Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 12 Dec 2007 12:57:56 -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/2007/Dec/12/t119748862359aych47c2xgv7s.htm/, Retrieved Thu, 02 May 2024 14:43:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3266, Retrieved Thu, 02 May 2024 14:43:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact217
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [Standard deviatio...] [2007-11-28 15:52:16] [aa0d06577c57214974bc715dada29347]
-    D  [Standard Deviation-Mean Plot] [Tijdreeks 1: indu...] [2007-12-12 19:34:29] [74be16979710d4c4e7c6647856088456]
-    D      [Standard Deviation-Mean Plot] [Tijdreeks 2: omze...] [2007-12-12 19:57:56] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
106,0
100,9
114,3
101,2
109,2
111,6
91,7
93,7
105,7
109,5
105,3
102,8
100,6
97,6
110,3
107,2
107,2
108,1
97,1
92,2
112,2
111,6
115,7
111,3
104,2
103,2
112,7
106,4
102,6
110,6
95,2
89,0
112,5
116,8
107,2
113,6
101,8
102,6
122,7
110,3
110,5
121,6
100,3
100,7
123,4
127,1
124,1
131,2
111,6
114,2
130,1
125,9
119,0
133,8
107,5
113,5
134,4
126,8
135,6
139,9
129,8
131,0
153,1
134,1
144,1
155,9
123,3
128,1
144,3
153,0
149,9
150,9
141,0
138,9
157,4
142,9
151,7
161,0
138,6
136,0
151,9




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3266&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3266&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3266&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1104.3256.7737628860452213.7
2105.9257.3054307321210218.1
3106.1666666666678.046719640306666.5
4114.69166666666711.500391956429830
5124.35833333333310.854363038414437.3
6141.45833333333311.522188738834947.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 104.325 & 6.77376288604522 & 13.7 \tabularnewline
2 & 105.925 & 7.30543073212102 & 18.1 \tabularnewline
3 & 106.166666666667 & 8.04671964030666 & 6.5 \tabularnewline
4 & 114.691666666667 & 11.5003919564298 & 30 \tabularnewline
5 & 124.358333333333 & 10.8543630384144 & 37.3 \tabularnewline
6 & 141.458333333333 & 11.5221887388349 & 47.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3266&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]104.325[/C][C]6.77376288604522[/C][C]13.7[/C][/ROW]
[ROW][C]2[/C][C]105.925[/C][C]7.30543073212102[/C][C]18.1[/C][/ROW]
[ROW][C]3[/C][C]106.166666666667[/C][C]8.04671964030666[/C][C]6.5[/C][/ROW]
[ROW][C]4[/C][C]114.691666666667[/C][C]11.5003919564298[/C][C]30[/C][/ROW]
[ROW][C]5[/C][C]124.358333333333[/C][C]10.8543630384144[/C][C]37.3[/C][/ROW]
[ROW][C]6[/C][C]141.458333333333[/C][C]11.5221887388349[/C][C]47.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3266&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3266&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
1104.3256.7737628860452213.7
2105.9257.3054307321210218.1
3106.1666666666678.046719640306666.5
4114.69166666666711.500391956429830
5124.35833333333310.854363038414437.3
6141.45833333333311.522188738834947.8







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-4.83394538617932
beta0.121973712105647
S.D.0.0447359455326736
T-STAT2.72652585417159
p-value0.0526311921994315

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.83394538617932 \tabularnewline
beta & 0.121973712105647 \tabularnewline
S.D. & 0.0447359455326736 \tabularnewline
T-STAT & 2.72652585417159 \tabularnewline
p-value & 0.0526311921994315 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3266&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.83394538617932[/C][/ROW]
[ROW][C]beta[/C][C]0.121973712105647[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0447359455326736[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.72652585417159[/C][/ROW]
[ROW][C]p-value[/C][C]0.0526311921994315[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3266&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3266&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-4.83394538617932
beta0.121973712105647
S.D.0.0447359455326736
T-STAT2.72652585417159
p-value0.0526311921994315







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.66455642852636
beta1.65816320292111
S.D.0.577230422371016
T-STAT2.87261921523486
p-value0.0453487879205228
Lambda-0.658163202921111

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.66455642852636 \tabularnewline
beta & 1.65816320292111 \tabularnewline
S.D. & 0.577230422371016 \tabularnewline
T-STAT & 2.87261921523486 \tabularnewline
p-value & 0.0453487879205228 \tabularnewline
Lambda & -0.658163202921111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3266&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.66455642852636[/C][/ROW]
[ROW][C]beta[/C][C]1.65816320292111[/C][/ROW]
[ROW][C]S.D.[/C][C]0.577230422371016[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.87261921523486[/C][/ROW]
[ROW][C]p-value[/C][C]0.0453487879205228[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.658163202921111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3266&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3266&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-5.66455642852636
beta1.65816320292111
S.D.0.577230422371016
T-STAT2.87261921523486
p-value0.0453487879205228
Lambda-0.658163202921111



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')