One more part

Fundamentals of Bayesian Data Analysis in R

Rasmus Bååth

Data Scientist

rbinom Bayesian model 2

n_samples <- 100000
n_ads_shown <- 100
proportion_clicks <- 0.1
n_visitors <- rbinom(n_samples, size = n_ads_shown, 
                     prob = proportion_clicks)

runif - Random Uniform samples

proportion_clicks <- runif(n = 6, min = 0.0, max = 1.0)

proportion_clicks

0.05  0.58  0.21  0.61  0.69  0.39

runif - Random Uniform samples

proportion_clicks <- runif(n = 6, min = 0.0, max = 1.0)
n_clicks <- rbinom(n = 6, size = 100, proportion_clicks)

proportion_clicks

0.05  0.58  0.21  0.61  0.69  0.39

runif - Random Uniform samples

proportion_clicks <- runif(n = 6, min = 0.0, max = 1.0)
n_clicks <- rbinom(n = 6, size = 100, proportion_clicks)

proportion_clicks

0.05  0.58  0.21  0.61  0.69  0.39

n_clicks

7     59    13    63    67    29

Try this in practice!

Fundamentals of Bayesian Data Analysis in R