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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 computationSat, 26 Dec 2009 07:08:02 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/26/t1261836624o4cthrsfkfxzy3w.htm/, Retrieved Sun, 28 Apr 2024 21:48:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70746, Retrieved Sun, 28 Apr 2024 21:48:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Paper] [2009-12-21 20:42:12] [0df1a6455bedfaf424729b1e006090d0]
- RMPD    [Standard Deviation-Mean Plot] [Paper SDMP] [2009-12-26 14:08:02] [e2f800c9186517d2e5c4a809848912a7] [Current]
- RMP       [ARIMA Forecasting] [Paper] [2009-12-29 14:38:50] [b6394cb5c2dcec6d17418d3cdf42d699]
- RMP       [ARIMA Backward Selection] [paper] [2009-12-29 15:24:21] [b6394cb5c2dcec6d17418d3cdf42d699]
- RMP       [ARIMA Backward Selection] [Paper] [2009-12-29 15:27:00] [b6394cb5c2dcec6d17418d3cdf42d699]
-   P         [ARIMA Backward Selection] [Jan speciaal voor u] [2009-12-30 14:22:10] [bd8e774728cf1f2f4e6868fd314defe3]
- RMP       [ARIMA Backward Selection] [paper] [2009-12-29 15:29:50] [b6394cb5c2dcec6d17418d3cdf42d699]
- RMP         [ARIMA Forecasting] [Paper] [2009-12-30 16:21:20] [b6394cb5c2dcec6d17418d3cdf42d699]
- RMP       [ARIMA Backward Selection] [paper] [2009-12-29 17:31:46] [b6394cb5c2dcec6d17418d3cdf42d699]
- RMP         [ARIMA Forecasting] [paper] [2009-12-29 17:41:43] [b6394cb5c2dcec6d17418d3cdf42d699]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.202
1.2271
1.277
1.265
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
1.4684
1.457
1.4718
1.4748
1.5527
1.5751
1.5557
1.5553
1.577
1.4975
1.437
1.3322
1.2732
1.3449

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70746&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70746&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70746&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.243333333333330.04244370246323800.1423
21.2447750.05156309682850180.1415
31.255658333333330.03886141948311230.1275
41.370633333333330.05467872003112750.1685
51.47060.1040940047177640.3038

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.24333333333333 & 0.0424437024632380 & 0.1423 \tabularnewline
2 & 1.244775 & 0.0515630968285018 & 0.1415 \tabularnewline
3 & 1.25565833333333 & 0.0388614194831123 & 0.1275 \tabularnewline
4 & 1.37063333333333 & 0.0546787200311275 & 0.1685 \tabularnewline
5 & 1.4706 & 0.104094004717764 & 0.3038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70746&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]1.24333333333333[/C][C]0.0424437024632380[/C][C]0.1423[/C][/ROW]
[ROW][C]2[/C][C]1.244775[/C][C]0.0515630968285018[/C][C]0.1415[/C][/ROW]
[ROW][C]3[/C][C]1.25565833333333[/C][C]0.0388614194831123[/C][C]0.1275[/C][/ROW]
[ROW][C]4[/C][C]1.37063333333333[/C][C]0.0546787200311275[/C][C]0.1685[/C][/ROW]
[ROW][C]5[/C][C]1.4706[/C][C]0.104094004717764[/C][C]0.3038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70746&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70746&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
11.243333333333330.04244370246323800.1423
21.2447750.05156309682850180.1415
31.255658333333330.03886141948311230.1275
41.370633333333330.05467872003112750.1685
51.47060.1040940047177640.3038






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.253777845720314
beta0.236982562205818
S.D.0.0631656464169553
T-STAT3.75176342915104
p-value0.0330762618806368

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.253777845720314 \tabularnewline
beta & 0.236982562205818 \tabularnewline
S.D. & 0.0631656464169553 \tabularnewline
T-STAT & 3.75176342915104 \tabularnewline
p-value & 0.0330762618806368 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70746&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.253777845720314[/C][/ROW]
[ROW][C]beta[/C][C]0.236982562205818[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0631656464169553[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.75176342915104[/C][/ROW]
[ROW][C]p-value[/C][C]0.0330762618806368[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70746&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70746&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-0.253777845720314
beta0.236982562205818
S.D.0.0631656464169553
T-STAT3.75176342915104
p-value0.0330762618806368






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.18435040714406
beta4.67331602810904
S.D.1.25986981629393
T-STAT3.70936422769157
p-value0.0340564914220092
Lambda-3.67331602810904

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.18435040714406 \tabularnewline
beta & 4.67331602810904 \tabularnewline
S.D. & 1.25986981629393 \tabularnewline
T-STAT & 3.70936422769157 \tabularnewline
p-value & 0.0340564914220092 \tabularnewline
Lambda & -3.67331602810904 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70746&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.18435040714406[/C][/ROW]
[ROW][C]beta[/C][C]4.67331602810904[/C][/ROW]
[ROW][C]S.D.[/C][C]1.25986981629393[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.70936422769157[/C][/ROW]
[ROW][C]p-value[/C][C]0.0340564914220092[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.67331602810904[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70746&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70746&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-4.18435040714406
beta4.67331602810904
S.D.1.25986981629393
T-STAT3.70936422769157
p-value0.0340564914220092
Lambda-3.67331602810904


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')