Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 26 May 2010 19:11:09 +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/2010/May/26/t1274901258eitxv5a774a8vms.htm/, Retrieved Fri, 03 May 2024 10:26:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76543, Retrieved Fri, 03 May 2024 10:26:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [] [2010-05-26 19:08:03] [5a3034bcadf7735f2909fd8cdba599d5]
-   P     [Standard Deviation-Mean Plot] [] [2010-05-26 19:11:09] [ac302f869d0778eba7cafda3b14e71eb] [Current]
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Dataseries X:
70.5
70.65
70.71
15.80
170.99
15.26
17.21
16.97
16.80
18.37
18.53
18.708
18.73
18.63
19.15
19.76
20.02
20.26
20.32
20.52
20.81
21.26
22.15
23.05
270.01
270.69
70.38
26.33
27.36
28.55
30.10
32.20
36.28
700.91
7070.66
707.83
709.97
52.20
55.67
59.92
65.15
70.17
770.6
78.23
79.27
80.707
81.701
83.97
86.83
89.61
91.79
970.32
96.56
97.98
100.00
101.63
102.60
103.75
106.39
109.02
110.81
112.57
1170.93
118.13
120.7
122.707
127.97
127.87




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76543&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76543&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76543&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
143.374833333333346.7122354651489155.73
220.38833333333331.316668200996424.42
3772.6083333333331999.547566593437044.33
4182.2965261.172816454581718.4
5171.373333333333251.691994467023883.49

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 43.3748333333333 & 46.7122354651489 & 155.73 \tabularnewline
2 & 20.3883333333333 & 1.31666820099642 & 4.42 \tabularnewline
3 & 772.608333333333 & 1999.54756659343 & 7044.33 \tabularnewline
4 & 182.2965 & 261.172816454581 & 718.4 \tabularnewline
5 & 171.373333333333 & 251.691994467023 & 883.49 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76543&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]43.3748333333333[/C][C]46.7122354651489[/C][C]155.73[/C][/ROW]
[ROW][C]2[/C][C]20.3883333333333[/C][C]1.31666820099642[/C][C]4.42[/C][/ROW]
[ROW][C]3[/C][C]772.608333333333[/C][C]1999.54756659343[/C][C]7044.33[/C][/ROW]
[ROW][C]4[/C][C]182.2965[/C][C]261.172816454581[/C][C]718.4[/C][/ROW]
[ROW][C]5[/C][C]171.373333333333[/C][C]251.691994467023[/C][C]883.49[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76543&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76543&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
143.374833333333346.7122354651489155.73
220.38833333333331.316668200996424.42
3772.6083333333331999.547566593437044.33
4182.2965261.172816454581718.4
5171.373333333333251.691994467023883.49







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-134.360911353985
beta2.71607863308202
S.D.0.156824961991704
T-STAT17.3191729083646
p-value0.00041947046026568

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -134.360911353985 \tabularnewline
beta & 2.71607863308202 \tabularnewline
S.D. & 0.156824961991704 \tabularnewline
T-STAT & 17.3191729083646 \tabularnewline
p-value & 0.00041947046026568 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76543&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-134.360911353985[/C][/ROW]
[ROW][C]beta[/C][C]2.71607863308202[/C][/ROW]
[ROW][C]S.D.[/C][C]0.156824961991704[/C][/ROW]
[ROW][C]T-STAT[/C][C]17.3191729083646[/C][/ROW]
[ROW][C]p-value[/C][C]0.00041947046026568[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76543&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76543&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)
alpha-134.360911353985
beta2.71607863308202
S.D.0.156824961991704
T-STAT17.3191729083646
p-value0.00041947046026568







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.27234025747147
beta1.85732858607849
S.D.0.334562275455561
T-STAT5.55151827428672
p-value0.0115264763155871
Lambda-0.857328586078492

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.27234025747147 \tabularnewline
beta & 1.85732858607849 \tabularnewline
S.D. & 0.334562275455561 \tabularnewline
T-STAT & 5.55151827428672 \tabularnewline
p-value & 0.0115264763155871 \tabularnewline
Lambda & -0.857328586078492 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76543&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.27234025747147[/C][/ROW]
[ROW][C]beta[/C][C]1.85732858607849[/C][/ROW]
[ROW][C]S.D.[/C][C]0.334562275455561[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.55151827428672[/C][/ROW]
[ROW][C]p-value[/C][C]0.0115264763155871[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.857328586078492[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76543&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76543&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)
alpha-4.27234025747147
beta1.85732858607849
S.D.0.334562275455561
T-STAT5.55151827428672
p-value0.0115264763155871
Lambda-0.857328586078492



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')