En del till

Grunderna i bayesiansk dataanalys i R

Rasmus Bååth

Data Scientist

rbinom Bayesmodell 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 – slumpmässiga uniforma sampel

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 – slumpmässiga uniforma sampel

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 – slumpmässiga uniforma sampel

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

Nu kör vi en övning!

Grunderna i bayesiansk dataanalys i R