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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 12 May 2008 03:41:26 -0600
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/May/12/t1210585313hqj4a8z1300vsjb.htm/, Retrieved Mon, 20 May 2024 03:25:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12318, Retrieved Mon, 20 May 2024 03:25:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180

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] [Niet-werkende wer...] [2008-05-12 09:41:26] [d8973bbb712c03ae516525a15d4e5e48] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7840
8292
8534
8441
8602
8468
8832
9006
8749
8714
8193
8251
8192
9056
9407
9068
9431
9907
10044
10838
10871
11127
11303
11349
11493
12694
13227
12253
12234
12491
13248
14042
14392
14834
15542
15518
16197
17325
24016
23671
24998
25329
25904
26548
26752
26967
27034
27056
27476
28497
29085
28720
29067
29249
29672
29761
30066
30315
30571
30757
30742
31310
31381
31470
31226
31081
31061
31114
30828
30418
30195
29877
29192
29876
29409
28458
28340
28164
28438
28053

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=12318&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=12318&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12318&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
18493.5319.7625539507261166
210049.41666666671041.587028470883157
313497.33333333331351.852287071564049
424316.41666666673719.1170373999810859
529436.3333333333948.416607091033281
630891.9166666667499.122586205641593

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8493.5 & 319.762553950726 & 1166 \tabularnewline
2 & 10049.4166666667 & 1041.58702847088 & 3157 \tabularnewline
3 & 13497.3333333333 & 1351.85228707156 & 4049 \tabularnewline
4 & 24316.4166666667 & 3719.11703739998 & 10859 \tabularnewline
5 & 29436.3333333333 & 948.41660709103 & 3281 \tabularnewline
6 & 30891.9166666667 & 499.12258620564 & 1593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12318&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]8493.5[/C][C]319.762553950726[/C][C]1166[/C][/ROW]
[ROW][C]2[/C][C]10049.4166666667[/C][C]1041.58702847088[/C][C]3157[/C][/ROW]
[ROW][C]3[/C][C]13497.3333333333[/C][C]1351.85228707156[/C][C]4049[/C][/ROW]
[ROW][C]4[/C][C]24316.4166666667[/C][C]3719.11703739998[/C][C]10859[/C][/ROW]
[ROW][C]5[/C][C]29436.3333333333[/C][C]948.41660709103[/C][C]3281[/C][/ROW]
[ROW][C]6[/C][C]30891.9166666667[/C][C]499.12258620564[/C][C]1593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12318&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12318&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
18493.5319.7625539507261166
210049.41666666671041.587028470883157
313497.33333333331351.852287071564049
424316.41666666673719.1170373999810859
529436.3333333333948.416607091033281
630891.9166666667499.122586205641593






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha846.478579232101
beta0.0240047017627717
S.D.0.0607712461678869
T-STAT0.395000979516797
p-value0.713000424914597

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 846.478579232101 \tabularnewline
beta & 0.0240047017627717 \tabularnewline
S.D. & 0.0607712461678869 \tabularnewline
T-STAT & 0.395000979516797 \tabularnewline
p-value & 0.713000424914597 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12318&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]846.478579232101[/C][/ROW]
[ROW][C]beta[/C][C]0.0240047017627717[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0607712461678869[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.395000979516797[/C][/ROW]
[ROW][C]p-value[/C][C]0.713000424914597[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12318&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12318&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)
alpha846.478579232101
beta0.0240047017627717
S.D.0.0607712461678869
T-STAT0.395000979516797
p-value0.713000424914597






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.42231030343295
beta0.45607633466122
S.D.0.71465174499062
T-STAT0.638179837743495
p-value0.558062007850933
Lambda0.54392366533878

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.42231030343295 \tabularnewline
beta & 0.45607633466122 \tabularnewline
S.D. & 0.71465174499062 \tabularnewline
T-STAT & 0.638179837743495 \tabularnewline
p-value & 0.558062007850933 \tabularnewline
Lambda & 0.54392366533878 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12318&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.42231030343295[/C][/ROW]
[ROW][C]beta[/C][C]0.45607633466122[/C][/ROW]
[ROW][C]S.D.[/C][C]0.71465174499062[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.638179837743495[/C][/ROW]
[ROW][C]p-value[/C][C]0.558062007850933[/C][/ROW]
[ROW][C]Lambda[/C][C]0.54392366533878[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12318&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12318&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)
alpha2.42231030343295
beta0.45607633466122
S.D.0.71465174499062
T-STAT0.638179837743495
p-value0.558062007850933
Lambda0.54392366533878


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')