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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 computationTue, 22 Mar 2016 19:41:51 +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/22/t14586757339sfgl7hn2i39cxm.htm/, Retrieved Mon, 29 Apr 2024 08:40:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294460, Retrieved Mon, 29 Apr 2024 08:40:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65

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] [] [2016-03-22 19:41:51] [3d038f408b3fdbe799ace9817e748893] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
90.4
89.5
88.9
88.4
87.6
87.1
86.5
85.7
85.3
84.9
84.5
84.4
84.3
84.2
84.1
83.8
83.5
83.2
82.8
82.2
81.5
80.8
80.3
79.8
79.2
78.8
78.1
77.8
77.3
76.7
76.2
76.1
76.3
76.2
76.2
76.6
75.5
75.4
75.5
75.5
75.2
74.9
74.6
74.4
74
73.3
72.7
72
71.2
70.9
70.4
70
69.7
69.2
68.7
68.6
68.4
67.9
67.4
66.5
65.6
64.6
63.8
63
62.1
61.7
61.4
61.1
61.1
61
60.5
60.2
59.9
59.4
59.6
59.5
59.3
59.3
59.1
58.8

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=294460&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=294460&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294460&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
186.93333333333332.043763610834116
282.54166666666671.596848221473864.5
377.1251.099690038973793.10000000000001
474.41666666666671.189983447809513.5
569.0751.430273336877194.7
662.1751.709930886428935.39999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 86.9333333333333 & 2.04376361083411 & 6 \tabularnewline
2 & 82.5416666666667 & 1.59684822147386 & 4.5 \tabularnewline
3 & 77.125 & 1.09969003897379 & 3.10000000000001 \tabularnewline
4 & 74.4166666666667 & 1.18998344780951 & 3.5 \tabularnewline
5 & 69.075 & 1.43027333687719 & 4.7 \tabularnewline
6 & 62.175 & 1.70993088642893 & 5.39999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294460&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]86.9333333333333[/C][C]2.04376361083411[/C][C]6[/C][/ROW]
[ROW][C]2[/C][C]82.5416666666667[/C][C]1.59684822147386[/C][C]4.5[/C][/ROW]
[ROW][C]3[/C][C]77.125[/C][C]1.09969003897379[/C][C]3.10000000000001[/C][/ROW]
[ROW][C]4[/C][C]74.4166666666667[/C][C]1.18998344780951[/C][C]3.5[/C][/ROW]
[ROW][C]5[/C][C]69.075[/C][C]1.43027333687719[/C][C]4.7[/C][/ROW]
[ROW][C]6[/C][C]62.175[/C][C]1.70993088642893[/C][C]5.39999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294460&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294460&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
186.93333333333332.043763610834116
282.54166666666671.596848221473864.5
377.1251.099690038973793.10000000000001
474.41666666666671.189983447809513.5
569.0751.430273336877194.7
662.1751.709930886428935.39999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.717750580179294
beta0.0105335776709647
S.D.0.0187216654512253
T-STAT0.562641058745942
p-value0.603717433623075

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.717750580179294 \tabularnewline
beta & 0.0105335776709647 \tabularnewline
S.D. & 0.0187216654512253 \tabularnewline
T-STAT & 0.562641058745942 \tabularnewline
p-value & 0.603717433623075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294460&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.717750580179294[/C][/ROW]
[ROW][C]beta[/C][C]0.0105335776709647[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0187216654512253[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.562641058745942[/C][/ROW]
[ROW][C]p-value[/C][C]0.603717433623075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294460&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294460&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)
alpha0.717750580179294
beta0.0105335776709647
S.D.0.0187216654512253
T-STAT0.562641058745942
p-value0.603717433623075






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.01728316404725
beta0.326263895287442
S.D.0.938554946286261
T-STAT0.347623649077154
p-value0.745644272898667
Lambda0.673736104712558

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.01728316404725 \tabularnewline
beta & 0.326263895287442 \tabularnewline
S.D. & 0.938554946286261 \tabularnewline
T-STAT & 0.347623649077154 \tabularnewline
p-value & 0.745644272898667 \tabularnewline
Lambda & 0.673736104712558 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294460&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.01728316404725[/C][/ROW]
[ROW][C]beta[/C][C]0.326263895287442[/C][/ROW]
[ROW][C]S.D.[/C][C]0.938554946286261[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.347623649077154[/C][/ROW]
[ROW][C]p-value[/C][C]0.745644272898667[/C][/ROW]
[ROW][C]Lambda[/C][C]0.673736104712558[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294460&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294460&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-1.01728316404725
beta0.326263895287442
S.D.0.938554946286261
T-STAT0.347623649077154
p-value0.745644272898667
Lambda0.673736104712558


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')