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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 computationMon, 22 Dec 2008 09:37:45 -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/22/t1229963894l8ex263rfg6sj1b.htm/, Retrieved Mon, 13 May 2024 18:22:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36134, Retrieved Mon, 13 May 2024 18:22:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148

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...] [2008-12-12 14:14:19] [1ce0d16c8f4225c977b42c8fa93bc163]
-         [Standard Deviation-Mean Plot] [21] [2008-12-22 16:37:45] [d96f761aa3e94002e7c05c3c847d2c79] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9 700
9 081
9 084
9 743
8 587
9 731
9 563
9 998
9 437
10 038
9 918
9 252
9 737
9 035
9 133
9 487
8 700
9 627
8 947
9 283
8 829
9 947
9 628
9 318
9 605
8 640
9 214
9 567
8 547
9 185
9 470
9 123
9 278
10 170
9 434
9 655
9 429
8 739
9 552
9 687
9 019
9 672
9 206
9 069
9 788
10 312
10 105
9 863
9 656
9 295
9 946
9 701
9 049
10 190
9 706
9 765
9 893
9 994
10 433
10 073
10 112
9 266
9 820
10 097
9 115
10 411
9 678
10 408
10 153
10 368
10 581
10 597
10 680
9 738
9 556

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36134&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36134&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36134&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
19511438.4640547099921451
29305.91666666667388.9165506035111247
39324441.3024112576521623
49536.75465.0368753707021573
59808.41666666667375.825505528911384
610050.5489.6754955162561482

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9511 & 438.464054709992 & 1451 \tabularnewline
2 & 9305.91666666667 & 388.916550603511 & 1247 \tabularnewline
3 & 9324 & 441.302411257652 & 1623 \tabularnewline
4 & 9536.75 & 465.036875370702 & 1573 \tabularnewline
5 & 9808.41666666667 & 375.82550552891 & 1384 \tabularnewline
6 & 10050.5 & 489.675495516256 & 1482 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36134&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]9511[/C][C]438.464054709992[/C][C]1451[/C][/ROW]
[ROW][C]2[/C][C]9305.91666666667[/C][C]388.916550603511[/C][C]1247[/C][/ROW]
[ROW][C]3[/C][C]9324[/C][C]441.302411257652[/C][C]1623[/C][/ROW]
[ROW][C]4[/C][C]9536.75[/C][C]465.036875370702[/C][C]1573[/C][/ROW]
[ROW][C]5[/C][C]9808.41666666667[/C][C]375.82550552891[/C][C]1384[/C][/ROW]
[ROW][C]6[/C][C]10050.5[/C][C]489.675495516256[/C][C]1482[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36134&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36134&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
19511438.4640547099921451
29305.91666666667388.9165506035111247
39324441.3024112576521623
49536.75465.0368753707021573
59808.41666666667375.825505528911384
610050.5489.6754955162561482






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-63.9320339299989
beta0.0518420268246785
S.D.0.0707682193515611
T-STAT0.73256084863657
p-value0.50443984674494

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -63.9320339299989 \tabularnewline
beta & 0.0518420268246785 \tabularnewline
S.D. & 0.0707682193515611 \tabularnewline
T-STAT & 0.73256084863657 \tabularnewline
p-value & 0.50443984674494 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36134&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-63.9320339299989[/C][/ROW]
[ROW][C]beta[/C][C]0.0518420268246785[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0707682193515611[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.73256084863657[/C][/ROW]
[ROW][C]p-value[/C][C]0.50443984674494[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36134&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36134&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-63.9320339299989
beta0.0518420268246785
S.D.0.0707682193515611
T-STAT0.73256084863657
p-value0.50443984674494






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.63608875815898
beta1.05834855630331
S.D.1.61914610202505
T-STAT0.653646113207231
p-value0.5490103780068
Lambda-0.0583485563033119

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.63608875815898 \tabularnewline
beta & 1.05834855630331 \tabularnewline
S.D. & 1.61914610202505 \tabularnewline
T-STAT & 0.653646113207231 \tabularnewline
p-value & 0.5490103780068 \tabularnewline
Lambda & -0.0583485563033119 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36134&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.63608875815898[/C][/ROW]
[ROW][C]beta[/C][C]1.05834855630331[/C][/ROW]
[ROW][C]S.D.[/C][C]1.61914610202505[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.653646113207231[/C][/ROW]
[ROW][C]p-value[/C][C]0.5490103780068[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0583485563033119[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36134&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36134&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-3.63608875815898
beta1.05834855630331
S.D.1.61914610202505
T-STAT0.653646113207231
p-value0.5490103780068
Lambda-0.0583485563033119


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ; par2 = ; par3 = ; 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')