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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 computationThu, 12 Mar 2015 15:06:23 +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/2015/Mar/12/t1426172807johiv9y6m8uwvk3.htm/, Retrieved Fri, 17 May 2024 01:25:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278282, Retrieved Fri, 17 May 2024 01:25:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

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] [] [2015-03-12 15:06:23] [f51cc71db71177f4a98625dd32633bf7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
950
775
805
680
705
755
715
860
900
1010
925
650
1060
1050
1025
1085
1160
1310
1445
1445
1615
1650
1255
1175
1300
1280
1390
1340
1110
1325
1265
1150
1430
1655
1570
1345
1430
1260
1495
1125
895
1085
870
1185
1455
1540
1615
1200
1260
1095
1160
1095
1300
1215
1245
1350
1300
1280
1270
1065
1340
1265
1155
930
880
925
980
1015
1040
1365
1160
1115
1630
1225
1200
1265
1140
1270
1445
1305
1665
1830
1690
1520

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'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278282&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278282&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278282&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'Sir Maurice George Kendall' @ kendall.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1810.833333333333116.868872388388360
21272.91666666667220.38662652601625
31346.66666666667154.409922745995545
41262.91666666667246.774265025322745
51219.5833333333393.8678552137218285
61097.5163.755638348452485
71432.08333333333229.341531081459690

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 810.833333333333 & 116.868872388388 & 360 \tabularnewline
2 & 1272.91666666667 & 220.38662652601 & 625 \tabularnewline
3 & 1346.66666666667 & 154.409922745995 & 545 \tabularnewline
4 & 1262.91666666667 & 246.774265025322 & 745 \tabularnewline
5 & 1219.58333333333 & 93.8678552137218 & 285 \tabularnewline
6 & 1097.5 & 163.755638348452 & 485 \tabularnewline
7 & 1432.08333333333 & 229.341531081459 & 690 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278282&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]810.833333333333[/C][C]116.868872388388[/C][C]360[/C][/ROW]
[ROW][C]2[/C][C]1272.91666666667[/C][C]220.38662652601[/C][C]625[/C][/ROW]
[ROW][C]3[/C][C]1346.66666666667[/C][C]154.409922745995[/C][C]545[/C][/ROW]
[ROW][C]4[/C][C]1262.91666666667[/C][C]246.774265025322[/C][C]745[/C][/ROW]
[ROW][C]5[/C][C]1219.58333333333[/C][C]93.8678552137218[/C][C]285[/C][/ROW]
[ROW][C]6[/C][C]1097.5[/C][C]163.755638348452[/C][C]485[/C][/ROW]
[ROW][C]7[/C][C]1432.08333333333[/C][C]229.341531081459[/C][C]690[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278282&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278282&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
1810.833333333333116.868872388388360
21272.91666666667220.38662652601625
31346.66666666667154.409922745995545
41262.91666666667246.774265025322745
51219.5833333333393.8678552137218285
61097.5163.755638348452485
71432.08333333333229.341531081459690






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-18.5198771660607
beta0.160502677108886
S.D.0.107740925554045
T-STAT1.4897094700414
p-value0.196482803226508

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -18.5198771660607 \tabularnewline
beta & 0.160502677108886 \tabularnewline
S.D. & 0.107740925554045 \tabularnewline
T-STAT & 1.4897094700414 \tabularnewline
p-value & 0.196482803226508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278282&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-18.5198771660607[/C][/ROW]
[ROW][C]beta[/C][C]0.160502677108886[/C][/ROW]
[ROW][C]S.D.[/C][C]0.107740925554045[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.4897094700414[/C][/ROW]
[ROW][C]p-value[/C][C]0.196482803226508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278282&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278282&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-18.5198771660607
beta0.160502677108886
S.D.0.107740925554045
T-STAT1.4897094700414
p-value0.196482803226508






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.08028270776702
beta1.01562188099767
S.D.0.737748557533127
T-STAT1.37665044631695
p-value0.227069542160375
Lambda-0.0156218809976674

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.08028270776702 \tabularnewline
beta & 1.01562188099767 \tabularnewline
S.D. & 0.737748557533127 \tabularnewline
T-STAT & 1.37665044631695 \tabularnewline
p-value & 0.227069542160375 \tabularnewline
Lambda & -0.0156218809976674 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278282&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.08028270776702[/C][/ROW]
[ROW][C]beta[/C][C]1.01562188099767[/C][/ROW]
[ROW][C]S.D.[/C][C]0.737748557533127[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.37665044631695[/C][/ROW]
[ROW][C]p-value[/C][C]0.227069542160375[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0156218809976674[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278282&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278282&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-2.08028270776702
beta1.01562188099767
S.D.0.737748557533127
T-STAT1.37665044631695
p-value0.227069542160375
Lambda-0.0156218809976674


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')