Summarizing Categorical Data using Tables

Summarizing Categorical Data using Tables
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  • 0:06 Categorical Data
  • 0:55 Prepping Your Data
  • 1:51 Data Table
  • 2:39 Using Percentages
  • 4:30 Lesson Summary
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Lesson Transcript
Instructor: Yuanxin (Amy) Yang Alcocer

Amy has a master's degree in secondary education and has taught math at a public charter high school.

Watch this video lesson to find out why data tables are an excellent way to summarize your categorical data. Learn what you need to do to your data before constructing a table and the two ways you can show your data.

Categorical Data

Categorical data is data that can be categorized or grouped. You see examples of categorical data all the time whenever you fill out applications for anything. When it asks you for your gender and occupation, it is asking for categorical data.

Once you answer those questions, whoever reads the application can place you into a group based on your gender or occupation. You can be grouped into the student group, or the groups can incorporate both sets of data, and you can be grouped into the female student group if you're a girl or the male student group if you're a boy.

While the answers to a piece of categorical data may not be numerical in nature, once a survey is done, the various groups can be counted to see how many are in each group. It is this information that we will focus on.

Prepping Your Data

Let's see how we go about summarizing our categorical data with a little scenario. Imagine that we have just surveyed a random group of people about their favorite junk food. Each person we survey chooses his or her favorite junk food from a list of five choices. Our choices are: potato chips, pizza, hamburgers, hot dogs, and fries. After our survey is done, we have a stack of papers of everyone's choices.

To prep our data so we can summarize it, we now need to count how many are in each group. We go through our stack of responses, and we separate them into various groups based on their answers. We then count the number of papers in each group. We found that 15 people chose potato chips, 23 people chose pizza, 18 people chose hamburgers, 8 people chose hot dogs, and 10 people chose fries.

Data Table

We can take our group counts and input them directly into a table. Our table will have two columns: one for the type of junk food and the other for the result. Our top row will be our title row with 'Junk Food' and 'Result' as our titles for each respective column.

Junk Food Result
Potato chips 15
Pizza 23
Hamburgers 18
Hot dogs 8
Fries 10

We can reorder our data table so that the most popular is listed first and the least popular is listed last.

Junk Food Result
Pizza 23
Hamburgers 18
Potato chips 15
Fries 10
Hot dogs 8

This is one way we can use a data table to summarize our information. We can clearly see which junk food is the most popular out of our survey group and which is the least favorite. This does give us good information, but if we wanted to generalize our information to the general public, we would need to report our results in percentage form.

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