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, 21 Mar 2016 13:52:49 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/21/t14585683933cdcc1efzesec73.htm/, Retrieved Sun, 05 May 2024 20:27:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294377, Retrieved Sun, 05 May 2024 20:27:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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] [] [2016-03-21 13:52:49] [9d122f8260d20611f07666190c7f1fd6] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
45564.6
47295.5
46465.5
50679.5
47452.8
49415.4
48165.3
51814
49030.7
50820.8
49729.5
53501.6
50524.9
52095
51290.3
55064
52505.2
54318.3
53039.6
57607.6
54236.4
56586.4
55614
60085.9
56963.5
59152.8
57804.6
62541.5
59449.3
61704.7
60399
65724.7
62679.4
65526.5
64274.8
68769.1
63542.8
66198
64544.9
71041.8
66087.2
69005.8
66897
73702
68485.3
71457
69774.6
76479.7
71204.7
73783.9
71651
78541.6
72714.4
75258
73168.1
79701.6
73944.5
76401.2
73948.1
80583.3

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' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294377&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294377&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294377&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' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
149161.26666666672314.659874614747937
254413.96666666672776.277869029079561
362082.49166666673544.6362184056811805.6
468934.6753807.426041095112936.9
575075.03333333333099.603765977299378.60000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 49161.2666666667 & 2314.65987461474 & 7937 \tabularnewline
2 & 54413.9666666667 & 2776.27786902907 & 9561 \tabularnewline
3 & 62082.4916666667 & 3544.63621840568 & 11805.6 \tabularnewline
4 & 68934.675 & 3807.4260410951 & 12936.9 \tabularnewline
5 & 75075.0333333333 & 3099.60376597729 & 9378.60000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294377&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]49161.2666666667[/C][C]2314.65987461474[/C][C]7937[/C][/ROW]
[ROW][C]2[/C][C]54413.9666666667[/C][C]2776.27786902907[/C][C]9561[/C][/ROW]
[ROW][C]3[/C][C]62082.4916666667[/C][C]3544.63621840568[/C][C]11805.6[/C][/ROW]
[ROW][C]4[/C][C]68934.675[/C][C]3807.4260410951[/C][C]12936.9[/C][/ROW]
[ROW][C]5[/C][C]75075.0333333333[/C][C]3099.60376597729[/C][C]9378.60000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294377&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294377&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
149161.26666666672314.659874614747937
254413.96666666672776.277869029079561
362082.49166666673544.6362184056811805.6
468934.6753807.426041095112936.9
575075.03333333333099.603765977299378.60000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha656.132800095343
beta0.0395971240393436
S.D.0.0234345514332951
T-STAT1.68968986464513
p-value0.189668580803647

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 656.132800095343 \tabularnewline
beta & 0.0395971240393436 \tabularnewline
S.D. & 0.0234345514332951 \tabularnewline
T-STAT & 1.68968986464513 \tabularnewline
p-value & 0.189668580803647 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294377&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]656.132800095343[/C][/ROW]
[ROW][C]beta[/C][C]0.0395971240393436[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0234345514332951[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.68968986464513[/C][/ROW]
[ROW][C]p-value[/C][C]0.189668580803647[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294377&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294377&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)
alpha656.132800095343
beta0.0395971240393436
S.D.0.0234345514332951
T-STAT1.68968986464513
p-value0.189668580803647






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.63149509246662
beta0.87624297458201
S.D.0.433240451672564
T-STAT2.02253268640819
p-value0.136322438217359
Lambda0.12375702541799

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.63149509246662 \tabularnewline
beta & 0.87624297458201 \tabularnewline
S.D. & 0.433240451672564 \tabularnewline
T-STAT & 2.02253268640819 \tabularnewline
p-value & 0.136322438217359 \tabularnewline
Lambda & 0.12375702541799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294377&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.63149509246662[/C][/ROW]
[ROW][C]beta[/C][C]0.87624297458201[/C][/ROW]
[ROW][C]S.D.[/C][C]0.433240451672564[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.02253268640819[/C][/ROW]
[ROW][C]p-value[/C][C]0.136322438217359[/C][/ROW]
[ROW][C]Lambda[/C][C]0.12375702541799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294377&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294377&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-1.63149509246662
beta0.87624297458201
S.D.0.433240451672564
T-STAT2.02253268640819
p-value0.136322438217359
Lambda0.12375702541799


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')