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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 16 Nov 2015 22:36:48 +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/Nov/16/t1447713444vcsmfcub3adrmbz.htm/, Retrieved Wed, 15 May 2024 01:39:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283411, Retrieved Wed, 15 May 2024 01:39:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
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...] [2015-11-16 22:36:48] [c4e632f9a17048eeb9519d4e8ae83546] [Current]
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Dataseries X:
79.58
80.08
80.41
80.34
80.32
80.39
81.01
81.54
82.48
84.68
88.26
90.6
92.46
93.31
93.58
93.92
93.92
93.67
93.76
93.95
93.89
94.07
93.93
93.35
93.58
93.55
93.44
93.38
93.17
92.95
93.37
94.13
94.07
94
94.47
94.81
94.18
94.14
93.96
93.23
93.13
92.51
92.49
92.73
92.75
92.83
92.85
93.27
93.98
94.34
94.57
94.62
94.82
95.07
95.72
96.06
96.54
96.38
96.8
97.02
97.29
97.45
97.95
97.69
97.63
97.35
97.38
98.06
98.34
98.53
98.79
98.77
99.2
99.76
99.84
99.83
99.88
99.48
99.66
99.58
99.89
100.7
101.19
100.99
101.52
101.75
101.56
102.57
102.66
102.62
102.76
102.73
102.26
101.72
101.48
100.93




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=283411&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=283411&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283411&T=0

As an alternative you can also use a 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
182.47416666666673.558537642278811.02
293.65083333333330.4459200567026551.61
393.74333333333330.5537858682548581.86
493.17250.6094874896173021.69000000000001
595.49333333333331.051426159888073.03999999999999
697.93583333333330.5573224679961631.5
71000.6199120172176921.98999999999999
8102.0466666666670.6235577298247871.83

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 82.4741666666667 & 3.5585376422788 & 11.02 \tabularnewline
2 & 93.6508333333333 & 0.445920056702655 & 1.61 \tabularnewline
3 & 93.7433333333333 & 0.553785868254858 & 1.86 \tabularnewline
4 & 93.1725 & 0.609487489617302 & 1.69000000000001 \tabularnewline
5 & 95.4933333333333 & 1.05142615988807 & 3.03999999999999 \tabularnewline
6 & 97.9358333333333 & 0.557322467996163 & 1.5 \tabularnewline
7 & 100 & 0.619912017217692 & 1.98999999999999 \tabularnewline
8 & 102.046666666667 & 0.623557729824787 & 1.83 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283411&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]82.4741666666667[/C][C]3.5585376422788[/C][C]11.02[/C][/ROW]
[ROW][C]2[/C][C]93.6508333333333[/C][C]0.445920056702655[/C][C]1.61[/C][/ROW]
[ROW][C]3[/C][C]93.7433333333333[/C][C]0.553785868254858[/C][C]1.86[/C][/ROW]
[ROW][C]4[/C][C]93.1725[/C][C]0.609487489617302[/C][C]1.69000000000001[/C][/ROW]
[ROW][C]5[/C][C]95.4933333333333[/C][C]1.05142615988807[/C][C]3.03999999999999[/C][/ROW]
[ROW][C]6[/C][C]97.9358333333333[/C][C]0.557322467996163[/C][C]1.5[/C][/ROW]
[ROW][C]7[/C][C]100[/C][C]0.619912017217692[/C][C]1.98999999999999[/C][/ROW]
[ROW][C]8[/C][C]102.046666666667[/C][C]0.623557729824787[/C][C]1.83[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283411&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283411&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
182.47416666666673.558537642278811.02
293.65083333333330.4459200567026551.61
393.74333333333330.5537858682548581.86
493.17250.6094874896173021.69000000000001
595.49333333333331.051426159888073.03999999999999
697.93583333333330.5573224679961631.5
71000.6199120172176921.98999999999999
8102.0466666666670.6235577298247871.83







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha14.7706240215812
beta-0.145211104226499
S.D.0.040948038862375
T-STAT-3.54622854380275
p-value0.0121272070038323

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 14.7706240215812 \tabularnewline
beta & -0.145211104226499 \tabularnewline
S.D. & 0.040948038862375 \tabularnewline
T-STAT & -3.54622854380275 \tabularnewline
p-value & 0.0121272070038323 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283411&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.7706240215812[/C][/ROW]
[ROW][C]beta[/C][C]-0.145211104226499[/C][/ROW]
[ROW][C]S.D.[/C][C]0.040948038862375[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.54622854380275[/C][/ROW]
[ROW][C]p-value[/C][C]0.0121272070038323[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283411&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283411&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha14.7706240215812
beta-0.145211104226499
S.D.0.040948038862375
T-STAT-3.54622854380275
p-value0.0121272070038323







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha36.0528976708744
beta-7.98143429724235
S.D.2.64162172204002
T-STAT-3.02141454646981
p-value0.0233545340563195
Lambda8.98143429724235

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 36.0528976708744 \tabularnewline
beta & -7.98143429724235 \tabularnewline
S.D. & 2.64162172204002 \tabularnewline
T-STAT & -3.02141454646981 \tabularnewline
p-value & 0.0233545340563195 \tabularnewline
Lambda & 8.98143429724235 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283411&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]36.0528976708744[/C][/ROW]
[ROW][C]beta[/C][C]-7.98143429724235[/C][/ROW]
[ROW][C]S.D.[/C][C]2.64162172204002[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.02141454646981[/C][/ROW]
[ROW][C]p-value[/C][C]0.0233545340563195[/C][/ROW]
[ROW][C]Lambda[/C][C]8.98143429724235[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283411&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283411&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha36.0528976708744
beta-7.98143429724235
S.D.2.64162172204002
T-STAT-3.02141454646981
p-value0.0233545340563195
Lambda8.98143429724235



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')