Alexander De Raeymaeker - Opdracht 8.2.3

*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, 09 May 2011 21:46:33 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/09/t1304977691wf4i3b2hd1t8943.htm/, Retrieved Mon, 09 May 2011 23:48:11 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W83

Dataseries X:

» Textbox « » Textfile « » CSV «

2435 1379 1511 2021 1614 1680 1630 870 1877 2428 1711 127 3192 1934 2075 1700 1198 1582 1705 911 1817 1168 920 84 2254 1485 1886 1358 1167 1781 1218 779 1418 1641 1196 132 2926 1777 2094 1648 1646 1537 1917 977 1475 2124 1209 135 2917 1981 1398 1171 903 1390 1280 781 1828 1631 1063 186 2275 1342 1070 950 1121 1305 1586 548 1225 1419 880 124 2044 1143 897 1264 1326 1529 1373 587 1137 1426 1016 176 2614

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 2 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 1836.5 485.626399611883 1056 2 1448.5 386.689798158679 810 3 1535.75 987.901943514638 2301 4 2225.25 662.795783028227 1492 5 1349 363.166628422822 794 6 997.25 716.737690279133 1733 7 1745.75 406.746747579703 896 8 1236.25 412.697932310465 1002 9 1096.75 668.331940979431 1509 10 2111.25 574.583544839217 1278 11 1519.25 395.230207178888 940 12 1235.75 828.370840867784 1989 13 1866.75 778.860866907563 1746 14 1088.5 292.427198917383 609 15 1177 735.978713460292 1642 16 1409.25 600.012985970582 1325 17 1140 438.545322629258 1038 18 912 570.668029593388 1295 19 1337 495.450636626227 1147 20 1203.75 420.221667694563 942 21 938.75 536.802493163609 1250 Regression: S.E.(k) = alpha + beta * Mean(k) alpha 484.471324873897 beta 0.0538570583174877 S.D. 0.109617118661329 T-STAT 0.491319777195416 p-value 0.628827700403929 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha 5.40369851258795 beta 0.121551285801388 S.D. 0.282297001155001 T-STAT 0.430579444004251 p-value 0.671619035008393 Lambda 0.878448714198612

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/09/t1304977691wf4i3b2hd1t8943/1oppm1304977589.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304977691wf4i3b2hd1t8943/1oppm1304977589.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304977691wf4i3b2hd1t8943/2ltpt1304977589.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t1304977691wf4i3b2hd1t8943/2ltpt1304977589.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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