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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 20 Nov 2014 20:23:04 +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/20/t1416515080mmgicbfni1ftp2z.htm/, Retrieved Sun, 19 May 2024 16:13:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=257395, Retrieved Sun, 19 May 2024 16:13:01 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2014-11-20 20:23:04] [5fd46a639be569026986aaac39788635] [Current]
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Dataseries X:
3004
3080
3017
3114
3057
3032
3127
3050
2910
2671
2638
2672
2654
2568
2467
2419
2363
2291
2560
2527
2370
2310
2231
2367
2346
2286
2249
2226
2108
2131
2387
2358
2284
2312
2293
2576
2665
2749
2926
2886
2893
2944
3060
3045
2894
2955
2954
3243
3120
3074
3034
2981
2876
2835
2978
2881
2768
2722
2630
2753
2771
2652
2584
2501
2449
2445
2620
2579
2460
2434
2392
1037
1212
1232
1174
1158
1140
1118
1212
1207
1186
608
627
626
649
619
612
643
623
649
699
693
659
669
668
693




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=257395&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=257395&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257395&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'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12947.66666666667182.085560973822489
22427.25128.738017977314423
32296.33333333333121.808593019267468
42934.5146.737551740886578
52887.66666666667152.622727566038490
62410.33333333333446.3362640499431734
71041.66666666667256.152771650518624
8656.33333333333329.493707598041887

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2947.66666666667 & 182.085560973822 & 489 \tabularnewline
2 & 2427.25 & 128.738017977314 & 423 \tabularnewline
3 & 2296.33333333333 & 121.808593019267 & 468 \tabularnewline
4 & 2934.5 & 146.737551740886 & 578 \tabularnewline
5 & 2887.66666666667 & 152.622727566038 & 490 \tabularnewline
6 & 2410.33333333333 & 446.336264049943 & 1734 \tabularnewline
7 & 1041.66666666667 & 256.152771650518 & 624 \tabularnewline
8 & 656.333333333333 & 29.4937075980418 & 87 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257395&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]2947.66666666667[/C][C]182.085560973822[/C][C]489[/C][/ROW]
[ROW][C]2[/C][C]2427.25[/C][C]128.738017977314[/C][C]423[/C][/ROW]
[ROW][C]3[/C][C]2296.33333333333[/C][C]121.808593019267[/C][C]468[/C][/ROW]
[ROW][C]4[/C][C]2934.5[/C][C]146.737551740886[/C][C]578[/C][/ROW]
[ROW][C]5[/C][C]2887.66666666667[/C][C]152.622727566038[/C][C]490[/C][/ROW]
[ROW][C]6[/C][C]2410.33333333333[/C][C]446.336264049943[/C][C]1734[/C][/ROW]
[ROW][C]7[/C][C]1041.66666666667[/C][C]256.152771650518[/C][C]624[/C][/ROW]
[ROW][C]8[/C][C]656.333333333333[/C][C]29.4937075980418[/C][C]87[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257395&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257395&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
12947.66666666667182.085560973822489
22427.25128.738017977314423
32296.33333333333121.808593019267468
42934.5146.737551740886578
52887.66666666667152.622727566038490
62410.33333333333446.3362640499431734
71041.66666666667256.152771650518624
8656.33333333333329.493707598041887







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha125.485246458177
beta0.0261390613382426
S.D.0.0565127896209947
T-STAT0.462533552378943
p-value0.659997461313196

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 125.485246458177 \tabularnewline
beta & 0.0261390613382426 \tabularnewline
S.D. & 0.0565127896209947 \tabularnewline
T-STAT & 0.462533552378943 \tabularnewline
p-value & 0.659997461313196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257395&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]125.485246458177[/C][/ROW]
[ROW][C]beta[/C][C]0.0261390613382426[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0565127896209947[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.462533552378943[/C][/ROW]
[ROW][C]p-value[/C][C]0.659997461313196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257395&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257395&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)
alpha125.485246458177
beta0.0261390613382426
S.D.0.0565127896209947
T-STAT0.462533552378943
p-value0.659997461313196







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.829924718262732
beta0.766945175219238
S.D.0.472641202837491
T-STAT1.62267946724682
p-value0.155784394826869
Lambda0.233054824780762

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.829924718262732 \tabularnewline
beta & 0.766945175219238 \tabularnewline
S.D. & 0.472641202837491 \tabularnewline
T-STAT & 1.62267946724682 \tabularnewline
p-value & 0.155784394826869 \tabularnewline
Lambda & 0.233054824780762 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=257395&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.829924718262732[/C][/ROW]
[ROW][C]beta[/C][C]0.766945175219238[/C][/ROW]
[ROW][C]S.D.[/C][C]0.472641202837491[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.62267946724682[/C][/ROW]
[ROW][C]p-value[/C][C]0.155784394826869[/C][/ROW]
[ROW][C]Lambda[/C][C]0.233054824780762[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=257395&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=257395&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-0.829924718262732
beta0.766945175219238
S.D.0.472641202837491
T-STAT1.62267946724682
p-value0.155784394826869
Lambda0.233054824780762



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')