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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 22 Dec 2016 22:38:22 +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/Dec/22/t1482446234b0ypfgsqtba9ezx.htm/, Retrieved Fri, 01 Nov 2024 03:45:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302719, Retrieved Fri, 01 Nov 2024 03:45:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

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] [ACF1] [2016-12-22 17:08:50] [267314984f6394bb93cd815224aa34ba]
- RM      [Standard Deviation-Mean Plot] [SMP1] [2016-12-22 21:38:22] [636d0f72197ac5e1dae4a755427db02a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2601.76
2819.1
2368.84
2683.5
2649.22
2760.3
2326
2819.3
2957.02
3460.5
2873.16
3252.48
3628.52
3899.22
3049.36
3751.58
4639.42
4991.02
4076.28
4782.4
5173.8
5177.94
4048.46
4828.98
4727.62
5366.84
4597.38
4838.16
4268.2
4769.34
4223.34
4396.38
4911.6
5368.4
4665
5081.46

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302719&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [ROW]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302719&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12797.59833333333324.6580217519331134.5
24337.24833333333688.3840045924862128.58
34767.81377.6480003678271145.06

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2797.59833333333 & 324.658021751933 & 1134.5 \tabularnewline
2 & 4337.24833333333 & 688.384004592486 & 2128.58 \tabularnewline
3 & 4767.81 & 377.648000367827 & 1145.06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302719&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]2797.59833333333[/C][C]324.658021751933[/C][C]1134.5[/C][/ROW]
[ROW][C]2[/C][C]4337.24833333333[/C][C]688.384004592486[/C][C]2128.58[/C][/ROW]
[ROW][C]3[/C][C]4767.81[/C][C]377.648000367827[/C][C]1145.06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302719&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
12797.59833333333324.6580217519331134.5
24337.24833333333688.3840045924862128.58
34767.81377.6480003678271145.06






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha136.538628513542
beta0.0824248038607308
S.D.0.170855517236782
T-STAT0.482424010613023
p-value0.713846917426077

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 136.538628513542 \tabularnewline
beta & 0.0824248038607308 \tabularnewline
S.D. & 0.170855517236782 \tabularnewline
T-STAT & 0.482424010613023 \tabularnewline
p-value & 0.713846917426077 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302719&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]136.538628513542[/C][/ROW]
[ROW][C]beta[/C][C]0.0824248038607308[/C][/ROW]
[ROW][C]S.D.[/C][C]0.170855517236782[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.482424010613023[/C][/ROW]
[ROW][C]p-value[/C][C]0.713846917426077[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302719&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)
alpha136.538628513542
beta0.0824248038607308
S.D.0.170855517236782
T-STAT0.482424010613023
p-value0.713846917426077






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.0714189116609397
beta0.727844424509196
S.D.1.19309240806178
T-STAT0.610048659761071
p-value0.651275300738856
Lambda0.272155575490804

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.0714189116609397 \tabularnewline
beta & 0.727844424509196 \tabularnewline
S.D. & 1.19309240806178 \tabularnewline
T-STAT & 0.610048659761071 \tabularnewline
p-value & 0.651275300738856 \tabularnewline
Lambda & 0.272155575490804 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302719&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0714189116609397[/C][/ROW]
[ROW][C]beta[/C][C]0.727844424509196[/C][/ROW]
[ROW][C]S.D.[/C][C]1.19309240806178[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.610048659761071[/C][/ROW]
[ROW][C]p-value[/C][C]0.651275300738856[/C][/ROW]
[ROW][C]Lambda[/C][C]0.272155575490804[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302719&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302719&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)
alpha0.0714189116609397
beta0.727844424509196
S.D.1.19309240806178
T-STAT0.610048659761071
p-value0.651275300738856
Lambda0.272155575490804


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ; par2 = -0.3 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 0 ; par10 = FALSE ;
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')