# PALS0046 candidate / Lab 03 - descriptive statistics
# Run from the folder containing data/.
pals <- read.csv("data/pals_synthetic.csv", stringsAsFactors = FALSE)
pals$condition <- factor(pals$condition,
                        levels = c("Control", "Training", "Mindfulness"))
mean(pals$rt_ms)
median(pals$rt_ms)
sd(pals$rt_ms)
IQR(pals$rt_ms)
sd(pals$rt_ms) / sqrt(nrow(pals))  # descriptive SE approximation
table(pals$condition)
aggregate(rt_ms ~ condition, data = pals, FUN = mean)
hist(pals$rt_ms, main = "Synthetic reaction times", xlab = "ms")
boxplot(rt_ms ~ condition, data = pals, ylab = "Reaction time (ms)")
outlier_copy <- pals
outlier_copy$rt_ms[1] <- 900
mean(outlier_copy$rt_ms)
median(outlier_copy$rt_ms)
# STUDENT TODO:
# Compare SD with SE; explain why units are milliseconds.
# Report three group means and describe what the artificial data cannot prove.