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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 computationSat, 22 Nov 2014 10:59:52 +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/22/t1416654195x4lt89uhk2w2sb2.htm/, Retrieved Sun, 19 May 2024 15:56:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257808, Retrieved Sun, 19 May 2024 15:56:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102

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] [] [2014-11-22 10:59:52] [25af208440423f5cc2d7fa35cacd4ca5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27
2513.17
2466.92
2502.66
2539.91
2482.6
2626.15
2656.32
2446.66
2467.38
2462.32
2504.58
2579.39
2649.24
2636.87
2613.94
2634.01
2711.94
2646.43
2717.79
2701.54
2572.98
2488.92
2204.91
2123.99
2149.1
2036.71
2048.32
2159.56
2267.79
2313.55
2247.3
2134.43
2114
2236.94
2345.39
2422.4
2385.96
2378.17
2457.13
2527.67
2530.03
2604.92
2596.8
2713.2
2574.82
2611.98
2768.46
2785.61
2859.27
2880.53
2824.5

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'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257808&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257808&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257808&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'George Udny Yule' @ yule.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13126.66583333333740.9765292376411994.79
22135.2325298.12292754759843.1
32555.4466666666780.3370105281872209.66
42419.72281.348220828987681.08
52288.55166666667114.163561360113343.13
62689.81583333333130.06962103975352.86

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3126.66583333333 & 740.976529237641 & 1994.79 \tabularnewline
2 & 2135.2325 & 298.12292754759 & 843.1 \tabularnewline
3 & 2555.44666666667 & 80.3370105281872 & 209.66 \tabularnewline
4 & 2419.72 & 281.348220828987 & 681.08 \tabularnewline
5 & 2288.55166666667 & 114.163561360113 & 343.13 \tabularnewline
6 & 2689.81583333333 & 130.06962103975 & 352.86 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257808&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]3126.66583333333[/C][C]740.976529237641[/C][C]1994.79[/C][/ROW]
[ROW][C]2[/C][C]2135.2325[/C][C]298.12292754759[/C][C]843.1[/C][/ROW]
[ROW][C]3[/C][C]2555.44666666667[/C][C]80.3370105281872[/C][C]209.66[/C][/ROW]
[ROW][C]4[/C][C]2419.72[/C][C]281.348220828987[/C][C]681.08[/C][/ROW]
[ROW][C]5[/C][C]2288.55166666667[/C][C]114.163561360113[/C][C]343.13[/C][/ROW]
[ROW][C]6[/C][C]2689.81583333333[/C][C]130.06962103975[/C][C]352.86[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257808&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257808&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
13126.66583333333740.9765292376411994.79
22135.2325298.12292754759843.1
32555.4466666666780.3370105281872209.66
42419.72281.348220828987681.08
52288.55166666667114.163561360113343.13
62689.81583333333130.06962103975352.86






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-888.753637714792
beta0.458583066687787
S.D.0.267839057744889
T-STAT1.71215905009858
p-value0.162030554440059

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -888.753637714792 \tabularnewline
beta & 0.458583066687787 \tabularnewline
S.D. & 0.267839057744889 \tabularnewline
T-STAT & 1.71215905009858 \tabularnewline
p-value & 0.162030554440059 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257808&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-888.753637714792[/C][/ROW]
[ROW][C]beta[/C][C]0.458583066687787[/C][/ROW]
[ROW][C]S.D.[/C][C]0.267839057744889[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.71215905009858[/C][/ROW]
[ROW][C]p-value[/C][C]0.162030554440059[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257808&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257808&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)
alpha-888.753637714792
beta0.458583066687787
S.D.0.267839057744889
T-STAT1.71215905009858
p-value0.162030554440059






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-13.600184036737
beta2.41650924876398
S.D.2.79751786579417
T-STAT0.863804760037868
p-value0.436415857000063
Lambda-1.41650924876398

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -13.600184036737 \tabularnewline
beta & 2.41650924876398 \tabularnewline
S.D. & 2.79751786579417 \tabularnewline
T-STAT & 0.863804760037868 \tabularnewline
p-value & 0.436415857000063 \tabularnewline
Lambda & -1.41650924876398 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257808&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.600184036737[/C][/ROW]
[ROW][C]beta[/C][C]2.41650924876398[/C][/ROW]
[ROW][C]S.D.[/C][C]2.79751786579417[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.863804760037868[/C][/ROW]
[ROW][C]p-value[/C][C]0.436415857000063[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.41650924876398[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257808&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257808&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)
alpha-13.600184036737
beta2.41650924876398
S.D.2.79751786579417
T-STAT0.863804760037868
p-value0.436415857000063
Lambda-1.41650924876398


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')