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...3.4 .... 12 M 10 2.1 To do the correct test of hypothesis using anova, I need to calculate the tank means and use those in the anova. I have tried using tapply() and by() functions, but when I do so I "loose" the treatment level because it is categorical. I have used Meandat<tapply(Size,list(Tank, Trt), mean) But that doesn't give me a dataframe that I can then use to do the actual aov analysis. So what is the most efficient way to accomplish the analysis Thanks Tom Miller

...rm")tests<-c("t","Wilcoxon")samplesizes<-c(10,30,40)reject1<-numeric(k)for(distribution in distributions){for(test in tests){for(samplesize in samplesizes){for(i in 1:k){if(distribution=="Normal"){#randomly generate data from normal distribution with true meandat<-rnorm(n=samplesize,mean=mu.true,sd=sigma.true)}else{#randomly generate data from a uniform distributiondat<-runif(samplesize,min=x1,max=y1)}if(test=="t"){#perform a t-test on sampleres<-t.test(dat,alternative="two.sided",mu=H0)#record if p-value is less than alpharejec...

...rm")tests<-c("t","Wilcoxon")samplesizes<-c(10,30,40)reject1<-numeric(k)for(distribution in distributions){for(test in tests){for(samplesize in samplesizes){for(i in 1:k){if(distribution=="Normal"){#randomly generate data from normal distribution with true meandat<-rnorm(n=samplesize,mean=mu.true,sd=sigma.true)}else{#randomly generate data from a uniform distributiondat<-runif(samplesize,min=x1,max=y1)}if(test=="t"){#perform a t-test on sampleres<-t.test(dat,alternative="two.sided",mu=H0)#record if p-value is less than alpharejec...