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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 computationSat, 22 Nov 2014 11:06:19 +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/22/t1416654930lnnvuhjo12tdae8.htm/, Retrieved Tue, 28 May 2024 17:34:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257811, Retrieved Tue, 28 May 2024 17:34:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

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] [] [2014-11-22 11:06:19] [e9c24c4a54e855481a8eaf4353236c0f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
24175
23658
26727
24397
25829
25503
24914
24875
25461
27647
28382
25259
28100
27900
28078
28479
28156
29219
28782
27078
30031
29579
26532
23995
22067
21818
23787
21551
21309
22395
22906
21430
23492
24144
24438
24689
24569
23754
28473
27051
27081
29635
27715
26373
28009
29472
30005
29777
28886
28549
33348
29017
30924
30435
29431
30290
31286
30622
31742
30391
30740
32086
33947
31312
33239
32362
32170
32665
31412
34891
33919
30706
32846
31368
33130
31665
33139
32201
32230
30287
31918
33853
32232
31484

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'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=257811&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=257811&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257811&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
125568.91666666671402.307802959974724
227994.08333333331596.594697720086036
322835.51237.022341240153380
427659.52025.386225794076251
530410.08333333331354.546449308164799
632454.08333333331334.26046648484185
732196.0833333333959.5588435538623566

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 25568.9166666667 & 1402.30780295997 & 4724 \tabularnewline
2 & 27994.0833333333 & 1596.59469772008 & 6036 \tabularnewline
3 & 22835.5 & 1237.02234124015 & 3380 \tabularnewline
4 & 27659.5 & 2025.38622579407 & 6251 \tabularnewline
5 & 30410.0833333333 & 1354.54644930816 & 4799 \tabularnewline
6 & 32454.0833333333 & 1334.2604664848 & 4185 \tabularnewline
7 & 32196.0833333333 & 959.558843553862 & 3566 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257811&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]25568.9166666667[/C][C]1402.30780295997[/C][C]4724[/C][/ROW]
[ROW][C]2[/C][C]27994.0833333333[/C][C]1596.59469772008[/C][C]6036[/C][/ROW]
[ROW][C]3[/C][C]22835.5[/C][C]1237.02234124015[/C][C]3380[/C][/ROW]
[ROW][C]4[/C][C]27659.5[/C][C]2025.38622579407[/C][C]6251[/C][/ROW]
[ROW][C]5[/C][C]30410.0833333333[/C][C]1354.54644930816[/C][C]4799[/C][/ROW]
[ROW][C]6[/C][C]32454.0833333333[/C][C]1334.2604664848[/C][C]4185[/C][/ROW]
[ROW][C]7[/C][C]32196.0833333333[/C][C]959.558843553862[/C][C]3566[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257811&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257811&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
125568.91666666671402.307802959974724
227994.08333333331596.594697720086036
322835.51237.022341240153380
427659.52025.386225794076251
530410.08333333331354.546449308164799
632454.08333333331334.26046648484185
732196.0833333333959.5588435538623566






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2055.56878402751
beta-0.0224957012284482
S.D.0.0406894337931755
T-STAT-0.552863461870566
p-value0.604163655628584

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2055.56878402751 \tabularnewline
beta & -0.0224957012284482 \tabularnewline
S.D. & 0.0406894337931755 \tabularnewline
T-STAT & -0.552863461870566 \tabularnewline
p-value & 0.604163655628584 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257811&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2055.56878402751[/C][/ROW]
[ROW][C]beta[/C][C]-0.0224957012284482[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0406894337931755[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.552863461870566[/C][/ROW]
[ROW][C]p-value[/C][C]0.604163655628584[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257811&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257811&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)
alpha2055.56878402751
beta-0.0224957012284482
S.D.0.0406894337931755
T-STAT-0.552863461870566
p-value0.604163655628584






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha11.5751322016196
beta-0.423691167367285
S.D.0.779979768222797
T-STAT-0.543207894138942
p-value0.610317389157062
Lambda1.42369116736729

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 11.5751322016196 \tabularnewline
beta & -0.423691167367285 \tabularnewline
S.D. & 0.779979768222797 \tabularnewline
T-STAT & -0.543207894138942 \tabularnewline
p-value & 0.610317389157062 \tabularnewline
Lambda & 1.42369116736729 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257811&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]11.5751322016196[/C][/ROW]
[ROW][C]beta[/C][C]-0.423691167367285[/C][/ROW]
[ROW][C]S.D.[/C][C]0.779979768222797[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.543207894138942[/C][/ROW]
[ROW][C]p-value[/C][C]0.610317389157062[/C][/ROW]
[ROW][C]Lambda[/C][C]1.42369116736729[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257811&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257811&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)
alpha11.5751322016196
beta-0.423691167367285
S.D.0.779979768222797
T-STAT-0.543207894138942
p-value0.610317389157062
Lambda1.42369116736729


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')