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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, 12 Mar 2015 07:56:39 +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/2015/Mar/12/t1426147021g0ovsdkhulhpf5s.htm/, Retrieved Fri, 17 May 2024 12:28:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278225, Retrieved Fri, 17 May 2024 12:28:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

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] [] [2015-03-12 07:56:39] [70effeb63bf28517d1b6107bc8921f07] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15071
14236
14771
14804
15597
15418
16903
16350
16393
15685
14556
14850
15391
13704
15409
15098
15254
15522
16669
16238
16246
15424
14952
15008
14929
13905
14994
14753
15031
15386
16160
16116
16219
16064
15436
15404
15112
14119
14775
14289
15121
15371
15782
16104
15674
15105
14223
14385
14558
13804
14672
14244
15089
14580
15218
15696
15129
15110
14204
13655
14534
12746
14074
13699
14184
14110
15820
15362
14993
14437
13694
13688

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=278225&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=278225&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278225&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
115386.1666666667825.4172315021092667
215409.5833333333761.9439800850712965
315366.4166666667698.4631777023472314
415005658.816293886931985
514663.25612.8722431009882041
614278.4166666667831.4804385534093074

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 15386.1666666667 & 825.417231502109 & 2667 \tabularnewline
2 & 15409.5833333333 & 761.943980085071 & 2965 \tabularnewline
3 & 15366.4166666667 & 698.463177702347 & 2314 \tabularnewline
4 & 15005 & 658.81629388693 & 1985 \tabularnewline
5 & 14663.25 & 612.872243100988 & 2041 \tabularnewline
6 & 14278.4166666667 & 831.480438553409 & 3074 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278225&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]15386.1666666667[/C][C]825.417231502109[/C][C]2667[/C][/ROW]
[ROW][C]2[/C][C]15409.5833333333[/C][C]761.943980085071[/C][C]2965[/C][/ROW]
[ROW][C]3[/C][C]15366.4166666667[/C][C]698.463177702347[/C][C]2314[/C][/ROW]
[ROW][C]4[/C][C]15005[/C][C]658.81629388693[/C][C]1985[/C][/ROW]
[ROW][C]5[/C][C]14663.25[/C][C]612.872243100988[/C][C]2041[/C][/ROW]
[ROW][C]6[/C][C]14278.4166666667[/C][C]831.480438553409[/C][C]3074[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278225&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278225&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
115386.1666666667825.4172315021092667
215409.5833333333761.9439800850712965
315366.4166666667698.4631777023472314
415005658.816293886931985
514663.25612.8722431009882041
614278.4166666667831.4804385534093074






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha675.043680784061
beta0.00375913512134204
S.D.0.0962892276113227
T-STAT0.0390400381703758
p-value0.97072926482313

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 675.043680784061 \tabularnewline
beta & 0.00375913512134204 \tabularnewline
S.D. & 0.0962892276113227 \tabularnewline
T-STAT & 0.0390400381703758 \tabularnewline
p-value & 0.97072926482313 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278225&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]675.043680784061[/C][/ROW]
[ROW][C]beta[/C][C]0.00375913512134204[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0962892276113227[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0390400381703758[/C][/ROW]
[ROW][C]p-value[/C][C]0.97072926482313[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278225&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278225&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)
alpha675.043680784061
beta0.00375913512134204
S.D.0.0962892276113227
T-STAT0.0390400381703758
p-value0.97072926482313






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha5.11421155074723
beta0.153331674842187
S.D.1.97891850667586
T-STAT0.0774825614723013
p-value0.941960647384201
Lambda0.846668325157813

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.11421155074723 \tabularnewline
beta & 0.153331674842187 \tabularnewline
S.D. & 1.97891850667586 \tabularnewline
T-STAT & 0.0774825614723013 \tabularnewline
p-value & 0.941960647384201 \tabularnewline
Lambda & 0.846668325157813 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278225&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.11421155074723[/C][/ROW]
[ROW][C]beta[/C][C]0.153331674842187[/C][/ROW]
[ROW][C]S.D.[/C][C]1.97891850667586[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0774825614723013[/C][/ROW]
[ROW][C]p-value[/C][C]0.941960647384201[/C][/ROW]
[ROW][C]Lambda[/C][C]0.846668325157813[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278225&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278225&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)
alpha5.11421155074723
beta0.153331674842187
S.D.1.97891850667586
T-STAT0.0774825614723013
p-value0.941960647384201
Lambda0.846668325157813


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')