# Item 1
getr2 <- function(obj, adjusted = FALSE) {
	sumobj <- summary(obj)
	if(adjusted) {
		sumobj[["r.squared"]]
	} else {
		sumobj[["adj.r.squared"]]
	}
}


# Item 2
gendata <- function(n, m, stdev, distype = 1) {
  result <- NULL
  if(distype == 1) {
    result <- rnorm(n, 0, 1)
  } else if (distype == 2) {
    result <- rt(n, 4)
  } else if (distype == 3) {
    result <- rf(n, 1, 15)
  } else if (distype == 4) {
    result <- 1 - rf(n, 1, 15)
  } else {
    stop("The distype argument is not valid.")
  }
  result <- (result - mean(result)) / sd(result)

  temp <- rnorm(n, m, stdev)
  result <- sd(temp) * result + mean(temp)
  return(result)
}

nonnormalsim <- function(cond, nrep, alpha = 0.05) {
	result <- rep(NA, nrep)
	for(i in 1:nrep) {
		x <- gendata(cond[1], 0, 1, cond[2])
		y <- gendata(cond[1], 0, 1, cond[3])
		out <- cor.test(x, y)
		result[i] <- out[["p.value"]] < alpha
	}
	result
}

ns <- c(50, 150, 250)
xdists <- 1:4
ydists <- 1:4
conds <- expand.grid(ns, xdists, ydists)
superresult <- apply(conds, 1, nonnormalsim, nrep = 1000, alpha = 0.05)
cbind(conds, apply(superresult, 2, mean))