### Sim to show distribution of P-values with different parameters # Set known parameters g_means <- c(0, 0) g_sds <- c(1, 1.6) g_samples <- c(40, 20) g_labels <- factor(rep(c("G1","G2"), times = g_samples)) # Set the number of runs runs <- 1000 # Pre-allocate loop output p_vals <- numeric(runs) for (run in 1:runs){ # Generate simulated sample from normal distribution g1_data <- rnorm(n = g_samples[1], g_means[1], g_sds[1]) g2_data <- rnorm(n = g_samples[2], g_means[2], g_sds[2]) # Put into data frame sim_df <- data.frame(measure = c(g1_data, g2_data), group = g_labels) # Run t-test on data stat_output <- t.test(measure ~ group, data = sim_df) p_vals[run] <- stat_output$p.value } hist(p_vals, breaks = 20) mean(p_vals <= 0.05)