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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 10 Aug 2016 23:00:44 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/10/t1470866486t1k6kcl7378sywa.htm/, Retrieved Tue, 30 Apr 2024 04:31:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296264, Retrieved Tue, 30 Apr 2024 04:31:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Braadoven Omzet -...] [2016-08-10 13:53:09] [74be16979710d4c4e7c6647856088456]
- RMP     [Standard Deviation-Mean Plot] [Braadoven Omzet -...] [2016-08-10 22:00:44] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7175
7048.75
6922.5
6670
9225
9098.75
7175
5897.5
6023.75
6023.75
6150
6416.25
5645
4872.5
4240
4240
6670
6922.5
4998.75
2822.5
3973.75
3973.75
4872.5
5391.25
5265
3973.75
4620
4366.25
6542.5
6023.75
3973.75
2442.5
3847.5
4240
4620
5125
4100
3215
3595
3721.25
7048.75
7048.75
5125
4872.5
5645
5265
6290
7567.5
7821.25
6023.75
5517.5
4998.75
8466.25
8720
8073.75
8720
8592.5
7567.5
8720
9997.5
10516.25
8972.5
7947.5
8720
12047.5
13072.5
12820
13325
13198.75
11921.25
14097.5
14616.25
15375
13072.5
12173.75
13198.75
15641.25
17817.5
17298.75
17298.75
17552.5
16666.25
18970
18970
18577.5
16400
16792.5
17046.25
18716.25
20892.5
19348.75
20121.25
19475
19096.25
22045
21398.75
20500
19222.5
20500
21146.25
21917.5
22942.5
21917.5
22550
21778.75
21652.5
24853.75
25120
24095
22297.5
23828.75
24473.75
25246.25
26397.5
25246.25
26145
25752.5
24347.5
27296.25
27296.25

Tables (Output of Computation)





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=296264&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=296264&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296264&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 time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
16985.520833333331116.662725075023327.5
24885.208333333331165.078254459824100
34586.666666666671074.775522722044100
45291.145833333331469.610382265614352.5
57768.229166666671500.586481779454998.75
611771.252219.510977056156668.75
716169.58333333332304.233772106286796.25
819159.16666666671799.659242787795645
922008.43751710.793453359245897.5
1025201.8751483.396124607314998.75

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6985.52083333333 & 1116.66272507502 & 3327.5 \tabularnewline
2 & 4885.20833333333 & 1165.07825445982 & 4100 \tabularnewline
3 & 4586.66666666667 & 1074.77552272204 & 4100 \tabularnewline
4 & 5291.14583333333 & 1469.61038226561 & 4352.5 \tabularnewline
5 & 7768.22916666667 & 1500.58648177945 & 4998.75 \tabularnewline
6 & 11771.25 & 2219.51097705615 & 6668.75 \tabularnewline
7 & 16169.5833333333 & 2304.23377210628 & 6796.25 \tabularnewline
8 & 19159.1666666667 & 1799.65924278779 & 5645 \tabularnewline
9 & 22008.4375 & 1710.79345335924 & 5897.5 \tabularnewline
10 & 25201.875 & 1483.39612460731 & 4998.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296264&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]6985.52083333333[/C][C]1116.66272507502[/C][C]3327.5[/C][/ROW]
[ROW][C]2[/C][C]4885.20833333333[/C][C]1165.07825445982[/C][C]4100[/C][/ROW]
[ROW][C]3[/C][C]4586.66666666667[/C][C]1074.77552272204[/C][C]4100[/C][/ROW]
[ROW][C]4[/C][C]5291.14583333333[/C][C]1469.61038226561[/C][C]4352.5[/C][/ROW]
[ROW][C]5[/C][C]7768.22916666667[/C][C]1500.58648177945[/C][C]4998.75[/C][/ROW]
[ROW][C]6[/C][C]11771.25[/C][C]2219.51097705615[/C][C]6668.75[/C][/ROW]
[ROW][C]7[/C][C]16169.5833333333[/C][C]2304.23377210628[/C][C]6796.25[/C][/ROW]
[ROW][C]8[/C][C]19159.1666666667[/C][C]1799.65924278779[/C][C]5645[/C][/ROW]
[ROW][C]9[/C][C]22008.4375[/C][C]1710.79345335924[/C][C]5897.5[/C][/ROW]
[ROW][C]10[/C][C]25201.875[/C][C]1483.39612460731[/C][C]4998.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296264&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296264&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
16985.520833333331116.662725075023327.5
24885.208333333331165.078254459824100
34586.666666666671074.775522722044100
45291.145833333331469.610382265614352.5
57768.229166666671500.586481779454998.75
611771.252219.510977056156668.75
716169.58333333332304.233772106286796.25
819159.16666666671799.659242787795645
922008.43751710.793453359245897.5
1025201.8751483.396124607314998.75






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1247.63333971857
beta0.0271990056486002
S.D.0.0172378277605978
T-STAT1.57786735233378
p-value0.153248154813257

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1247.63333971857 \tabularnewline
beta & 0.0271990056486002 \tabularnewline
S.D. & 0.0172378277605978 \tabularnewline
T-STAT & 1.57786735233378 \tabularnewline
p-value & 0.153248154813257 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296264&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1247.63333971857[/C][/ROW]
[ROW][C]beta[/C][C]0.0271990056486002[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0172378277605978[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.57786735233378[/C][/ROW]
[ROW][C]p-value[/C][C]0.153248154813257[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296264&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296264&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)
alpha1247.63333971857
beta0.0271990056486002
S.D.0.0172378277605978
T-STAT1.57786735233378
p-value0.153248154813257






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.86216454354752
beta0.267768742269429
S.D.0.109131898841678
T-STAT2.45362488063999
p-value0.0397115974245909
Lambda0.732231257730571

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.86216454354752 \tabularnewline
beta & 0.267768742269429 \tabularnewline
S.D. & 0.109131898841678 \tabularnewline
T-STAT & 2.45362488063999 \tabularnewline
p-value & 0.0397115974245909 \tabularnewline
Lambda & 0.732231257730571 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296264&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.86216454354752[/C][/ROW]
[ROW][C]beta[/C][C]0.267768742269429[/C][/ROW]
[ROW][C]S.D.[/C][C]0.109131898841678[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.45362488063999[/C][/ROW]
[ROW][C]p-value[/C][C]0.0397115974245909[/C][/ROW]
[ROW][C]Lambda[/C][C]0.732231257730571[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296264&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296264&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)
alpha4.86216454354752
beta0.267768742269429
S.D.0.109131898841678
T-STAT2.45362488063999
p-value0.0397115974245909
Lambda0.732231257730571


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')