Why do you use dummy variables

Now imagine you have or categories Of course, if you will have 10 categories your table will explode with OneHotEncoding method and you will need to do some grouping with it or use some tree methods at last without doing OneHotEncoding. Sign up to join this community.

The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Learn more. Why do we create dummy variables? Asked 3 years, 5 months ago. Active 2 years, 3 months ago. Viewed 4k times.

Improve this question. Nick Cox Antoine Charlet Antoine Charlet 11 1 1 silver badge 2 2 bronze badges. Add a comment. Active Oldest Votes. Improve this answer. CrazyElf CrazyElf 99 2 2 bronze badges. Featured on Meta. Now live: A fully responsive profile.

It does make sense to create a variable called "Republican" and interpret it as meaning that someone assigned a 1 on this varible is Republican and someone with an 0 is not. Nominal variables with multiple levels If you have a nominal variable that has more than two levels, you need to create multiple dummy variables to "take the place of" the original nominal variable.

For example, imagine that you wanted to predict depression from year in school: freshman, sophomore, junior, or senior. Obviously, "year in school" has more than two levels. What you need to do is to recode "year in school" into a set of dummy variables, each of which has two levels. The first step in this process is to decide the number of dummy variables. This is easy; it's simply k-1, where k is the number of levels of the original variable.

You could also create dummy variables for all levels in the original variable, and simply drop one from each analysis. In order to create these variables, we are going to take 3 of the levels of "year of school", and create a variable corresponding to each level, which will have the value of yes or no i. Using Displayr. Working faster with large data files 12 Nov by Andrew Kelly.

Boost your analysis with in-built Calculations 20 Aug by Andrew Kelly. Find the stories in your data! Displayr is a data science, visualization and reporting tool for everyone. Prepare to watch, play, learn, make, and discover! Get access to all the premium content on Displayr First name.

Last name. Work email. Phone number. Last question, we promise! What type of survey data have you got?