par1<-as.numeric(par1) par2<-as.numeric(par2) par3<-as.numeric(par3) par4<-as.numeric(par4) par5<-as.numeric(par5) par6<-as.numeric(par6) c <- 'NA' csn <- abs(qnorm(par5)) if (par3 == par4) { conclusion <- 'Error: the null hypothesis and sample mean must not be equal.' } if (par3 > par4) { c <- par4 + csn * sqrt(par2) / sqrt(par1) } if (par3 < par4) { c <- par4 - csn * sqrt(par2) / sqrt(par1) } p <- pnorm((c - par6) / (sqrt(par2/par1))) print(p) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Testing Mean with known Variance',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'sample size',header=TRUE) a<-table.element(a,par1) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'population variance',header=TRUE) a<-table.element(a,par2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'sample mean',header=TRUE) a<-table.element(a,par3) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'null hypothesis about mean',header=TRUE) a<-table.element(a,par4) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'type I error',header=TRUE) a<-table.element(a,par5) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alternative hypothesis about mean',header=TRUE) a<-table.element(a,par6) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Type II Error',header=TRUE) a<-table.element(a,p) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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