I am in need of a little guidance on a stat problem...

I've performed a permutation on two data sets, in R, regarding sunblock efficacy, and have concluded that in any permutation, there is only one instance of matching efficacy, the original data set. now I have to find a 95% C.I. for the SPF... do I just use the t.test that I used in the original data t.statistic calculation for my CI?

many thanks!

> n1<-13

> n2<-13

> n<- n1+n2

> data <- ex0430$Control

> for (i in 1:n2) {

+ data[i+n2]<-ex0430$Sunscreen

+ }

> tt <- t.test(data[1:n1], data[(n1+1):n], var.equal=T)

> t_stat <- tt$statistic

>

>

> B <- 100000; statistics <- numeric(B)

> for (i in 1:B) {

+ idx <- sample(n, n1)

+ d1 <- data[idx]; d2 <- data[-idx]

+ mean1 <- mean(d1); mean2 <- mean(d2)

+ var1 <- var(d1); var2 <- var(d2)

+ sp <- sqrt(((n1-1)*var1+(n2-1)*var2)/(n-2))

+ se <- sp*sqrt(1/n1+1/n2)

+ statistics

+ }

> tt <- t.test(data[1:n1], data[(n1+1):n], var.equal=T)

> t_stat <- tt$statistic

>

>

> B <- 100000; statistics <- numeric(B)

> for (i in 1:B) {

+ idx <- sample(n, n1)

+ d1 <- data[idx]; d2 <- data[-idx]

+ mean1 <- mean(d1); mean2 <- mean(d2)

+ var1 <- var(d1); var2 <- var(d2)

+ sp <- sqrt(((n1-1)*var1+(n2-1)*var2)/(n-2))

+ se <- sp*sqrt(1/n1+1/n2)

+ statistics

*<- (mean1-mean2)/se*

+ }

> sum(t_stat <= statistics) / length(statistics)

[1] 1+ }

> sum(t_stat <= statistics) / length(statistics)

[1] 1