FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Standard Deviation-Mean plot Totaal # niet-werkende werkzoekende vrouwen in...

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 15 Dec 2008 11:06:42 -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/15/t1229365087ugfm8itgbnns5fb.htm/, Retrieved Thu, 16 May 2024 01:22:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33765, Retrieved Thu, 16 May 2024 01:22:00 +0000
QR Codes:

Original text written by user:Seasonal period: 12
IsPrivate?No (this computation is public)
User-defined keywordsStandard Deviation-Mean plot Totaal niet-werkende werkzoekende vrouwen Vlaams gewest
Estimated Impact160

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...] [2008-12-15 18:06:42] [f4b2017b314c03698059f43b95818e67] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
121148
114624
109822
112081
113534
112110
109826
107423
105540
108573
128591
139145
129700
132828
126868
128390
126830
124105
122323
119296
116822
119224
139357
144322
133676
128283
121640
122877
117284
116463
112685
113235
111692
113152
129889
131153
123770
112516
105940
104320
103582
99064
94989
92241
89752
90610
109456
110213
97694
91844
87572
89812
89050
85990
85070
83277
79586
84215
99708
100698
90861
86700

Tables (Output of Computation)





Summary of computational 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 computational 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=33765&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]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=33765&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33765&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1115201.4166666679844.0632636060833605
2127505.4166666678238.383661620827500
3121002.4166666678044.257674756521984
4103037.7510228.338469219234018
5895436762.9917398091921112

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 115201.416666667 & 9844.06326360608 & 33605 \tabularnewline
2 & 127505.416666667 & 8238.3836616208 & 27500 \tabularnewline
3 & 121002.416666667 & 8044.2576747565 & 21984 \tabularnewline
4 & 103037.75 & 10228.3384692192 & 34018 \tabularnewline
5 & 89543 & 6762.99173980919 & 21112 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33765&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]115201.416666667[/C][C]9844.06326360608[/C][C]33605[/C][/ROW]
[ROW][C]2[/C][C]127505.416666667[/C][C]8238.3836616208[/C][C]27500[/C][/ROW]
[ROW][C]3[/C][C]121002.416666667[/C][C]8044.2576747565[/C][C]21984[/C][/ROW]
[ROW][C]4[/C][C]103037.75[/C][C]10228.3384692192[/C][C]34018[/C][/ROW]
[ROW][C]5[/C][C]89543[/C][C]6762.99173980919[/C][C]21112[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33765&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33765&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
1115201.4166666679844.0632636060833605
2127505.4166666678238.383661620827500
3121002.4166666678044.257674756521984
4103037.7510228.338469219234018
5895436762.9917398091921112






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6173.33627102962
beta0.0220233213860822
S.D.0.0525458092458022
T-STAT0.419126124465228
p-value0.703325194329569

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6173.33627102962 \tabularnewline
beta & 0.0220233213860822 \tabularnewline
S.D. & 0.0525458092458022 \tabularnewline
T-STAT & 0.419126124465228 \tabularnewline
p-value & 0.703325194329569 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33765&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6173.33627102962[/C][/ROW]
[ROW][C]beta[/C][C]0.0220233213860822[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0525458092458022[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.419126124465228[/C][/ROW]
[ROW][C]p-value[/C][C]0.703325194329569[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33765&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33765&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)
alpha6173.33627102962
beta0.0220233213860822
S.D.0.0525458092458022
T-STAT0.419126124465228
p-value0.703325194329569






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.41313202895576
beta0.399426070911024
S.D.0.645032105639714
T-STAT0.619234403092062
p-value0.579607154037017
Lambda0.600573929088976

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.41313202895576 \tabularnewline
beta & 0.399426070911024 \tabularnewline
S.D. & 0.645032105639714 \tabularnewline
T-STAT & 0.619234403092062 \tabularnewline
p-value & 0.579607154037017 \tabularnewline
Lambda & 0.600573929088976 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33765&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.41313202895576[/C][/ROW]
[ROW][C]beta[/C][C]0.399426070911024[/C][/ROW]
[ROW][C]S.D.[/C][C]0.645032105639714[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.619234403092062[/C][/ROW]
[ROW][C]p-value[/C][C]0.579607154037017[/C][/ROW]
[ROW][C]Lambda[/C][C]0.600573929088976[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33765&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33765&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)
alpha4.41313202895576
beta0.399426070911024
S.D.0.645032105639714
T-STAT0.619234403092062
p-value0.579607154037017
Lambda0.600573929088976


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')