Exercise

# Summarizing gender discrimination

As the first step of any analysis, you should look at and summarize the data. Categorical variables are often summarized using proportions, and it is always important to understand the denominator of the proportion.

Do you want the proportion of women who were promoted or the proportion of promoted individuals who were women? Here, you want the first of these, so in your R code it's necessary to `group_by()`

the `sex`

variable.

The discrimination study data are available in your workspace as `disc`

.

Instructions

**100 XP**

- Using the
`count()`

function from`dplyr`

, tabulate the variables`sex`

and`promote`

. - Summarize the data by using
`group_by()`

on the`sex`

variable. - Find the proportion who were promoted. Call this variable
`promoted_prop`

. Note that with binary variables, the proportion of either value can be found using the`mean()`

function (e.g.`mean(variable == "value")`

).