TIJDREEKS B - STAP 21

*Unverified author*

R Software Module: /rwasp_smp.wasp (opens new window with default values)

Title produced by software: Standard Deviation-Mean Plot

Date of computation: Mon, 16 Aug 2010 19:26:41 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Aug/16/t1281986828b35sesf5coecd2i.htm/, Retrieved Mon, 16 Aug 2010 21:27:10 +0200

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Aug/16/t1281986828b35sesf5coecd2i.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

De Cock Nicola

Dataseries X:

» Textbox « » Textfile « » CSV «

76 75 74 72 70 69 70 72 73 73 74 76 74 67 66 58 55 58 64 68 66 76 75 88 85 83 77 66 65 65 63 62 57 68 69 79 74 76 82 75 75 76 78 77 67 74 68 87 76 88 95 96 96 105 108 113 101 107 102 116 105 121 134 140 131 141 131 128 123 129 125 144 135 141 156 159 146 154 145 133 126 127 122 148

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 74.25 1.70782512765993 4 2 70.25 1.25830573921179 3 3 74 1.41421356237310 3 4 66.25 6.55108133567785 16 5 61.25 5.85234995535981 13 6 76.25 9.03234926989282 22 7 77.75 8.53912563829967 19 8 63.75 1.5 3 9 68.25 8.9953691790091 22 10 76.75 3.59397644214130 8 11 76.5 1.29099444873581 3 12 74 9.20144916122817 20 13 88.75 9.21502396451939 20 14 105.5 7.14142842854285 17 15 106.5 6.85565460040104 15 16 125 15.5134350376268 35 17 132.75 5.67890834580027 13 18 130.25 9.5 21 19 147.75 11.5866302262565 24 20 144.5 8.66025403784439 21 21 130.75 11.7011395456454 26 Regression: S.E.(k) = alpha + beta * Mean(k) alpha -0.539564582660916 beta 0.0792087114571817 S.D. 0.0251011101843182 T-STAT 3.15558598307206 p-value 0.00520709122659696 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha -5.01467905710545 beta 1.48927621968915 S.D. 0.530924073905568 T-STAT 2.80506440164556 p-value 0.0112983039664927 Lambda -0.489276219689146

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/16/t1281986828b35sesf5coecd2i/1qsyq1281986800.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/16/t1281986828b35sesf5coecd2i/1qsyq1281986800.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/16/t1281986828b35sesf5coecd2i/2qsyq1281986800.png (open in new window) http://www.freestatistics.org/blog/date/2010/Aug/16/t1281986828b35sesf5coecd2i/2qsyq1281986800.ps (open in new window)

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

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')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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