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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 09:31:18 +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/t1470817898s6l5qhq099webun.htm/, Retrieved Tue, 30 Apr 2024 01:08:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296181, Retrieved Tue, 30 Apr 2024 01:08:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2016-08-10 08:31:18] [eed3b94f44ab74d862a61d666a631b56] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7263.63
7135.88
7008.00
6752.38
9339.00
9211.13
7263.63
5970.38
6098.13
6098.13
6226.00
6495.50
5714.75
4932.75
4292.38
4292.38
6752.38
7008.00
5060.50
2857.38
4022.88
4022.88
4932.75
5457.88
5330.00
4022.88
4677.13
4420.25
6623.38
6098.13
4022.88
2472.75
3895.00
4292.38
4677.13
5188.38
4150.63
3254.75
3639.50
3767.25
7135.88
7135.88
5188.38
4932.75
5714.75
5330.00
6367.75
7661.00
7917.88
6098.13
5585.63
5060.50
8570.88
8827.75
8173.50
8827.75
8698.63
7661.00
8827.75
10121.00
10646.13
9083.38
8045.63
8827.75
12196.25
13234.00
12978.38
13489.50
13361.75
12068.50
14271.63
14796.75
15564.88
13234.00
12324.13
13361.75
15834.38
18037.50
17512.38
17512.38
17769.25
16872.00
19204.25
19204.25
18806.88
16602.50
16999.88
17256.75
18947.38
21150.50
19587.63
20369.75
19715.50
19332.00
22317.25
21663.00
20753.13
19459.88
20753.13
21407.38
22188.13
23225.75
22188.13
22828.50
22047.63
21919.88
25160.63
25430.13
24392.50
22572.88
24123.00
24776.00
25558.00
26723.50
25558.00
26467.88
26070.50
24648.13
27633.25
27633.25

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296181&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296181&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296181&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17071.815833333331130.463456475493368.62
24945.575833333331179.459907187564150.62
34643.35751088.041753210584150.63
45356.543333333331487.764856483674406.25
57864.21519.137271521995060.5
611916.63752246.911681571866751.12
716369.26252332.667214265976880.12
819395.75166666671821.889468445695714.75
922280.19166666671731.904153950125970.25
1025513.07416666671501.695325432735060.37

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7071.81583333333 & 1130.46345647549 & 3368.62 \tabularnewline
2 & 4945.57583333333 & 1179.45990718756 & 4150.62 \tabularnewline
3 & 4643.3575 & 1088.04175321058 & 4150.63 \tabularnewline
4 & 5356.54333333333 & 1487.76485648367 & 4406.25 \tabularnewline
5 & 7864.2 & 1519.13727152199 & 5060.5 \tabularnewline
6 & 11916.6375 & 2246.91168157186 & 6751.12 \tabularnewline
7 & 16369.2625 & 2332.66721426597 & 6880.12 \tabularnewline
8 & 19395.7516666667 & 1821.88946844569 & 5714.75 \tabularnewline
9 & 22280.1916666667 & 1731.90415395012 & 5970.25 \tabularnewline
10 & 25513.0741666667 & 1501.69532543273 & 5060.37 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296181&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]7071.81583333333[/C][C]1130.46345647549[/C][C]3368.62[/C][/ROW]
[ROW][C]2[/C][C]4945.57583333333[/C][C]1179.45990718756[/C][C]4150.62[/C][/ROW]
[ROW][C]3[/C][C]4643.3575[/C][C]1088.04175321058[/C][C]4150.63[/C][/ROW]
[ROW][C]4[/C][C]5356.54333333333[/C][C]1487.76485648367[/C][C]4406.25[/C][/ROW]
[ROW][C]5[/C][C]7864.2[/C][C]1519.13727152199[/C][C]5060.5[/C][/ROW]
[ROW][C]6[/C][C]11916.6375[/C][C]2246.91168157186[/C][C]6751.12[/C][/ROW]
[ROW][C]7[/C][C]16369.2625[/C][C]2332.66721426597[/C][C]6880.12[/C][/ROW]
[ROW][C]8[/C][C]19395.7516666667[/C][C]1821.88946844569[/C][C]5714.75[/C][/ROW]
[ROW][C]9[/C][C]22280.1916666667[/C][C]1731.90415395012[/C][C]5970.25[/C][/ROW]
[ROW][C]10[/C][C]25513.0741666667[/C][C]1501.69532543273[/C][C]5060.37[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296181&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296181&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
17071.815833333331130.463456475493368.62
24945.575833333331179.459907187564150.62
34643.35751088.041753210584150.63
45356.543333333331487.764856483674406.25
57864.21519.137271521995060.5
611916.63752246.911681571866751.12
716369.26252332.667214265976880.12
819395.75166666671821.889468445695714.75
922280.19166666671731.904153950125970.25
1025513.07416666671501.695325432735060.37






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1263.04767761151
beta0.0271981170522561
S.D.0.0172378037916458
T-STAT1.57781799706048
p-value0.153259432725856

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1263.04767761151 \tabularnewline
beta & 0.0271981170522561 \tabularnewline
S.D. & 0.0172378037916458 \tabularnewline
T-STAT & 1.57781799706048 \tabularnewline
p-value & 0.153259432725856 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296181&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1263.04767761151[/C][/ROW]
[ROW][C]beta[/C][C]0.0271981170522561[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0172378037916458[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.57781799706048[/C][/ROW]
[ROW][C]p-value[/C][C]0.153259432725856[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296181&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296181&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)
alpha1263.04767761151
beta0.0271981170522561
S.D.0.0172378037916458
T-STAT1.57781799706048
p-value0.153259432725856






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.87118772869888
beta0.267764551575418
S.D.0.109132932911616
T-STAT2.45356323184564
p-value0.0397154155420084
Lambda0.732235448424582

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.87118772869888 \tabularnewline
beta & 0.267764551575418 \tabularnewline
S.D. & 0.109132932911616 \tabularnewline
T-STAT & 2.45356323184564 \tabularnewline
p-value & 0.0397154155420084 \tabularnewline
Lambda & 0.732235448424582 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296181&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.87118772869888[/C][/ROW]
[ROW][C]beta[/C][C]0.267764551575418[/C][/ROW]
[ROW][C]S.D.[/C][C]0.109132932911616[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.45356323184564[/C][/ROW]
[ROW][C]p-value[/C][C]0.0397154155420084[/C][/ROW]
[ROW][C]Lambda[/C][C]0.732235448424582[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296181&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296181&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)
alpha4.87118772869888
beta0.267764551575418
S.D.0.109132932911616
T-STAT2.45356323184564
p-value0.0397154155420084
Lambda0.732235448424582


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')