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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 computationSun, 21 Dec 2008 16:17:50 -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/t12299015026fb5u831sj1yaon.htm/, Retrieved Sun, 12 May 2024 13:40:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35906, Retrieved Sun, 12 May 2024 13:40:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172

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] [SD Mean plot Uitvoer] [2008-12-21 23:17:50] [ba85d9d0a82357dd3edf208eef933423] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15916.4
16535.9
15796
14418.6
15044.5
14944.2
16754.8
14254
15454.9
15644.8
14568.3
12520.2
14803
15873.2
14755.3
12875.1
14291.1
14205.3
15859.4
15258.9
15498.6
15106.5
15023.6
12083
15761.3
16943
15070.3
13659.6
14768.9
14725.1
15998.1
15370.6
14956.9
15469.7
15101.8
11703.7
16283.6
16726.5
14968.9
14861
14583.3
15305.8
17903.9
16379.4
15420.3
17870.5
15912.8
13866.5
17823.2
17872
17420.4
16704.4
15991.2
16583.6
19123.5
17838.7
17209.4
18586.5
16258.1
15141.6
19202.1
17746.5
19090.1
18040.3
17515.5
17751.8
21072.4
17170
19439.5
19795.4
17574.9
16165.4
19464.6
19932.1
19961.2
17343.4
18924.2
18574.1
21350.6
18594.6
19823.1
20844.4
19640.2
17735.4
19813.6
22238.5
20682.2
17818.6
21872.1
22117
21865.9
23451.3
20953.7
22497.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 5 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35906&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35906&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35906&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 time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
115154.38333333331147.480088029524234.6
214636.08333333331147.971186551093790.2
314960.751296.811194290205239.3
415840.20833333331254.602415442174037.4
517212.71666666671133.290074263533981.9
618380.3251356.146188234754907
719348.99166666671177.691521161274007.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 15154.3833333333 & 1147.48008802952 & 4234.6 \tabularnewline
2 & 14636.0833333333 & 1147.97118655109 & 3790.2 \tabularnewline
3 & 14960.75 & 1296.81119429020 & 5239.3 \tabularnewline
4 & 15840.2083333333 & 1254.60241544217 & 4037.4 \tabularnewline
5 & 17212.7166666667 & 1133.29007426353 & 3981.9 \tabularnewline
6 & 18380.325 & 1356.14618823475 & 4907 \tabularnewline
7 & 19348.9916666667 & 1177.69152116127 & 4007.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35906&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]15154.3833333333[/C][C]1147.48008802952[/C][C]4234.6[/C][/ROW]
[ROW][C]2[/C][C]14636.0833333333[/C][C]1147.97118655109[/C][C]3790.2[/C][/ROW]
[ROW][C]3[/C][C]14960.75[/C][C]1296.81119429020[/C][C]5239.3[/C][/ROW]
[ROW][C]4[/C][C]15840.2083333333[/C][C]1254.60241544217[/C][C]4037.4[/C][/ROW]
[ROW][C]5[/C][C]17212.7166666667[/C][C]1133.29007426353[/C][C]3981.9[/C][/ROW]
[ROW][C]6[/C][C]18380.325[/C][C]1356.14618823475[/C][C]4907[/C][/ROW]
[ROW][C]7[/C][C]19348.9916666667[/C][C]1177.69152116127[/C][C]4007.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35906&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35906&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
115154.38333333331147.480088029524234.6
214636.08333333331147.971186551093790.2
314960.751296.811194290205239.3
415840.20833333331254.602415442174037.4
517212.71666666671133.290074263533981.9
618380.3251356.146188234754907
719348.99166666671177.691521161274007.2






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1082.15363540261
beta0.00812679922940899
S.D.0.0208357931177943
T-STAT0.390040311087007
p-value0.712568666066525

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1082.15363540261 \tabularnewline
beta & 0.00812679922940899 \tabularnewline
S.D. & 0.0208357931177943 \tabularnewline
T-STAT & 0.390040311087007 \tabularnewline
p-value & 0.712568666066525 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35906&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1082.15363540261[/C][/ROW]
[ROW][C]beta[/C][C]0.00812679922940899[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0208357931177943[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.390040311087007[/C][/ROW]
[ROW][C]p-value[/C][C]0.712568666066525[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35906&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35906&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)
alpha1082.15363540261
beta0.00812679922940899
S.D.0.0208357931177943
T-STAT0.390040311087007
p-value0.712568666066525






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.0306149727611
beta0.110320911325912
S.D.0.283752847451919
T-STAT0.388792261704460
p-value0.7134349650707
Lambda0.889679088674088

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.0306149727611 \tabularnewline
beta & 0.110320911325912 \tabularnewline
S.D. & 0.283752847451919 \tabularnewline
T-STAT & 0.388792261704460 \tabularnewline
p-value & 0.7134349650707 \tabularnewline
Lambda & 0.889679088674088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35906&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.0306149727611[/C][/ROW]
[ROW][C]beta[/C][C]0.110320911325912[/C][/ROW]
[ROW][C]S.D.[/C][C]0.283752847451919[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.388792261704460[/C][/ROW]
[ROW][C]p-value[/C][C]0.7134349650707[/C][/ROW]
[ROW][C]Lambda[/C][C]0.889679088674088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35906&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35906&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)
alpha6.0306149727611
beta0.110320911325912
S.D.0.283752847451919
T-STAT0.388792261704460
p-value0.7134349650707
Lambda0.889679088674088


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')