Section outline

  • Course Overview

    This course introduces you to powerful and flexible tools in the R programming language that are used on a daily basis by social scientists to investigate real-world data sets. You will learn how to explore and manipulate data, using RStudio to perform commonly accepted statistical techniques and present your findings both graphically and numerically. At the end of the course, you will use the skills you have learnt to complete a final data analysis project incorporating data management, data exploration, and data visualization of a multidimensional construct.

    This course contains frequent exercises and working examples which you are expected to use as an opportunity to understand and further explore the options available for you to apply these to your own work. It also provides you with additional resources to understand the given tools and techniques in more depth, and to discover others that are outside the scope of the course.

    Learning Outcomes

    This course will help you to:

    1. Understand how to treat data in R to apply common social science principles to your own papers and projects
    2. Produce a range of visualizations that illustrate complex relationships in your data
    3. Complete a full analysis of multiple data sets to produce publication quality tables and graphs that represent trends and interactions within the data

    • Course Instructor: Dr Andreea Moldovan

      • Dr Andreea Moldovan


        Dr Andreea Moldovan is a Data Scientist in the financial services sector. She was previously a Research Fellow at Exeter University. She has a background in sociology, social research methods, and survey methodology. Her main interests are latent variable modelling, longitudinal data analysis, and machine learning techniques that overcome assumptions of traditional regression methods. Andreea has run R demonstrations for teams based in a large charity and is very passionate about encouraging other social scientists to discover the wonderful world of R.

        View Bio for Dr Andreea Moldovan

      • Course Resources

        You will need to access certain files and resources throughout the course to get the most out of the activities. You can find them all here. 

      • Video Transcripts

        You can access all video transcripts here.

      • Pre-Course Self Assessment

        Before you dive into this course, spend a few moments reflecting on your familiarity with the topic and your current level of skills confidence. 

        You will then re-visit the same questions in our Post-Course Self Assessment and reflect on how the course has helped you develop in confidence and grow your skills.

        • Module One: What is R and Why Use It?

          This module will help you to:

          1. Install and launch R
          2. Install and launch RStudio
          3. Customize RStudio to suit your working preferences
          4. Identify the primary resources for R users

        • Module Two: The R Language Simplified

          This module will help you to:

          1. Use R, RStudio and user-contributed packages
          2. Understand essential R terminology and help functions
          3. Create and set up your own workspace and R environments

        • Module Three: Everyday Data Management

          This module will help you to:

          1. Understand basic data management techniques
          2. Prepare your own data for analysis
          3. Employ specific R packages

        • Module Four: Descriptive Statistics and Graphs

          This module will help you to:

          1. Produce descriptive statistics to describe data numerically
          2. Examine the internal structure of R objects
          3. Describe data graphically with a variety of graphs

        • Module Five: Summated Scales in R

          This module will help you to:

          1. Explore relationships between multiple variables
          2. Interpret real-world data sets
          3. Create summated scales
          4. Perform a reliability analysis

        • Module Six: Ordinary Least Squares Regression

          This module will help you to:

          1. Expand your statistical testing vocabulary in R
          2. Use R to carry out bivariate and multivariate regressions
          3. Fit interaction terms to your data
          4. Produce interaction visualizations

        • Final Project

          In the final project, you will need to complete data analysis exercises in sequence to reinforce the skills you have acquired throughout this course.

          IMPORTANT: If you already had R installed before taking this course, please make sure you are using version 3.5.0 or newer. If you have an older version, please update it before attempting this final project.

        • Big Data and R in brief

          In this module, you will learn how to continue developing your R skillset to be able to work on big data projects.

        • Post-Course Self Assessment

          Now you’ve completed the course, spend a few moments reflecting on where your familiarity with the topics and your confidence skills levels are at now. 

          Has the course helped you develop new skills and grow your confidence?

          You'll need to complete the Post-Course Self Assessment in order to download your certificate. If you didn't do the Pre-Course Self Assessment before starting the course, please go to the top of the page and reflect on your familiarity with the topic and your level of skills confidence before you started the course.

          • Completion: Certificate

            Completing all modules (plus the pre and post-course assessments) will unlock the course certificate, which you can then download here. Your course certificate will only be made available once you have completed all these sections.

            If you have difficulty accessing your certificate, please contact the Sage support team at: onlinesupport@sagepub.co.uk. You can also check out this FAQ page which may be helpful.

            • Give Feedback About This Course

              Did you enjoy the course? Please take two minutes to share your feedback. We use learner feedback in future course updates and developments to provide an excellent learning experience.

            • Accessibility

              We have high standards of accessibility on Sage Campus and as of May/June 2024 all activities within this course are keyboard and screen reader compatible. For more details on accessibility standards, please see the Sage Campus Accessibility Guide.

              For those using assistive technology, please note that within this course:

              • Tab components: JAWS and NVDA behave slightly differently. For NVDA to keep reading, it is best to exit focus mode and go back to browse mode. 
              • Matching: JAWS does not read out question label on dropdown focus.