Using p-values to test a hypothesis
# https://lakens.github.io/statistical_inferences/01-pvalue.html # red line is alpha of 5% (100000 x 0.05=5000) nsims <- 100000 # number of simulations m <- 106 # mean sample n <- 26 # set sample size sd <- 15 # SD of the simulated data p <- numeric(nsims) # set up empty vector bars <- 20 for (i in 1:nsims) { # for each simulated experiment x <- rnorm(n = n, mean = m, sd = sd) z <- t.test(x, mu = 100) # perform the t-test p[i] <- z$p.value # get the p-value } power <- round((sum(p < 0.05) / nsims), 2) # power # Plot figure hist(p, breaks = bars, xlab = "P-values", ylab = "number of p-values\n", axes = FALSE, main = paste("P-value Distribution with", round(power * 100, digits = 1), "% Power"), col = "grey", xlim = c(0, 1), ylim = c(0, nsims)) axis(side = 1, at = seq(0, 1, 0.1), labels = seq(0, ...