FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 04 Dec 2009 09:08:44 -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/04/t1259942989urds7asjcrams82.htm/, Retrieved Sun, 28 Apr 2024 17:36:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63824, Retrieved Sun, 28 Apr 2024 17:36:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112

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] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
F    D      [Standard Deviation-Mean Plot] [] [2009-12-04 16:08:44] [1c886d75b2eec2d50a82160bb8104e3b] [Current]
Feedback Forum
2009-12-04 20:32:51 [d41d8cd98f00b204e9800998ecf8427e] [reply] 
Let er ook op dat deze link (en volgende links) een NO bevatten bij de kolom verified. Controleer of je elke stap juist uit hebt gevoerd bij het bloggen van je resultaten.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95.5
76.7
79.4
55.2
60
64.8
82.3
210.5
106
80.8
97.3
189.5
90
69.3
87.3
57.4
56.2
61.6
77.7
177.2
97.6
81.6
96.8
191.3
106
75.1
72
63.5
57.4
62.3
79.4
178.1
109.3
85.2
102.7
193.7
108.4
73.4
85.9
58.5
58.6
62.7
77.5
180.5
102.2
82.6
97.8
197.8
93.8
72.4
77.7
58.7
53.1
64.3
76.4
188.4
105.5
79.8
96.1
202.5

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'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=63824&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=63824&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63824&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
199.833333333333349.3401612801531155.3
295.333333333333344.0016390879276135.1
398.72544.3183550113166136.3
498.82545.3788522031213139.3
597.391666666666748.3612440311705149.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.8333333333333 & 49.3401612801531 & 155.3 \tabularnewline
2 & 95.3333333333333 & 44.0016390879276 & 135.1 \tabularnewline
3 & 98.725 & 44.3183550113166 & 136.3 \tabularnewline
4 & 98.825 & 45.3788522031213 & 139.3 \tabularnewline
5 & 97.3916666666667 & 48.3612440311705 & 149.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63824&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]99.8333333333333[/C][C]49.3401612801531[/C][C]155.3[/C][/ROW]
[ROW][C]2[/C][C]95.3333333333333[/C][C]44.0016390879276[/C][C]135.1[/C][/ROW]
[ROW][C]3[/C][C]98.725[/C][C]44.3183550113166[/C][C]136.3[/C][/ROW]
[ROW][C]4[/C][C]98.825[/C][C]45.3788522031213[/C][C]139.3[/C][/ROW]
[ROW][C]5[/C][C]97.3916666666667[/C][C]48.3612440311705[/C][C]149.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63824&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63824&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
199.833333333333349.3401612801531155.3
295.333333333333344.0016390879276135.1
398.72544.3183550113166136.3
498.82545.3788522031213139.3
597.391666666666748.3612440311705149.4






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-20.8855123054850
beta0.685211391646977
S.D.0.703616383731866
T-STAT0.97384229175098
p-value0.40196041114649

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -20.8855123054850 \tabularnewline
beta & 0.685211391646977 \tabularnewline
S.D. & 0.703616383731866 \tabularnewline
T-STAT & 0.97384229175098 \tabularnewline
p-value & 0.40196041114649 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63824&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-20.8855123054850[/C][/ROW]
[ROW][C]beta[/C][C]0.685211391646977[/C][/ROW]
[ROW][C]S.D.[/C][C]0.703616383731866[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.97384229175098[/C][/ROW]
[ROW][C]p-value[/C][C]0.40196041114649[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63824&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63824&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-20.8855123054850
beta0.685211391646977
S.D.0.703616383731866
T-STAT0.97384229175098
p-value0.40196041114649






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.75487854798168
beta1.43694895562838
S.D.1.47016560391023
T-STAT0.977406185947007
p-value0.400450617416752
Lambda-0.43694895562838

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.75487854798168 \tabularnewline
beta & 1.43694895562838 \tabularnewline
S.D. & 1.47016560391023 \tabularnewline
T-STAT & 0.977406185947007 \tabularnewline
p-value & 0.400450617416752 \tabularnewline
Lambda & -0.43694895562838 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63824&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.75487854798168[/C][/ROW]
[ROW][C]beta[/C][C]1.43694895562838[/C][/ROW]
[ROW][C]S.D.[/C][C]1.47016560391023[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.977406185947007[/C][/ROW]
[ROW][C]p-value[/C][C]0.400450617416752[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.43694895562838[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63824&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63824&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-2.75487854798168
beta1.43694895562838
S.D.1.47016560391023
T-STAT0.977406185947007
p-value0.400450617416752
Lambda-0.43694895562838


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')