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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 29 Nov 2007 08:18:01 -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/2007/Nov/29/t11963488873csdfulq4x6nmt1.htm/, Retrieved Fri, 03 May 2024 09:16:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7510, Retrieved Fri, 03 May 2024 09:16:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [US dollar per euro] [2007-11-29 15:18:01] [6c82e325b196f1aec5740f38b2795d46] [Current]
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Dataseries X:
0.8552
0.8564
0.8973
0.9383
0.9217
0.9095
0.892
0.8742
0.8532
0.8607
0.9005
0.9111
0.9059
0.8883
0.8924
0.8833
0.87
0.8758
0.8858
0.917
0.9554
0.9922
0.9778
0.9808
0.9811
1.0014
1.0183
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.202
1.2271
1.277
1.265
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7510&T=0

[TABLE]
[ROW][C]Summary of compuational 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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7510&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7510&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.8891750.02880180313168540.0831
20.9187250.04515488748337620.1358
31.083633333333330.06009093613899360.2739
41.216591666666670.02962534106695370.3813
51.271708333333330.0457043355479410.4708
61.230258333333330.03961033975051860.4053
71.330833333333330.03740870908159640.5038

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.889175 & 0.0288018031316854 & 0.0831 \tabularnewline
2 & 0.918725 & 0.0451548874833762 & 0.1358 \tabularnewline
3 & 1.08363333333333 & 0.0600909361389936 & 0.2739 \tabularnewline
4 & 1.21659166666667 & 0.0296253410669537 & 0.3813 \tabularnewline
5 & 1.27170833333333 & 0.045704335547941 & 0.4708 \tabularnewline
6 & 1.23025833333333 & 0.0396103397505186 & 0.4053 \tabularnewline
7 & 1.33083333333333 & 0.0374087090815964 & 0.5038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7510&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]0.889175[/C][C]0.0288018031316854[/C][C]0.0831[/C][/ROW]
[ROW][C]2[/C][C]0.918725[/C][C]0.0451548874833762[/C][C]0.1358[/C][/ROW]
[ROW][C]3[/C][C]1.08363333333333[/C][C]0.0600909361389936[/C][C]0.2739[/C][/ROW]
[ROW][C]4[/C][C]1.21659166666667[/C][C]0.0296253410669537[/C][C]0.3813[/C][/ROW]
[ROW][C]5[/C][C]1.27170833333333[/C][C]0.045704335547941[/C][C]0.4708[/C][/ROW]
[ROW][C]6[/C][C]1.23025833333333[/C][C]0.0396103397505186[/C][C]0.4053[/C][/ROW]
[ROW][C]7[/C][C]1.33083333333333[/C][C]0.0374087090815964[/C][C]0.5038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7510&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7510&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.8891750.02880180313168540.0831
20.9187250.04515488748337620.1358
31.083633333333330.06009093613899360.2739
41.216591666666670.02962534106695370.3813
51.271708333333330.0457043355479410.4708
61.230258333333330.03961033975051860.4053
71.330833333333330.03740870908159640.5038







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0409236568981205
beta-8.72015360663324e-06
S.D.0.0276253798692586
T-STAT-0.000315657328438657
p-value0.99976034873812

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0409236568981205 \tabularnewline
beta & -8.72015360663324e-06 \tabularnewline
S.D. & 0.0276253798692586 \tabularnewline
T-STAT & -0.000315657328438657 \tabularnewline
p-value & 0.99976034873812 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7510&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0409236568981205[/C][/ROW]
[ROW][C]beta[/C][C]-8.72015360663324e-06[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0276253798692586[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.000315657328438657[/C][/ROW]
[ROW][C]p-value[/C][C]0.99976034873812[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7510&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7510&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0409236568981205
beta-8.72015360663324e-06
S.D.0.0276253798692586
T-STAT-0.000315657328438657
p-value0.99976034873812







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.23859226276959
beta0.116492246114249
S.D.0.71665438313213
T-STAT0.162550106238269
p-value0.87723783691024
Lambda0.88350775388575

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.23859226276959 \tabularnewline
beta & 0.116492246114249 \tabularnewline
S.D. & 0.71665438313213 \tabularnewline
T-STAT & 0.162550106238269 \tabularnewline
p-value & 0.87723783691024 \tabularnewline
Lambda & 0.88350775388575 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7510&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.23859226276959[/C][/ROW]
[ROW][C]beta[/C][C]0.116492246114249[/C][/ROW]
[ROW][C]S.D.[/C][C]0.71665438313213[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.162550106238269[/C][/ROW]
[ROW][C]p-value[/C][C]0.87723783691024[/C][/ROW]
[ROW][C]Lambda[/C][C]0.88350775388575[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7510&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7510&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.23859226276959
beta0.116492246114249
S.D.0.71665438313213
T-STAT0.162550106238269
p-value0.87723783691024
Lambda0.88350775388575



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')