6.27174041462133 \tabularnewline
p-value & 0.0015128316143675 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257697&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2082.33900814767[/C][/ROW]
[ROW][C]beta[/C][C]2.25671578126423[/C][/ROW]
[ROW][C]S.D.[/C][C]0.359822893180199[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.27174041462133[/C][/ROW]
[ROW][C]p-value[/C][C]0.0015128316143675[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257697&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257697&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-2082.33900814767
beta2.25671578126423
S.D.0.359822893180199
T-STAT6.27174041462133
p-value0.0015128316143675






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-11.0363829702038
beta2.47339699327129
S.D.0.346237093481804
T-STAT7.14365109872689
p-value0.000834807432966823
Lambda-1.47339699327129

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -11.0363829702038 \tabularnewline
beta & 2.47339699327129 \tabularnewline
S.D. & 0.346237093481804 \tabularnewline
T-STAT & 7.14365109872689 \tabularnewline
p-value & 0.000834807432966823 \tabularnewline
Lambda & -1.47339699327129 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257697&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-11.0363829702038[/C][/ROW]
[ROW][C]beta[/C][C]2.47339699327129[/C][/ROW]
[ROW][C]S.D.[/C][C]0.346237093481804[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.14365109872689[/C][/ROW]
[ROW][C]p-value[/C][C]0.000834807432966823[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.47339699327129[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257697&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257697&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-11.0363829702038
beta2.47339699327129
S.D.0.346237093481804
T-STAT7.14365109872689
p-value0.000834807432966823
Lambda-1.47339699327129


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')