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## Introduction to R for social researchers - Online

**Introduction/Overview**

One of the most popular software tools for data management and analysis is the open source package R, often used with the Rstudio interface. These are extremely powerful and are able to handle most types of data and analyses used in social research.

In this course you will learn the basics of R and Rstudio. We will cover the main types of objects in R and how to select cases and variables. We will also discuss how to import and export data and how to describe the data using tables and summary analyses. Through the practical exercises you will get accustomed to running functions in R and using the syntax.

**IMPORTANT:** participants will need to have a reasonable familiarity with quantitative data.

### Objectives

By the end of the workshop participants will:

- the basic types of objects and data in R
- how to create and change objects in R
- how to select cases and variables in a dataset
- the different types of variables used in social data
- how to use syntax in R
- how to import and export data in R
- how to describe data in R

### Topics

During the course we will cover:

- types of objects in R
- types of variables
- importing and exporting data
- selection of cases and variables
- data description via tables and other basic analyses

### Who will benefit?

People with a basic understanding of quantitative data, who:

- Want to learn the basics of R and Rstudio
- Want to use data in R and Rstudio
- Want to extend their understanding of quantitative data and analysis

### Learning outcomes

- To about the main types of data and variables
- To learn how to use R and Rstudio
- To learn how to select cases and variables
- To learn how to describe data with R

### Course Tutor

**Alexandru Cernat** is a senior lecturer in social statistics at the University of Manchester. He received a PhD in survey methodology from the University of Essex and was a post-doc at the National Centre for Research Methods.

His expertise covers: latent variable modelling, non-response, new forms of data, longitudinal data design, longitudinal analysis.

He has taught from multiple organizations such as the National Centre for Research Methods, European Survey Research Association, International Program in Data Science and the African Institute of Mathematical Science.

You can find more about his research at www.alexcernat.com

This course contributes 6 hours to the MRS CPD programme

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