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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 computationSun, 22 Nov 2015 22:48:26 +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/Nov/22/t1448232522a2p3hjatba5ben8.htm/, Retrieved Wed, 15 May 2024 03:54:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283908, Retrieved Wed, 15 May 2024 03:54:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

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] [] [2015-11-22 22:48:26] [06d8efd1cada8e807c830d2ff46bf732] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
31902
30260
32823
32018
32100
31952
33274
29491
32751
33643
31226
30976

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=283908&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=283908&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283908&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
127994.08333333331596.594697720086036
222835.51237.022341240153380
327659.52025.386225794076251
430410.08333333331354.546449308164799
532454.08333333331334.26046648484185
632196.0833333333959.5588435538623566
7318681219.065663083454152

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 27994.0833333333 & 1596.59469772008 & 6036 \tabularnewline
2 & 22835.5 & 1237.02234124015 & 3380 \tabularnewline
3 & 27659.5 & 2025.38622579407 & 6251 \tabularnewline
4 & 30410.0833333333 & 1354.54644930816 & 4799 \tabularnewline
5 & 32454.0833333333 & 1334.2604664848 & 4185 \tabularnewline
6 & 32196.0833333333 & 959.558843553862 & 3566 \tabularnewline
7 & 31868 & 1219.06566308345 & 4152 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283908&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]27994.0833333333[/C][C]1596.59469772008[/C][C]6036[/C][/ROW]
[ROW][C]2[/C][C]22835.5[/C][C]1237.02234124015[/C][C]3380[/C][/ROW]
[ROW][C]3[/C][C]27659.5[/C][C]2025.38622579407[/C][C]6251[/C][/ROW]
[ROW][C]4[/C][C]30410.0833333333[/C][C]1354.54644930816[/C][C]4799[/C][/ROW]
[ROW][C]5[/C][C]32454.0833333333[/C][C]1334.2604664848[/C][C]4185[/C][/ROW]
[ROW][C]6[/C][C]32196.0833333333[/C][C]959.558843553862[/C][C]3566[/C][/ROW]
[ROW][C]7[/C][C]31868[/C][C]1219.06566308345[/C][C]4152[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283908&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283908&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
127994.08333333331596.594697720086036
222835.51237.022341240153380
327659.52025.386225794076251
430410.08333333331354.546449308164799
532454.08333333331334.26046648484185
632196.0833333333959.5588435538623566
7318681219.065663083454152






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2291.65353527925
beta-0.0307429755673173
S.D.0.0414134145452579
T-STAT-0.742343414685607
p-value0.491259126816701

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2291.65353527925 \tabularnewline
beta & -0.0307429755673173 \tabularnewline
S.D. & 0.0414134145452579 \tabularnewline
T-STAT & -0.742343414685607 \tabularnewline
p-value & 0.491259126816701 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283908&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2291.65353527925[/C][/ROW]
[ROW][C]beta[/C][C]-0.0307429755673173[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0414134145452579[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.742343414685607[/C][/ROW]
[ROW][C]p-value[/C][C]0.491259126816701[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283908&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283908&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)
alpha2291.65353527925
beta-0.0307429755673173
S.D.0.0414134145452579
T-STAT-0.742343414685607
p-value0.491259126816701






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha12.7116415227792
beta-0.534891860291371
S.D.0.794204416550691
T-STAT-0.673493938266498
p-value0.530504542449341
Lambda1.53489186029137

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 12.7116415227792 \tabularnewline
beta & -0.534891860291371 \tabularnewline
S.D. & 0.794204416550691 \tabularnewline
T-STAT & -0.673493938266498 \tabularnewline
p-value & 0.530504542449341 \tabularnewline
Lambda & 1.53489186029137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283908&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.7116415227792[/C][/ROW]
[ROW][C]beta[/C][C]-0.534891860291371[/C][/ROW]
[ROW][C]S.D.[/C][C]0.794204416550691[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.673493938266498[/C][/ROW]
[ROW][C]p-value[/C][C]0.530504542449341[/C][/ROW]
[ROW][C]Lambda[/C][C]1.53489186029137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283908&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283908&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)
alpha12.7116415227792
beta-0.534891860291371
S.D.0.794204416550691
T-STAT-0.673493938266498
p-value0.530504542449341
Lambda1.53489186029137


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')