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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 computationSun, 16 Aug 2015 10:08:27 +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/2015/Aug/16/t1439716149chqsmhjyg9r7gxu.htm/, Retrieved Sat, 18 May 2024 19:10:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280107, Retrieved Sat, 18 May 2024 19:10:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

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] [spreidings- en ge...] [2015-08-16 09:08:27] [0d8529ada52922935dd1fcf0fb375c74] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
133448.00
132951.00
132447.00
131404.00
141722.00
141176.00
133448.00
128310.00
128807.00
128807.00
129360.00
130354.00
131901.00
131901.00
130907.00
128310.00
141722.00
143766.00
140679.00
133448.00
136542.00
131901.00
133994.00
134995.00
136038.00
133448.00
133994.00
130354.00
141722.00
145313.00
142226.00
136542.00
142723.00
136038.00
142226.00
141722.00
143269.00
137585.00
143766.00
143269.00
152544.00
150451.00
142226.00
138082.00
143766.00
136038.00
141722.00
142723.00
144816.00
140182.00
142723.00
144270.00
149954.00
145313.00
139132.00
132447.00
138635.00
121625.00
129857.00
134491.00
139132.00
132447.00
132447.00
132447.00
136038.00
130907.00
124173.00
118538.00
122626.00
106666.00
116445.00
122129.00
123172.00
117488.00
117985.00
116445.00
121625.00
117985.00
110810.00
105623.00
114394.00
95347.00
107716.00
113351.00
113351.00
106666.00
100485.00
99988.00
105623.00
100485.00
90713.00
83979.00
91210.00
74207.00
89663.00
97888.00
100485.00
94801.00
87619.00
92757.00
94801.00
93254.00
77791.00
70616.00
75747.00
60291.00
76251.00
81935.00
86569.00
78841.00
71610.00
75747.00
77791.00
73703.00
58247.00
51513.00
57694.00
40691.00
59241.00
70616.00

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'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280107&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280107&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280107&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'Gwilym Jenkins' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1132686.1666666674496.5108864001613412
2135005.54771.1004924535915456
3138528.8333333334679.8421658181714959
4142953.4166666674788.1009038189216506
5138620.4166666677884.8549010496128329
6126166.259400.864303833532466
7113495.0833333337731.0546670652627825
896188.166666666710775.352648380939144
983862.333333333312032.126618752740194
1066855.2513316.245861387145878

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 132686.166666667 & 4496.51088640016 & 13412 \tabularnewline
2 & 135005.5 & 4771.10049245359 & 15456 \tabularnewline
3 & 138528.833333333 & 4679.84216581817 & 14959 \tabularnewline
4 & 142953.416666667 & 4788.10090381892 & 16506 \tabularnewline
5 & 138620.416666667 & 7884.85490104961 & 28329 \tabularnewline
6 & 126166.25 & 9400.8643038335 & 32466 \tabularnewline
7 & 113495.083333333 & 7731.05466706526 & 27825 \tabularnewline
8 & 96188.1666666667 & 10775.3526483809 & 39144 \tabularnewline
9 & 83862.3333333333 & 12032.1266187527 & 40194 \tabularnewline
10 & 66855.25 & 13316.2458613871 & 45878 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280107&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]132686.166666667[/C][C]4496.51088640016[/C][C]13412[/C][/ROW]
[ROW][C]2[/C][C]135005.5[/C][C]4771.10049245359[/C][C]15456[/C][/ROW]
[ROW][C]3[/C][C]138528.833333333[/C][C]4679.84216581817[/C][C]14959[/C][/ROW]
[ROW][C]4[/C][C]142953.416666667[/C][C]4788.10090381892[/C][C]16506[/C][/ROW]
[ROW][C]5[/C][C]138620.416666667[/C][C]7884.85490104961[/C][C]28329[/C][/ROW]
[ROW][C]6[/C][C]126166.25[/C][C]9400.8643038335[/C][C]32466[/C][/ROW]
[ROW][C]7[/C][C]113495.083333333[/C][C]7731.05466706526[/C][C]27825[/C][/ROW]
[ROW][C]8[/C][C]96188.1666666667[/C][C]10775.3526483809[/C][C]39144[/C][/ROW]
[ROW][C]9[/C][C]83862.3333333333[/C][C]12032.1266187527[/C][C]40194[/C][/ROW]
[ROW][C]10[/C][C]66855.25[/C][C]13316.2458613871[/C][C]45878[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280107&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280107&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
1132686.1666666674496.5108864001613412
2135005.54771.1004924535915456
3138528.8333333334679.8421658181714959
4142953.4166666674788.1009038189216506
5138620.4166666677884.8549010496128329
6126166.259400.864303833532466
7113495.0833333337731.0546670652627825
896188.166666666710775.352648380939144
983862.333333333312032.126618752740194
1066855.2513316.245861387145878






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha21275.7152457858
beta-0.113151792219188
S.D.0.0185894327362386
T-STAT-6.08688784777213
p-value0.000293686871073618

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 21275.7152457858 \tabularnewline
beta & -0.113151792219188 \tabularnewline
S.D. & 0.0185894327362386 \tabularnewline
T-STAT & -6.08688784777213 \tabularnewline
p-value & 0.000293686871073618 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280107&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]21275.7152457858[/C][/ROW]
[ROW][C]beta[/C][C]-0.113151792219188[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0185894327362386[/C][/ROW]
[ROW][C]T-STAT[/C][C]-6.08688784777213[/C][/ROW]
[ROW][C]p-value[/C][C]0.000293686871073618[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280107&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280107&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)
alpha21275.7152457858
beta-0.113151792219188
S.D.0.0185894327362386
T-STAT-6.08688784777213
p-value0.000293686871073618






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha25.0463413102424
beta-1.38589065989076
S.D.0.316605261909548
T-STAT-4.37734563074539
p-value0.00235715681397519
Lambda2.38589065989076

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 25.0463413102424 \tabularnewline
beta & -1.38589065989076 \tabularnewline
S.D. & 0.316605261909548 \tabularnewline
T-STAT & -4.37734563074539 \tabularnewline
p-value & 0.00235715681397519 \tabularnewline
Lambda & 2.38589065989076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280107&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]25.0463413102424[/C][/ROW]
[ROW][C]beta[/C][C]-1.38589065989076[/C][/ROW]
[ROW][C]S.D.[/C][C]0.316605261909548[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.37734563074539[/C][/ROW]
[ROW][C]p-value[/C][C]0.00235715681397519[/C][/ROW]
[ROW][C]Lambda[/C][C]2.38589065989076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280107&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280107&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)
alpha25.0463413102424
beta-1.38589065989076
S.D.0.316605261909548
T-STAT-4.37734563074539
p-value0.00235715681397519
Lambda2.38589065989076


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')