Foundations of Probability in R
David Robinson
Chief Data Scientist, DataCamp
flips <- rbinom(100000, 10, .5)
flips <- rbinom(100000, 1000, .5)
$$X \sim \text{Normal}(\mu,\sigma)$$
$$\sigma = \sqrt{\text{Var}(X)}$$
binomial <- rbinom(100000, 1000, .5)
$$\mu = \text{size} \cdot p$$ $$\sigma = \sqrt{\text{size} \cdot p \cdot (1 - p)}$$
expected_value <- 1000 * .5
variance <- 1000 * .5 * (1 - .5)
stdev <- sqrt(variance)
normal <- rnorm(100000, expected_value, stdev)
compare_histograms(binomial, normal)
Foundations of Probability in R