Lab 1G: What’s the FREQ?

Lab 1G - What's the FREQ?

Directions: Follow along with the slides and answer the questions in bold 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.

How do we summarize categorical variables?

  • 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

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 = ____)

2-way Frequency Tables

  • 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 occurrence of physical challenges than the other? If so, which one and explain your reasoning?

Interpreting 2-way frequency tables

  • 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?

One final option

  • 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.

On your own

  • 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.