# Function for testing

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## Function for testing

 Hi all, I want to create a sample called x, with length 10 from a N(0,1) distribution. Next to that I want to create a sample called y, with length 10 from a N(0.5 ,1) distribution. Both samples are undergoing a t.test. The outcome must be that I can see how many times for x H0 was rejected. The same for y. I am testing under a confidence level of 0.05 Down below is the function I must use: pv=function(n=10,N=100,m=1,...){ resx=numeric(N) resy=numeric(N) for (i in 1:N){ x=rnorm(n) y=rnorm(n,m) resx[i]=t.test(x,...)[[3]] resy[i]=t.test(y,...)[[3]] } z=list(resx,resy) names(z)=c("px","py") z} So I compute pv(10,100,0.5) which gives me p-values in px and py. But somewhere I must give a statement (I think at the ... but that gives me errors) that px<0.05 so I can see how many times H0 was rejected. Thus, the values that are computed must be compared with the statement <0.05.