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Data:
61.712 62.084 61.406 60.724 58.904 58.722 59.704 60.674 59.813 60.568 61.401 61.427 61.080 61.999 63.888 66.284 67.309 66.685 65.404 65.045 63.867 64.156 62.224 63.193 64.256 66.153 68.072 68.245 68.741 67.795 67.315 67.245 66.448 69.112 71.787 74.366 76.337 77.618 77.090 76.925 78.384 80.462 82.765 85.033 83.608 81.813 81.467 80.708 80.631 79.133 77.396 75.491 74.267 72.882 71.286 70.737 67.425 67.530 67.157 67.215 66.268 66.053 54.905 54.459 51.159 44.725 40.184 44.094 46.904 47.141 45.052 42.758 41.388 41.154 40.019 39.928 38.598 36.584 32.566 30.140 27.713 25.380 23.823 21.376 18.696 16.304 14.203 11.807 7.551 4.215 3.346 3.010 2.849 2.485 1.744 1.221 803 553 314 204 125 55 53 27 10 6
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R Code
library(MASS) par1 <- as.numeric(par1) if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2) x <- as.ts(x) #otherwise the fitdistr function does not work properly r <- fitdistr(x,'normal') r bitmap(file='test1.png') myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F) curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$estimate[1]) a<-table.element(a,r$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'standard deviation',header=TRUE) a<-table.element(a,r$estimate[2]) a<-table.element(a,r$sd[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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