R For Social Statistics

 R for Social Statistics

Monday, November 7, 2016

HM Tory Building TB-39 (Computer Lab)

University of Alberta

9:00 am – 4:00 pm

Instructor: Dr. Michelle Maroto, Department of Sociology


Cost:    $125 Off campus (Non-U of A)

            $100 University of Alberta Faculty/Staff

            $40   Student

Workshop includes lunch and refreshments.


About the Workshop

This one-day workshop will provide a friendly introduction to the statistical data analysis program, R. We will cover the basic structure and functions of R; data entry and management in R; and ways to describe, visualize, and analyze data in R. Please note that the course is intended for persons with some statistical background. Registrants should have a working knowledge of hypothesis testing, correlation, and regression, as these topics will be included in the workshop. 


R (cran.r-project.org) is a free computing language and software environment that provides access to a variety of statistical and graphic techniques. Due to its open source structure and flexibility, R has been growing in popularity since its official release in 2000, making it one of the most widely used statistical software programs both inside and outside academia. Although many software programs and coding languages for data analysis exist, R is one of the few software environments directly oriented towards statistical analyses, which is continually expanding through the implementation of user-created packages. In addition, a large active community of programmers, statisticians, and researchers continue to strengthen the program and the resources available.

About the Instructor

Dr. Michelle Maroto is an Assistant Professor of Sociology at the University of Alberta whose research interests include stratification, wealth inequality, social policy, and quantitative methodology. Michelle regularly uses R as the primary software for her research and she teaches students to use the program in both her introductory and more advanced statistics and data analysis courses.















Part I: R Basics

R overview

   R and RStudio

   Packages and libraries

   An overgrown calculator

R language and programming

   Variables and vectors

   The graphics system

   Matrices and Arrays



   Data frames

Data entry and management

   Working with data

   Selecting and subsetting

   Cleaning data

   Missing data

   Recoding variables

Part II: Describing data in R

Frequency distributions and bivariate tables

Measures of central tendency

  Mean, median, and mode

Measures of dispersion

  Range, interquartile range, variance, and standard deviation

R graphics

Basic plots
  Pie charts, bar charts, histograms, scatterplots

More advanced plotting options

Part III: Inferential statistics in R

Hypothesis testing

Single and two sample means

Single and two sample proportions


Chi square



Linear regression basics

Regression diagnostics

Introduction to and discussion of more advanced methods


Registration deadline: October 31, 2016

Registrants canceling their registration on or before November 3, 2016 will receive a refund of the registration fee, less a $20 administrative fee.


If you have any questions, please email the instructor at maroto@ualberta.ca