What’s the FREQ?

Lab 1G

Directions: Follow along with the slides and answer the questions in red font in your journal.

Clean it up!

In Lab 1F, we saw how we could clean data to make it easier to use and analyze.
- Using the data you cleaned, we can start analyzing a small set of variables from the American Time Use (ATU) survey.
- The process of cleaning and then analyzing data is very common in Data Science.
In this lab, we’ll learn how we can create frequency tables to detect relationships between categorical variables.
- Use the data() function to load the atu_clean data file to use in this lab.

When we’re dealing with categorical variables, we can’t just calculate an average to describe a typical value.
- (Honestly, what’s the average of categories orange, apple and banana, for instance?)
When trying to describe categorical variables with numbers, we calculate frequency tables

When it comes to categories, about all you can do is count or tally how often each category comes up in the data.
Fill in the blanks below to answer the following: How many more females than males are there in our ATU data??

tally(~ ____, data = ____)

Counting the categories of a single variable is nice, but often times we want to make comparisons.
Use a line of code, that’s similar to how we facet plots, to tally the number of people with physical challenges and their genders.
- Does one gender seem to have a higher occurence of physical challenges than the other? If so, which one and explain your reasoning?

Recall that there were 1153 more women than men in our data set.
- If there are more women, then we might expect women to have more physical challenges (compared to men).
Instead of using counts we use percentages.
Include: format = "percent" as option to the code you used to make your 2-way frequency table. Then answer this question again:
- Does one gender seem to have a higher occurence of physical challenges than the other? If so, which one and explain your reasoning?
- Did your answer change from before? Why?

It’s often helpful to display totals in our 2-way frequency tables.
- To include them, include margins = TRUE as an option in the tally function.

Describe what happens if you create a 2-way frequency table with a numerical variable and a categorical variable.
How are the types of statistical questions that 2-way frequency tables can answer different than 1-way frequency tables?
Which gender has a higher rate of part time employment?
Does one gender socialize more than the other? To answer this question first:
- Create a subset of the ATU data that includes only people who socialized more than 0 minutes.
- Create a histogram and include type = "percent" as an option in the function.