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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 21 Dec 2009 06:17:50 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/21/t12614015294vlgu06zn9v5hge.htm/, Retrieved Sun, 05 May 2024 08:59:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70145, Retrieved Sun, 05 May 2024 08:59:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

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] [Standard deviatio...] [2008-12-11 16:40:34] [12d343c4448a5f9e527bb31caeac580b]
-  M D  [Standard Deviation-Mean Plot] [Standard Deviatio...] [2009-12-18 19:32:26] [976efdaed7598845c859b86bc2e467ce]
-    D      [Standard Deviation-Mean Plot] [Standard Deviatio...] [2009-12-21 13:17:50] [d45d8d97b86162be82506c3c0ea6e4a6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
168802
173276
172957
173558
173820
171663
174110
174338
175440
174922
172188
171330
169560
174579
173740
173427
172952
170305
172717
173019
173690
172439
171914
171968
169500
173898
172308
171568
164939
161275
160770
162466
160185
154836
154103
150495
142707
149962
149967
144572
143819
141070
144119
145330
143279
139063
139202
133632
134476
141859
140693
138047
138346
140167
146796
152228
155410
159032
160312
157687
160141
167421
167628
164403
163405

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70145&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70145&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70145&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1173033.6666666671823.513907184966638
2172525.8333333331437.794449421715019
3163028.5833333337646.4860908706823403
4143060.1666666674556.3231355064716335
5147087.759337.1017318009325836

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 173033.666666667 & 1823.51390718496 & 6638 \tabularnewline
2 & 172525.833333333 & 1437.79444942171 & 5019 \tabularnewline
3 & 163028.583333333 & 7646.48609087068 & 23403 \tabularnewline
4 & 143060.166666667 & 4556.32313550647 & 16335 \tabularnewline
5 & 147087.75 & 9337.10173180093 & 25836 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70145&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]173033.666666667[/C][C]1823.51390718496[/C][C]6638[/C][/ROW]
[ROW][C]2[/C][C]172525.833333333[/C][C]1437.79444942171[/C][C]5019[/C][/ROW]
[ROW][C]3[/C][C]163028.583333333[/C][C]7646.48609087068[/C][C]23403[/C][/ROW]
[ROW][C]4[/C][C]143060.166666667[/C][C]4556.32313550647[/C][C]16335[/C][/ROW]
[ROW][C]5[/C][C]147087.75[/C][C]9337.10173180093[/C][C]25836[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70145&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70145&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
1173033.6666666671823.513907184966638
2172525.8333333331437.794449421715019
3163028.5833333337646.4860908706823403
4143060.1666666674556.3231355064716335
5147087.759337.1017318009325836






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha30570.8681664972
beta-0.160319707034240
S.D.0.109699257498429
T-STAT-1.46144751286521
p-value0.240044406712620

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 30570.8681664972 \tabularnewline
beta & -0.160319707034240 \tabularnewline
S.D. & 0.109699257498429 \tabularnewline
T-STAT & -1.46144751286521 \tabularnewline
p-value & 0.240044406712620 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70145&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]30570.8681664972[/C][/ROW]
[ROW][C]beta[/C][C]-0.160319707034240[/C][/ROW]
[ROW][C]S.D.[/C][C]0.109699257498429[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.46144751286521[/C][/ROW]
[ROW][C]p-value[/C][C]0.240044406712620[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70145&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70145&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)
alpha30570.8681664972
beta-0.160319707034240
S.D.0.109699257498429
T-STAT-1.46144751286521
p-value0.240044406712620






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha88.9448414962849
beta-6.7361806787366
S.D.3.80656807492717
T-STAT-1.76962044186363
p-value0.174933319934663
Lambda7.7361806787366

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 88.9448414962849 \tabularnewline
beta & -6.7361806787366 \tabularnewline
S.D. & 3.80656807492717 \tabularnewline
T-STAT & -1.76962044186363 \tabularnewline
p-value & 0.174933319934663 \tabularnewline
Lambda & 7.7361806787366 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70145&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]88.9448414962849[/C][/ROW]
[ROW][C]beta[/C][C]-6.7361806787366[/C][/ROW]
[ROW][C]S.D.[/C][C]3.80656807492717[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.76962044186363[/C][/ROW]
[ROW][C]p-value[/C][C]0.174933319934663[/C][/ROW]
[ROW][C]Lambda[/C][C]7.7361806787366[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70145&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70145&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)
alpha88.9448414962849
beta-6.7361806787366
S.D.3.80656807492717
T-STAT-1.76962044186363
p-value0.174933319934663
Lambda7.7361806787366


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')