Section outline

  • Course Overview

    This course introduces quantitative data analysis, linking it to the scientific method and research design. You'll learn key terms, recognize the purpose of quantitative analysis, and explore various techniques it also covers data preparation, statistical software, and storytelling with data, culminating in a hands-on analysis of real datasets to solidify your understanding.

    Learning Outcomes

    This course will help you to:

    1. Make the connection between the scientific method, research design, and quantitative data analysis 
    2. Choose statistical software to conduct quantitative data analysis   
    3. Explain relationships and predict changes between variables 
    4. Conduct descriptive and exploratory analysis   
    5. Interpret multiple linear regression results  
    6. Put together a presentation using quantitative data and analysis that tells a captivating story  

    • Course Instructor: Brian Fogarty

      • Brian Fogarty

        Brian Fogarty serves as an associate director for Lucy Family Institute, specifically overseeing the Center for Social Science Research. He is also concurrent associate professor of the practice in the Department of Political Science. At the CSSR, he works with social science researchers to support their project research design, data, and quantitative analysis needs. His current research focuses on the news media as a strategic actor in politics and understanding perceptions of voter and electoral fraud. Before joining Notre Dame, he was a lecturer in quantitative social science at the University of Glasgow’s Q-Step Centre. Prior to Glasgow, he was an associate professor of political science at the University of Missouri – St. Louis.  He received his Ph.D. in political science from the University of North Carolina – Chapel Hill.

        View Bio for Brian Fogarty

      • 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 Quantitative Data Analysis?

          This module will help you to:

          1. Make the connection between the scientific method, research design, and quantitative data analysis  
          2. Become familiar with key terms used in quantitative data analysis  
          3. Recognize the purpose of quantitative data analysis 

        • Module Two: Quantitative Data and Statistical Software

          This module will help you to:

          1. Identify and describe the different types of quantitative data 
          2. Find quantitative data for your own research  
          3. Choose statistical software to conduct quantitative data analysis 

        • Module Three: Quantitative Data Analysis Techniques

          This module will help you to:

          1. Describe quantitative data and variables  
          2. Explore relationships between variables    
          3. Explain relationships and predict changes between variables 

        • Module Four: Preparing Data for Quantitative Data Analysis

          This module will help you to:

          1. Examine the various aspects of a data set  
          2. Manipulate data to make it more manageable 
          3. Learn frequently used variable manipulation techniques  

        • Module Five: Quantitative Data Analysis in Action

          This module will help you to:

          1. Recognize the importance of viewing and manipulating variables before performing analysis  
          2. Conduct descriptive and exploratory analysis     
          3. Interpret multiple linear regression results  

        • Module Six: Storytelling With Quantitative Data and Analysis

          This module will help you to:

          1. Explain the substantive meaning of statistical results  
          2. Recognize the difference between statistical and substantive significance   
          3. Put together a presentation using quantitative data and analysis that tells a captivating story  

        • Glossary of Key Terms

          In addition to the glossary you’ll find woven throughout the course, you can find the full glossary collated in one place here.

        • 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.