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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, 09 May 2011 10:03:19 +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/2011/May/09/t1304935278r29tktlxvy8l30g.htm/, Retrieved Tue, 14 May 2024 20:09:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121232, Retrieved Tue, 14 May 2024 20:09:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [datareeks - sprei...] [2011-05-09 10:03:19] [7bcd6f70ebc29c57c8a78e561eff7496] [Current]
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Dataseries X:
5.81
5.76
5.99
6.12
6.03
6.25
5.80
5.67
5.89
5.91
5.86
6.07
6.27
6.68
6.77
6.71
6.62
6.50
5.89
6.05
6.43
6.47
6.62
6.77
6.70
6.95
6.73
7.07
7.28
7.32
6.76
6.93
6.99
7.16
7.28
7.08
7.34
7.87
6.28
6.30
6.36
6.28
5.89
6.04
5.96
6.10
6.26
6.02
6.25
6.41
6.22
6.57
6.18
6.26
6.10
6.02
6.06
6.35
6.21
6.48
6.74
6.53
6.80
6.75
6.56
6.66
6.18
6.40
6.43
6.54
6.44
6.64
6.82
6.97
7.00
6.91
6.74
6.98
6.37
6.56
6.63
6.87
6.68
6.75
6.84
7.15
7.09
6.97
7.15




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121232&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121232&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121232&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 time2 seconds
R Server'Gwilym Jenkins' @ www.wessa.org







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
15.920.1659317128620490.36
25.93750.2560436160761160.58
35.93250.09394147114027980.21
46.60750.2280898945591410.5
56.2650.350285597762740.73
66.57250.1550.34
76.86250.177646653031610.37
87.07250.2721978447134860.56
97.12750.1231191834497510.29
106.94750.7894882308601361.59
116.14250.2163908500838240.470000000000001
126.0850.130.3
136.36250.1615291511358450.350000000000001
146.140.1032795558988650.24
156.2750.1808314132002520.420000000000001
166.7050.1195826074310140.27
176.450.2094437076320670.48
186.51250.09844626283748220.21
196.9250.07937253933193750.18
206.66250.2600480724789170.61
216.73250.1040432602334240.24
227.01250.1372042273401230.31

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5.92 & 0.165931712862049 & 0.36 \tabularnewline
2 & 5.9375 & 0.256043616076116 & 0.58 \tabularnewline
3 & 5.9325 & 0.0939414711402798 & 0.21 \tabularnewline
4 & 6.6075 & 0.228089894559141 & 0.5 \tabularnewline
5 & 6.265 & 0.35028559776274 & 0.73 \tabularnewline
6 & 6.5725 & 0.155 & 0.34 \tabularnewline
7 & 6.8625 & 0.17764665303161 & 0.37 \tabularnewline
8 & 7.0725 & 0.272197844713486 & 0.56 \tabularnewline
9 & 7.1275 & 0.123119183449751 & 0.29 \tabularnewline
10 & 6.9475 & 0.789488230860136 & 1.59 \tabularnewline
11 & 6.1425 & 0.216390850083824 & 0.470000000000001 \tabularnewline
12 & 6.085 & 0.13 & 0.3 \tabularnewline
13 & 6.3625 & 0.161529151135845 & 0.350000000000001 \tabularnewline
14 & 6.14 & 0.103279555898865 & 0.24 \tabularnewline
15 & 6.275 & 0.180831413200252 & 0.420000000000001 \tabularnewline
16 & 6.705 & 0.119582607431014 & 0.27 \tabularnewline
17 & 6.45 & 0.209443707632067 & 0.48 \tabularnewline
18 & 6.5125 & 0.0984462628374822 & 0.21 \tabularnewline
19 & 6.925 & 0.0793725393319375 & 0.18 \tabularnewline
20 & 6.6625 & 0.260048072478917 & 0.61 \tabularnewline
21 & 6.7325 & 0.104043260233424 & 0.24 \tabularnewline
22 & 7.0125 & 0.137204227340123 & 0.31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121232&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]5.92[/C][C]0.165931712862049[/C][C]0.36[/C][/ROW]
[ROW][C]2[/C][C]5.9375[/C][C]0.256043616076116[/C][C]0.58[/C][/ROW]
[ROW][C]3[/C][C]5.9325[/C][C]0.0939414711402798[/C][C]0.21[/C][/ROW]
[ROW][C]4[/C][C]6.6075[/C][C]0.228089894559141[/C][C]0.5[/C][/ROW]
[ROW][C]5[/C][C]6.265[/C][C]0.35028559776274[/C][C]0.73[/C][/ROW]
[ROW][C]6[/C][C]6.5725[/C][C]0.155[/C][C]0.34[/C][/ROW]
[ROW][C]7[/C][C]6.8625[/C][C]0.17764665303161[/C][C]0.37[/C][/ROW]
[ROW][C]8[/C][C]7.0725[/C][C]0.272197844713486[/C][C]0.56[/C][/ROW]
[ROW][C]9[/C][C]7.1275[/C][C]0.123119183449751[/C][C]0.29[/C][/ROW]
[ROW][C]10[/C][C]6.9475[/C][C]0.789488230860136[/C][C]1.59[/C][/ROW]
[ROW][C]11[/C][C]6.1425[/C][C]0.216390850083824[/C][C]0.470000000000001[/C][/ROW]
[ROW][C]12[/C][C]6.085[/C][C]0.13[/C][C]0.3[/C][/ROW]
[ROW][C]13[/C][C]6.3625[/C][C]0.161529151135845[/C][C]0.350000000000001[/C][/ROW]
[ROW][C]14[/C][C]6.14[/C][C]0.103279555898865[/C][C]0.24[/C][/ROW]
[ROW][C]15[/C][C]6.275[/C][C]0.180831413200252[/C][C]0.420000000000001[/C][/ROW]
[ROW][C]16[/C][C]6.705[/C][C]0.119582607431014[/C][C]0.27[/C][/ROW]
[ROW][C]17[/C][C]6.45[/C][C]0.209443707632067[/C][C]0.48[/C][/ROW]
[ROW][C]18[/C][C]6.5125[/C][C]0.0984462628374822[/C][C]0.21[/C][/ROW]
[ROW][C]19[/C][C]6.925[/C][C]0.0793725393319375[/C][C]0.18[/C][/ROW]
[ROW][C]20[/C][C]6.6625[/C][C]0.260048072478917[/C][C]0.61[/C][/ROW]
[ROW][C]21[/C][C]6.7325[/C][C]0.104043260233424[/C][C]0.24[/C][/ROW]
[ROW][C]22[/C][C]7.0125[/C][C]0.137204227340123[/C][C]0.31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121232&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121232&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
15.920.1659317128620490.36
25.93750.2560436160761160.58
35.93250.09394147114027980.21
46.60750.2280898945591410.5
56.2650.350285597762740.73
66.57250.1550.34
76.86250.177646653031610.37
87.07250.2721978447134860.56
97.12750.1231191834497510.29
106.94750.7894882308601361.59
116.14250.2163908500838240.470000000000001
126.0850.130.3
136.36250.1615291511358450.350000000000001
146.140.1032795558988650.24
156.2750.1808314132002520.420000000000001
166.7050.1195826074310140.27
176.450.2094437076320670.48
186.51250.09844626283748220.21
196.9250.07937253933193750.18
206.66250.2600480724789170.61
216.73250.1040432602334240.24
227.01250.1372042273401230.31







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.241587139168137
beta0.0679011023648034
S.D.0.0843190649461669
T-STAT0.80528765835051
p-value0.430124092818931

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.241587139168137 \tabularnewline
beta & 0.0679011023648034 \tabularnewline
S.D. & 0.0843190649461669 \tabularnewline
T-STAT & 0.80528765835051 \tabularnewline
p-value & 0.430124092818931 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121232&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.241587139168137[/C][/ROW]
[ROW][C]beta[/C][C]0.0679011023648034[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0843190649461669[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.80528765835051[/C][/ROW]
[ROW][C]p-value[/C][C]0.430124092818931[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121232&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121232&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)
alpha-0.241587139168137
beta0.0679011023648034
S.D.0.0843190649461669
T-STAT0.80528765835051
p-value0.430124092818931







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.19959708911487
beta0.767509083777407
S.D.1.94313997162146
T-STAT0.394983940933991
p-value0.697035665804447
Lambda0.232490916222593

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.19959708911487 \tabularnewline
beta & 0.767509083777407 \tabularnewline
S.D. & 1.94313997162146 \tabularnewline
T-STAT & 0.394983940933991 \tabularnewline
p-value & 0.697035665804447 \tabularnewline
Lambda & 0.232490916222593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121232&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.19959708911487[/C][/ROW]
[ROW][C]beta[/C][C]0.767509083777407[/C][/ROW]
[ROW][C]S.D.[/C][C]1.94313997162146[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.394983940933991[/C][/ROW]
[ROW][C]p-value[/C][C]0.697035665804447[/C][/ROW]
[ROW][C]Lambda[/C][C]0.232490916222593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121232&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121232&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)
alpha-3.19959708911487
beta0.767509083777407
S.D.1.94313997162146
T-STAT0.394983940933991
p-value0.697035665804447
Lambda0.232490916222593



Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')