FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 23 Apr 2012 09:43:54 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/23/t1335188679qazo29h0cirykn5.htm/, Retrieved Fri, 03 May 2024 17:15:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164699, Retrieved Fri, 03 May 2024 17:15:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99

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] [Spreidings- en Ge...] [2012-04-23 13:43:54] [b1a32f872c4b465525fe03c124440f0d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10698
11514
13253
13807
13971
15548
17351
17409
17537
17704
17970
18004
18089
18479
18730
19169
19684
19785
20366
20506
20764
21382
21705
21725
21790
22205
22228
22397
22405
22414
22679
22780
22782
23843
23970
24319
24561
24693
25316
25591
25814
26105
26482
26887
27044
27071
27192
28029
28352
28806
29096
29133
29383
29462
29743
29965
30212
30364
31514
32034
32609
34777
35022
35338
35953
36438
36845
37702
37863
39690
41086
43129

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164699&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164699&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164699&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
115397.16666666672654.743433360317306
2200321249.322652843973636
322817.6666666667794.5535434024152529
426232.08333333331070.562762657043468
529838.66666666671076.285813116183682
637204.33333333332932.0501773373910520

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 15397.1666666667 & 2654.74343336031 & 7306 \tabularnewline
2 & 20032 & 1249.32265284397 & 3636 \tabularnewline
3 & 22817.6666666667 & 794.553543402415 & 2529 \tabularnewline
4 & 26232.0833333333 & 1070.56276265704 & 3468 \tabularnewline
5 & 29838.6666666667 & 1076.28581311618 & 3682 \tabularnewline
6 & 37204.3333333333 & 2932.05017733739 & 10520 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164699&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]15397.1666666667[/C][C]2654.74343336031[/C][C]7306[/C][/ROW]
[ROW][C]2[/C][C]20032[/C][C]1249.32265284397[/C][C]3636[/C][/ROW]
[ROW][C]3[/C][C]22817.6666666667[/C][C]794.553543402415[/C][C]2529[/C][/ROW]
[ROW][C]4[/C][C]26232.0833333333[/C][C]1070.56276265704[/C][C]3468[/C][/ROW]
[ROW][C]5[/C][C]29838.6666666667[/C][C]1076.28581311618[/C][C]3682[/C][/ROW]
[ROW][C]6[/C][C]37204.3333333333[/C][C]2932.05017733739[/C][C]10520[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164699&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164699&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
115397.16666666672654.743433360317306
2200321249.322652843973636
322817.6666666667794.5535434024152529
426232.08333333331070.562762657043468
529838.66666666671076.285813116183682
637204.33333333332932.0501773373910520






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1082.26336857572
beta0.0216730242298039
S.D.0.0587093124933824
T-STAT0.369158201814181
p-value0.730720688759666

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1082.26336857572 \tabularnewline
beta & 0.0216730242298039 \tabularnewline
S.D. & 0.0587093124933824 \tabularnewline
T-STAT & 0.369158201814181 \tabularnewline
p-value & 0.730720688759666 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164699&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1082.26336857572[/C][/ROW]
[ROW][C]beta[/C][C]0.0216730242298039[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0587093124933824[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.369158201814181[/C][/ROW]
[ROW][C]p-value[/C][C]0.730720688759666[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164699&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164699&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)
alpha1082.26336857572
beta0.0216730242298039
S.D.0.0587093124933824
T-STAT0.369158201814181
p-value0.730720688759666






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.14227705921116
beta0.0128620781166181
S.D.0.862812974512815
T-STAT0.0149071449973045
p-value0.988820158832777
Lambda0.987137921883382

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.14227705921116 \tabularnewline
beta & 0.0128620781166181 \tabularnewline
S.D. & 0.862812974512815 \tabularnewline
T-STAT & 0.0149071449973045 \tabularnewline
p-value & 0.988820158832777 \tabularnewline
Lambda & 0.987137921883382 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164699&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.14227705921116[/C][/ROW]
[ROW][C]beta[/C][C]0.0128620781166181[/C][/ROW]
[ROW][C]S.D.[/C][C]0.862812974512815[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0149071449973045[/C][/ROW]
[ROW][C]p-value[/C][C]0.988820158832777[/C][/ROW]
[ROW][C]Lambda[/C][C]0.987137921883382[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164699&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164699&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)
alpha7.14227705921116
beta0.0128620781166181
S.D.0.862812974512815
T-STAT0.0149071449973045
p-value0.988820158832777
Lambda0.987137921883382


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')