FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSun, 21 Dec 2008 11:04:34 -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/2008/Dec/21/t1229882748fdha7edjezfm9w1.htm/, Retrieved Sun, 19 May 2024 12:01:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35725, Retrieved Sun, 19 May 2024 12:01:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Paper - Mean plot...] [2008-12-18 11:43:00] [85841a4a203c2f9589565c024425a91b]
- RMPD  [Standard Deviation-Mean Plot] [Paper - Standard ...] [2008-12-21 18:00:45] [85841a4a203c2f9589565c024425a91b]
-           [Standard Deviation-Mean Plot] [Paper - Standard ...] [2008-12-21 18:04:34] [07b7cf1321bc38017c2c7efcf91ca696] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,57
97,74
97,92
98,19
98,23
98,41
98,59
98,71
99,14
99,62
100,18
100,66
101,19
101,75
102,2
102,87
98,81
97,6
96,68
95,96
98,89
99,05
99,2
99,11
99,19
99,77
100,70
100,78
100,53
101,01
100,92
101,10
103,11
102,99
102,31
102,61
103,68
104,72
107,66
108,87
108,12
107,61
106,42
105,61
105,71
105,49
105,57
105,18
106,09
106,34
108,47
116,87
121,08
123,27
124,18
125,60
126,57
127,18
128,04
128,55
129,67

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35725&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35725&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35725&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
198.74666666666670.973749392188713.09000000000000
299.44252.172401791900976.91000000000001
3101.2516666666671.247731274487153.92
4106.221.538860263016405.19
5120.1866666666678.6105456836194222.46

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 98.7466666666667 & 0.97374939218871 & 3.09000000000000 \tabularnewline
2 & 99.4425 & 2.17240179190097 & 6.91000000000001 \tabularnewline
3 & 101.251666666667 & 1.24773127448715 & 3.92 \tabularnewline
4 & 106.22 & 1.53886026301640 & 5.19 \tabularnewline
5 & 120.186666666667 & 8.61054568361942 & 22.46 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35725&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]98.7466666666667[/C][C]0.97374939218871[/C][C]3.09000000000000[/C][/ROW]
[ROW][C]2[/C][C]99.4425[/C][C]2.17240179190097[/C][C]6.91000000000001[/C][/ROW]
[ROW][C]3[/C][C]101.251666666667[/C][C]1.24773127448715[/C][C]3.92[/C][/ROW]
[ROW][C]4[/C][C]106.22[/C][C]1.53886026301640[/C][C]5.19[/C][/ROW]
[ROW][C]5[/C][C]120.186666666667[/C][C]8.61054568361942[/C][C]22.46[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35725&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35725&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
198.74666666666670.973749392188713.09000000000000
299.44252.172401791900976.91000000000001
3101.2516666666671.247731274487153.92
4106.221.538860263016405.19
5120.1866666666678.6105456836194222.46






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-32.8130095181227
beta0.339658049141293
S.D.0.0724333352564316
T-STAT4.68925043888731
p-value0.0183343023416702

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -32.8130095181227 \tabularnewline
beta & 0.339658049141293 \tabularnewline
S.D. & 0.0724333352564316 \tabularnewline
T-STAT & 4.68925043888731 \tabularnewline
p-value & 0.0183343023416702 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35725&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-32.8130095181227[/C][/ROW]
[ROW][C]beta[/C][C]0.339658049141293[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0724333352564316[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.68925043888731[/C][/ROW]
[ROW][C]p-value[/C][C]0.0183343023416702[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35725&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35725&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-32.8130095181227
beta0.339658049141293
S.D.0.0724333352564316
T-STAT4.68925043888731
p-value0.0183343023416702






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-43.5070380583860
beta9.50339070566134
S.D.2.65601059374106
T-STAT3.57806957850856
p-value0.0373374917774791
Lambda-8.50339070566134

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -43.5070380583860 \tabularnewline
beta & 9.50339070566134 \tabularnewline
S.D. & 2.65601059374106 \tabularnewline
T-STAT & 3.57806957850856 \tabularnewline
p-value & 0.0373374917774791 \tabularnewline
Lambda & -8.50339070566134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35725&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-43.5070380583860[/C][/ROW]
[ROW][C]beta[/C][C]9.50339070566134[/C][/ROW]
[ROW][C]S.D.[/C][C]2.65601059374106[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.57806957850856[/C][/ROW]
[ROW][C]p-value[/C][C]0.0373374917774791[/C][/ROW]
[ROW][C]Lambda[/C][C]-8.50339070566134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35725&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35725&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-43.5070380583860
beta9.50339070566134
S.D.2.65601059374106
T-STAT3.57806957850856
p-value0.0373374917774791
Lambda-8.50339070566134


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 12 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')