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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 computationSat, 19 Dec 2009 03:15:13 -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/19/t12612177853bgtrz3dbtil0yp.htm/, Retrieved Fri, 03 May 2024 21:49:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69476, Retrieved Fri, 03 May 2024 21:49:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-   PD        [Standard Deviation-Mean Plot] [WS8: SMP] [2009-11-27 19:29:24] [5c968c05ca472afa314d272082b56b09]
-   PD            [Standard Deviation-Mean Plot] [Differentatie - H...] [2009-12-19 10:15:13] [91df150cd527c563f0151b3a845ecd72] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
113
110
107
103
98
98
137
148
147
139
130
128
127
123
118
114
108
111
151
159
158
148
138
137
136
133
126
120
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69476&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]5 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=69476&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69476&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 time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1121.518.768929838238750
2132.66666666666718.391368199305551
313716.53096268439148
4133.33333333333316.188286075449945
5126.514.317821063276439

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 121.5 & 18.7689298382387 & 50 \tabularnewline
2 & 132.666666666667 & 18.3913681993055 & 51 \tabularnewline
3 & 137 & 16.530962684391 & 48 \tabularnewline
4 & 133.333333333333 & 16.1882860754499 & 45 \tabularnewline
5 & 126.5 & 14.3178210632764 & 39 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69476&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]121.5[/C][C]18.7689298382387[/C][C]50[/C][/ROW]
[ROW][C]2[/C][C]132.666666666667[/C][C]18.3913681993055[/C][C]51[/C][/ROW]
[ROW][C]3[/C][C]137[/C][C]16.530962684391[/C][C]48[/C][/ROW]
[ROW][C]4[/C][C]133.333333333333[/C][C]16.1882860754499[/C][C]45[/C][/ROW]
[ROW][C]5[/C][C]126.5[/C][C]14.3178210632764[/C][C]39[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69476&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69476&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
1121.518.768929838238750
2132.66666666666718.391368199305551
313716.53096268439148
4133.33333333333316.188286075449945
5126.514.317821063276439






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha23.5129935923467
beta-0.0512559141337511
S.D.0.166562409208646
T-STAT-0.307727982425764
p-value0.778416609758553

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 23.5129935923467 \tabularnewline
beta & -0.0512559141337511 \tabularnewline
S.D. & 0.166562409208646 \tabularnewline
T-STAT & -0.307727982425764 \tabularnewline
p-value & 0.778416609758553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69476&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]23.5129935923467[/C][/ROW]
[ROW][C]beta[/C][C]-0.0512559141337511[/C][/ROW]
[ROW][C]S.D.[/C][C]0.166562409208646[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.307727982425764[/C][/ROW]
[ROW][C]p-value[/C][C]0.778416609758553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69476&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69476&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)
alpha23.5129935923467
beta-0.0512559141337511
S.D.0.166562409208646
T-STAT-0.307727982425764
p-value0.778416609758553






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.45856004681991
beta-0.336787533756717
S.D.1.30521628411274
T-STAT-0.258031973594062
p-value0.813070910918893
Lambda1.33678753375672

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.45856004681991 \tabularnewline
beta & -0.336787533756717 \tabularnewline
S.D. & 1.30521628411274 \tabularnewline
T-STAT & -0.258031973594062 \tabularnewline
p-value & 0.813070910918893 \tabularnewline
Lambda & 1.33678753375672 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69476&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.45856004681991[/C][/ROW]
[ROW][C]beta[/C][C]-0.336787533756717[/C][/ROW]
[ROW][C]S.D.[/C][C]1.30521628411274[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.258031973594062[/C][/ROW]
[ROW][C]p-value[/C][C]0.813070910918893[/C][/ROW]
[ROW][C]Lambda[/C][C]1.33678753375672[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69476&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69476&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)
alpha4.45856004681991
beta-0.336787533756717
S.D.1.30521628411274
T-STAT-0.258031973594062
p-value0.813070910918893
Lambda1.33678753375672


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')