Free Statistics

of Irreproducible Research!

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 computationTue, 07 Dec 2010 17:30:24 +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/2010/Dec/07/t1291742913hqqquekc2a96tlq.htm/, Retrieved Fri, 03 May 2024 16:26:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106550, Retrieved Fri, 03 May 2024 16:26:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
-   PD    [Standard Deviation-Mean Plot] [WS9 - Standard De...] [2010-12-04 11:23:29] [8ef49741e164ec6343c90c7935194465]
-   P         [Standard Deviation-Mean Plot] [WS 9 ] [2010-12-07 17:30:24] [b47314d83d48c7bf812ec2bcd743b159] [Current]
-    D          [Standard Deviation-Mean Plot] [paper standard de...] [2010-12-10 11:40:00] [8214fe6d084e5ad7598b249a26cc9f06]
-    D            [Standard Deviation-Mean Plot] [standard deviatio...] [2010-12-20 20:53:15] [8214fe6d084e5ad7598b249a26cc9f06]
-    D              [Standard Deviation-Mean Plot] [standard deviatio...] [2010-12-22 13:50:12] [8214fe6d084e5ad7598b249a26cc9f06]
Feedback Forum

Post a new message
Dataseries X:
167.16
179.84
174.44
180.35
193.17
195.16
202.43
189.91
195.98
212.09
205.81
204.31
196.07
199.98
199.1
198.31
195.72
223.04
238.41
259.73
326.54
335.15
321.81
368.62
369.59
425
439.72
362.23
328.76
348.55
328.18
329.34
295.55
237.38
226.85
220.14
239.36
224.69
230.98
233.47
256.7
253.41
224.95
210.37
191.09
198.85
211.04
206.25
201.19
194.37
191.08
192.87
181.61
157.67
196.14
246.35
271.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 16 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106550&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]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106550&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106550&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'George Udny Yule' @ 72.249.76.132







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1191.72083333333313.798024534715344.93
2255.20666666666765.0777398519834172.9
3325.94083333333371.538733622656219.58
4223.4320.649544128800365.61

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 191.720833333333 & 13.7980245347153 & 44.93 \tabularnewline
2 & 255.206666666667 & 65.0777398519834 & 172.9 \tabularnewline
3 & 325.940833333333 & 71.538733622656 & 219.58 \tabularnewline
4 & 223.43 & 20.6495441288003 & 65.61 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106550&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]191.720833333333[/C][C]13.7980245347153[/C][C]44.93[/C][/ROW]
[ROW][C]2[/C][C]255.206666666667[/C][C]65.0777398519834[/C][C]172.9[/C][/ROW]
[ROW][C]3[/C][C]325.940833333333[/C][C]71.538733622656[/C][C]219.58[/C][/ROW]
[ROW][C]4[/C][C]223.43[/C][C]20.6495441288003[/C][C]65.61[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106550&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106550&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
1191.72083333333313.798024534715344.93
2255.20666666666765.0777398519834172.9
3325.94083333333371.538733622656219.58
4223.4320.649544128800365.61







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-72.4685185318099
beta0.462650694921094
S.D.0.164648184697435
T-STAT2.80993498817665
p-value0.106751590465350

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -72.4685185318099 \tabularnewline
beta & 0.462650694921094 \tabularnewline
S.D. & 0.164648184697435 \tabularnewline
T-STAT & 2.80993498817665 \tabularnewline
p-value & 0.106751590465350 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106550&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-72.4685185318099[/C][/ROW]
[ROW][C]beta[/C][C]0.462650694921094[/C][/ROW]
[ROW][C]S.D.[/C][C]0.164648184697435[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.80993498817665[/C][/ROW]
[ROW][C]p-value[/C][C]0.106751590465350[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106550&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106550&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)
alpha-72.4685185318099
beta0.462650694921094
S.D.0.164648184697435
T-STAT2.80993498817665
p-value0.106751590465350







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-14.8075827936529
beta3.33402797917676
S.D.1.07393909965064
T-STAT3.10448514283664
p-value0.0899743812925577
Lambda-2.33402797917676

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -14.8075827936529 \tabularnewline
beta & 3.33402797917676 \tabularnewline
S.D. & 1.07393909965064 \tabularnewline
T-STAT & 3.10448514283664 \tabularnewline
p-value & 0.0899743812925577 \tabularnewline
Lambda & -2.33402797917676 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106550&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-14.8075827936529[/C][/ROW]
[ROW][C]beta[/C][C]3.33402797917676[/C][/ROW]
[ROW][C]S.D.[/C][C]1.07393909965064[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.10448514283664[/C][/ROW]
[ROW][C]p-value[/C][C]0.0899743812925577[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.33402797917676[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106550&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106550&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-14.8075827936529
beta3.33402797917676
S.D.1.07393909965064
T-STAT3.10448514283664
p-value0.0899743812925577
Lambda-2.33402797917676



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')