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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 computationMon, 19 Jan 2015 12:40:02 +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/2015/Jan/19/t1421671230ygjr1764mep8yku.htm/, Retrieved Thu, 31 Oct 2024 23:16:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=274510, Retrieved Thu, 31 Oct 2024 23:16:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Forecasting] [] [2014-12-01 19:48:40] [d50bb58b1f85cf0f681a6345fc450f33]
- RMPD    [Standard Deviation-Mean Plot] [] [2015-01-19 12:40:02] [138e2467cf1c89ca2583ec64b039d8e8] [Current]
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Dataseries X:
46
62
66
59
58
61
41
27
58
70
49
59
44
36
72
45
56
54
53
35
61
52
47
51
52
63
74
45
51
64
36
30
55
64
39
40
63
45
59
55
40
64
27
28
45
57
45
69
60
56
58
50
51
53
37
22
55
70
62
58
39
49
58
47
42
62
39
40
72
70
54
65




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=274510&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=274510&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=274510&T=0

As an alternative you can also use a 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
154.666666666666711.972189997378643
250.510.264679067736937
351.083333333333313.466850433789744
449.7513.712137954116742
552.666666666666712.470571418950848
653.083333333333312.191340692425433

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 54.6666666666667 & 11.9721899973786 & 43 \tabularnewline
2 & 50.5 & 10.2646790677369 & 37 \tabularnewline
3 & 51.0833333333333 & 13.4668504337897 & 44 \tabularnewline
4 & 49.75 & 13.7121379541167 & 42 \tabularnewline
5 & 52.6666666666667 & 12.4705714189508 & 48 \tabularnewline
6 & 53.0833333333333 & 12.1913406924254 & 33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=274510&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]54.6666666666667[/C][C]11.9721899973786[/C][C]43[/C][/ROW]
[ROW][C]2[/C][C]50.5[/C][C]10.2646790677369[/C][C]37[/C][/ROW]
[ROW][C]3[/C][C]51.0833333333333[/C][C]13.4668504337897[/C][C]44[/C][/ROW]
[ROW][C]4[/C][C]49.75[/C][C]13.7121379541167[/C][C]42[/C][/ROW]
[ROW][C]5[/C][C]52.6666666666667[/C][C]12.4705714189508[/C][C]48[/C][/ROW]
[ROW][C]6[/C][C]53.0833333333333[/C][C]12.1913406924254[/C][C]33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=274510&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=274510&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
154.666666666666711.972189997378643
250.510.264679067736937
351.083333333333313.466850433789744
449.7513.712137954116742
552.666666666666712.470571418950848
653.083333333333312.191340692425433







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha18.6919922134068
beta-0.122130501093962
S.D.0.33073593097988
T-STAT-0.369268923192358
p-value0.730644321403998

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 18.6919922134068 \tabularnewline
beta & -0.122130501093962 \tabularnewline
S.D. & 0.33073593097988 \tabularnewline
T-STAT & -0.369268923192358 \tabularnewline
p-value & 0.730644321403998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=274510&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]18.6919922134068[/C][/ROW]
[ROW][C]beta[/C][C]-0.122130501093962[/C][/ROW]
[ROW][C]S.D.[/C][C]0.33073593097988[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.369268923192358[/C][/ROW]
[ROW][C]p-value[/C][C]0.730644321403998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=274510&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=274510&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha18.6919922134068
beta-0.122130501093962
S.D.0.33073593097988
T-STAT-0.369268923192358
p-value0.730644321403998







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.09200505081258
beta-0.400772512903992
S.D.1.45747244856086
T-STAT-0.274977762564036
p-value0.796952199848241
Lambda1.40077251290399

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.09200505081258 \tabularnewline
beta & -0.400772512903992 \tabularnewline
S.D. & 1.45747244856086 \tabularnewline
T-STAT & -0.274977762564036 \tabularnewline
p-value & 0.796952199848241 \tabularnewline
Lambda & 1.40077251290399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=274510&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.09200505081258[/C][/ROW]
[ROW][C]beta[/C][C]-0.400772512903992[/C][/ROW]
[ROW][C]S.D.[/C][C]1.45747244856086[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.274977762564036[/C][/ROW]
[ROW][C]p-value[/C][C]0.796952199848241[/C][/ROW]
[ROW][C]Lambda[/C][C]1.40077251290399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=274510&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=274510&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.09200505081258
beta-0.400772512903992
S.D.1.45747244856086
T-STAT-0.274977762564036
p-value0.796952199848241
Lambda1.40077251290399



Parameters (Session):
par1 = 12 ; par2 = Triple ; par3 = additive ;
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')