Coin flips with prop_model

The function prop_model has been loaded into your workspace. It implements a Bayesian model that assumes that:

The data is a vector of successes and failures represented by 1s and 0s.
There is an unknown underlying proportion of success.
Prior to being updated with data any underlying proportion of success is equally likely.

Assume you just flipped a coin four times and the result was heads, tails, tails, heads. If you code heads as a success and tails as a failure then the following R codes runs prop_model with this data

data <- c(1, 0, 0, 1)
prop_model(data)

The output of prop_model is a plot showing what the model learns about the underlying proportion of success from each data point in the order you entered them. At n=0 there is no data, and all the model knows is that it's equally probable that the proportion of success is anything from 0% to 100%. At n=4 all data has been added, and the model knows a little bit more.

Take prop_model for a spin by entering the R-code above into the script window to the right.

Take Hint (-15 XP)

Exercise

Coin flips with prop_model

Instructions 1/2