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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, 13 May 2016 17:43:44 +0100
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/May/13/t1463157858w3qyprdqbigar4g.htm/, Retrieved Sat, 04 May 2024 01:50:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295364, Retrieved Sat, 04 May 2024 01:50:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

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] [SD mean plot] [2016-05-13 16:43:44] [4e1138fa3bff5f7fc8fdb388bb0b126b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99.13
100.46
101.83
100.82
100.99
99.11
98.99
99.8
100.3
101.56
98.83
101.29
98.24
98.37
99.68
97.8
98.34
98.06
97.19
99.44
99.04
100.81
98.49
101.03
98.59
101.07
99.28
101.65
100.59
101.84
100.27
100.04
97.78
97.59
97.68
100.56
98.9
100.08
101.7
100.9
100.67
100.51
100.01
99.8
97.7
98.14
101.77
99.82
100.03
101.83
98.25
99.88
98.96
98.37
97.52
99.59
97.99
100.68
100.39
99.31
96.93
102.06
97.9
102.29
100.55
100.77
100.68
100.75
100.21
99.85
100.59
101.45

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' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295364&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295364&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295364&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' @ yule.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1100.2591666666671.069098671637463
298.87416666666671.172971815001493.84
399.7451.532505375935994.25
41001.264206542388624.06999999999999
599.41.253881247095674.31
6100.3358333333331.549389664782025.36

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.259166666667 & 1.06909867163746 & 3 \tabularnewline
2 & 98.8741666666667 & 1.17297181500149 & 3.84 \tabularnewline
3 & 99.745 & 1.53250537593599 & 4.25 \tabularnewline
4 & 100 & 1.26420654238862 & 4.06999999999999 \tabularnewline
5 & 99.4 & 1.25388124709567 & 4.31 \tabularnewline
6 & 100.335833333333 & 1.54938966478202 & 5.36 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295364&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]100.259166666667[/C][C]1.06909867163746[/C][C]3[/C][/ROW]
[ROW][C]2[/C][C]98.8741666666667[/C][C]1.17297181500149[/C][C]3.84[/C][/ROW]
[ROW][C]3[/C][C]99.745[/C][C]1.53250537593599[/C][C]4.25[/C][/ROW]
[ROW][C]4[/C][C]100[/C][C]1.26420654238862[/C][C]4.06999999999999[/C][/ROW]
[ROW][C]5[/C][C]99.4[/C][C]1.25388124709567[/C][C]4.31[/C][/ROW]
[ROW][C]6[/C][C]100.335833333333[/C][C]1.54938966478202[/C][C]5.36[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295364&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295364&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
1100.2591666666671.069098671637463
298.87416666666671.172971815001493.84
399.7451.532505375935994.25
41001.264206542388624.06999999999999
599.41.253881247095674.31
6100.3358333333331.549389664782025.36






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-8.01312026484302
beta0.0934170589668626
S.D.0.168006326363727
T-STAT0.556032983928344
p-value0.607822998017651

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -8.01312026484302 \tabularnewline
beta & 0.0934170589668626 \tabularnewline
S.D. & 0.168006326363727 \tabularnewline
T-STAT & 0.556032983928344 \tabularnewline
p-value & 0.607822998017651 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295364&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.01312026484302[/C][/ROW]
[ROW][C]beta[/C][C]0.0934170589668626[/C][/ROW]
[ROW][C]S.D.[/C][C]0.168006326363727[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.556032983928344[/C][/ROW]
[ROW][C]p-value[/C][C]0.607822998017651[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295364&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295364&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-8.01312026484302
beta0.0934170589668626
S.D.0.168006326363727
T-STAT0.556032983928344
p-value0.607822998017651






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-28.9218806150522
beta6.33966971600647
S.D.12.7928102033862
T-STAT0.495565056872993
p-value0.646192111307366
Lambda-5.33966971600647

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -28.9218806150522 \tabularnewline
beta & 6.33966971600647 \tabularnewline
S.D. & 12.7928102033862 \tabularnewline
T-STAT & 0.495565056872993 \tabularnewline
p-value & 0.646192111307366 \tabularnewline
Lambda & -5.33966971600647 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295364&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-28.9218806150522[/C][/ROW]
[ROW][C]beta[/C][C]6.33966971600647[/C][/ROW]
[ROW][C]S.D.[/C][C]12.7928102033862[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.495565056872993[/C][/ROW]
[ROW][C]p-value[/C][C]0.646192111307366[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.33966971600647[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295364&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295364&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-28.9218806150522
beta6.33966971600647
S.D.12.7928102033862
T-STAT0.495565056872993
p-value0.646192111307366
Lambda-5.33966971600647


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')