Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 21 Nov 2014 08:15:53 +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/2014/Nov/21/t1416557764pcfatocruxnpt8m.htm/, Retrieved Sun, 19 May 2024 13:00:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257521, Retrieved Sun, 19 May 2024 13:00:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2014-11-21 08:15:53] [bc3b0a9d08b571f2c6b79bb1a1231eac] [Current]
Feedback Forum

Post a new message
Dataseries X:
250.8
247.6
237.8
226.4
217.2
211.4
207.6
204.3
197.5
193.6
192.3
192
196.1
191.9
185.6
179.4
173.9
169.2
166.8
165.2
161.4
160.8
163.7
170.8
182.7
190.9
197.8
205.1
210.7
220.2
229.7
237.1
241.6
250.4
258.6
269.9
283.2
289.6
281.8
274.7
267.6
261.4
260.5
260.7
254.2
250.5
253.4
263.7
276.2
273.8
265.9
258.4
253.5
250.7
252.8
255.3
251.2
252.5
257.8
269.9
291.6
298.9
295.6
292.1
290.9
290.6
298
304
304.3
309.8
322.3
340.2
369.3
376.7
379.7
379.5
377.8
381.6
394.6
399.3
400.4
408.2
419.1
437.7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257521&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257521&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257521&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'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1214.87521.297807185461458.8
2173.73333333333311.959578385190535.3
3224.55833333333327.875256487473387.2
4266.77512.779680249236639.1
5259.8333333333339.1905419103587425.5
6303.19166666666714.925052662208549.6
7393.65833333333320.337312700521468.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 214.875 & 21.2978071854614 & 58.8 \tabularnewline
2 & 173.733333333333 & 11.9595783851905 & 35.3 \tabularnewline
3 & 224.558333333333 & 27.8752564874733 & 87.2 \tabularnewline
4 & 266.775 & 12.7796802492366 & 39.1 \tabularnewline
5 & 259.833333333333 & 9.19054191035874 & 25.5 \tabularnewline
6 & 303.191666666667 & 14.9250526622085 & 49.6 \tabularnewline
7 & 393.658333333333 & 20.3373127005214 & 68.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257521&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]214.875[/C][C]21.2978071854614[/C][C]58.8[/C][/ROW]
[ROW][C]2[/C][C]173.733333333333[/C][C]11.9595783851905[/C][C]35.3[/C][/ROW]
[ROW][C]3[/C][C]224.558333333333[/C][C]27.8752564874733[/C][C]87.2[/C][/ROW]
[ROW][C]4[/C][C]266.775[/C][C]12.7796802492366[/C][C]39.1[/C][/ROW]
[ROW][C]5[/C][C]259.833333333333[/C][C]9.19054191035874[/C][C]25.5[/C][/ROW]
[ROW][C]6[/C][C]303.191666666667[/C][C]14.9250526622085[/C][C]49.6[/C][/ROW]
[ROW][C]7[/C][C]393.658333333333[/C][C]20.3373127005214[/C][C]68.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257521&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257521&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
1214.87521.297807185461458.8
2173.73333333333311.959578385190535.3
3224.55833333333327.875256487473387.2
4266.77512.779680249236639.1
5259.8333333333339.1905419103587425.5
6303.19166666666714.925052662208549.6
7393.65833333333320.337312700521468.4







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha15.3068655573292
beta0.00610749101158136
S.D.0.0409269750676095
T-STAT0.149228986542301
p-value0.887205281243934

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 15.3068655573292 \tabularnewline
beta & 0.00610749101158136 \tabularnewline
S.D. & 0.0409269750676095 \tabularnewline
T-STAT & 0.149228986542301 \tabularnewline
p-value & 0.887205281243934 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257521&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15.3068655573292[/C][/ROW]
[ROW][C]beta[/C][C]0.00610749101158136[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0409269750676095[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.149228986542301[/C][/ROW]
[ROW][C]p-value[/C][C]0.887205281243934[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257521&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257521&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)
alpha15.3068655573292
beta0.00610749101158136
S.D.0.0409269750676095
T-STAT0.149228986542301
p-value0.887205281243934







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.91213578090862
beta0.153810256337596
S.D.0.654050085197131
T-STAT0.235165868514852
p-value0.823407827231013
Lambda0.846189743662404

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.91213578090862 \tabularnewline
beta & 0.153810256337596 \tabularnewline
S.D. & 0.654050085197131 \tabularnewline
T-STAT & 0.235165868514852 \tabularnewline
p-value & 0.823407827231013 \tabularnewline
Lambda & 0.846189743662404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257521&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.91213578090862[/C][/ROW]
[ROW][C]beta[/C][C]0.153810256337596[/C][/ROW]
[ROW][C]S.D.[/C][C]0.654050085197131[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.235165868514852[/C][/ROW]
[ROW][C]p-value[/C][C]0.823407827231013[/C][/ROW]
[ROW][C]Lambda[/C][C]0.846189743662404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257521&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257521&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)
alpha1.91213578090862
beta0.153810256337596
S.D.0.654050085197131
T-STAT0.235165868514852
p-value0.823407827231013
Lambda0.846189743662404



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')