# Applied Regression with R for Social Science Researchers [1]

## Event date/time:

R is a free, open source programming language that gives empirical researchers a powerful set of tools for regression analysis. Workshop participants will learn how to import and export data, perform exploratory data analysis, run multiple regressions, conduct hypothesis testing, and estimate fixed and random effects models in the R environment.

This class is geared toward social science researchers who work with regression models to analyze data in their particular field. This workshop is appropriate for researchers who have some experience with R, but are seeking additional help with multiple regression. Participants will learn how to import and export data, perform exploratory data analysis, run multiple regressions, conduct hypothesis testing, and estimate fixed and random effects models in the R environment. R is a free, open-source programming language that gives empirical researchers a powerful set of tools for regression analysis.

The first day will focus on getting you comfortable working in the R environment and running a regression model. We will cover estimating multiple regression models, and the tools needed to run them. This includes importing and plotting data, specifying a model, checking model assumptions, reading output, and hypothesis testing. The second day will focus on multiple regression extensions, including estimating fixed and random effects models with panel data, and interpreting output from these models. Participants are encouraged to bring their own data on the second day.

*Workshop runs May 19 and 20, 9 a.m. to 3 p.m. Lunch will be provided.*

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**Register here [2].**

Instructor: Christopher Burns

Software note: The instructor will be using the R-Studio environment for this course. R and R Studio are free for any user to download through the Internet. You can download R (must be downloaded before installing R-studio) at http://cran.r-project.org/ [3], and R-Studio at http://www.rstudio.com/ide/download/ [4].