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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 computationFri, 21 Nov 2014 15:33:02 +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/2014/Nov/21/t1416584088y1dnwat3y28f1em.htm/, Retrieved Sun, 19 May 2024 10:10:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257657, Retrieved Sun, 19 May 2024 10:10:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

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] [Spreidings- en gr...] [2014-11-21 15:33:02] [be7d2a6a6c016378f31f309d9b06695b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
71
77
76
69
74
101
105
73
68
65
70
65
80
92
93
90
96
125
134
100
97
97
101
90
108
113
112
103
103
125
128
91
84
83
83
69
77
83
78
70
75
101
117
80
87
81
78
73
93
105
102
97
100
127
138
107
107
106
109
107
129
138
137
134
134
166
180
131
135
127
121
116

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=257657&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=257657&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257657&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
176.166666666666713.127579111676840
299.583333333333315.156506753526654
3100.16666666666718.289755370566159
483.333333333333313.234482050745947
5108.16666666666712.517866020091845
6137.33333333333318.112443403931164

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 76.1666666666667 & 13.1275791116768 & 40 \tabularnewline
2 & 99.5833333333333 & 15.1565067535266 & 54 \tabularnewline
3 & 100.166666666667 & 18.2897553705661 & 59 \tabularnewline
4 & 83.3333333333333 & 13.2344820507459 & 47 \tabularnewline
5 & 108.166666666667 & 12.5178660200918 & 45 \tabularnewline
6 & 137.333333333333 & 18.1124434039311 & 64 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257657&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]76.1666666666667[/C][C]13.1275791116768[/C][C]40[/C][/ROW]
[ROW][C]2[/C][C]99.5833333333333[/C][C]15.1565067535266[/C][C]54[/C][/ROW]
[ROW][C]3[/C][C]100.166666666667[/C][C]18.2897553705661[/C][C]59[/C][/ROW]
[ROW][C]4[/C][C]83.3333333333333[/C][C]13.2344820507459[/C][C]47[/C][/ROW]
[ROW][C]5[/C][C]108.166666666667[/C][C]12.5178660200918[/C][C]45[/C][/ROW]
[ROW][C]6[/C][C]137.333333333333[/C][C]18.1124434039311[/C][C]64[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257657&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257657&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
176.166666666666713.127579111676840
299.583333333333315.156506753526654
3100.16666666666718.289755370566159
483.333333333333313.234482050745947
5108.16666666666712.517866020091845
6137.33333333333318.112443403931164






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha7.62707995711667
beta0.073875407966661
S.D.0.0474278632560988
T-STAT1.55763728101669
p-value0.194315422622801

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 7.62707995711667 \tabularnewline
beta & 0.073875407966661 \tabularnewline
S.D. & 0.0474278632560988 \tabularnewline
T-STAT & 1.55763728101669 \tabularnewline
p-value & 0.194315422622801 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257657&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.62707995711667[/C][/ROW]
[ROW][C]beta[/C][C]0.073875407966661[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0474278632560988[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.55763728101669[/C][/ROW]
[ROW][C]p-value[/C][C]0.194315422622801[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257657&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257657&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)
alpha7.62707995711667
beta0.073875407966661
S.D.0.0474278632560988
T-STAT1.55763728101669
p-value0.194315422622801






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.450388740343593
beta0.489803732158539
S.D.0.323918458794173
T-STAT1.5121204700155
p-value0.205042846817311
Lambda0.510196267841461

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.450388740343593 \tabularnewline
beta & 0.489803732158539 \tabularnewline
S.D. & 0.323918458794173 \tabularnewline
T-STAT & 1.5121204700155 \tabularnewline
p-value & 0.205042846817311 \tabularnewline
Lambda & 0.510196267841461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257657&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.450388740343593[/C][/ROW]
[ROW][C]beta[/C][C]0.489803732158539[/C][/ROW]
[ROW][C]S.D.[/C][C]0.323918458794173[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.5121204700155[/C][/ROW]
[ROW][C]p-value[/C][C]0.205042846817311[/C][/ROW]
[ROW][C]Lambda[/C][C]0.510196267841461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257657&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257657&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)
alpha0.450388740343593
beta0.489803732158539
S.D.0.323918458794173
T-STAT1.5121204700155
p-value0.205042846817311
Lambda0.510196267841461


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')