Analyze Qualitative Data

Section outline

• Course Overview

  Course Overview

  This course will develop your skills in understanding and evaluating your data. It identifies the appropriate approach to coding and uses techniques to categorize and pull themes from your data, building confidence and proficiency in every stage of the data analysis process.

  Learning Outcomes

  This course will help you to:

  1. Identify the types of data that generate themes and recognize why themes matter
  2. Effectively organize your data and decide on the best approach to transcribing it
  3. Evaluate the different approaches to coding and evaluate which is most suitable for analyzing your own data
  4. Identify meaningful data to create appropriate codes, organizing them into categories to help with data analysis
  5. Analyze your categories to find themes, evaluating these against the data
  6. Use evidence from your data to support your themes

  
  
• Course Instructor: Dr. Robert Thomas

  Course Instructor: Dr. Robert Thomas

  • Dr. Robert Thomas

    Dr. Thomas is currently a Lecturer (Marketing) at Aston Business School. Dr. Thomas’s primary research interests and publications encompass Brand Management, specifically the areas associated with sponsorship, fandom, co-creation, and brand community. His work has been published in the European Journal of Marketing, Computers in Human Behavior, Journal of Marketing Management, Journal of Product and Brand Management, Young Consumers, Strategic Change: Briefings in Entrepreneurial Finance, and IEEE Transactions on Engineering Management. Dr. Thomas sits on the editorial boards for Journal of Product and Brand Management, and International Journal of Sport Management and Marketing, winning reviewer of the year for Journal of Product and Brand Management in 2015.

    View Bio for Dr. Robert Thomas
• Course Resources

  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

  Video Transcripts

  You can access all video transcripts here.
• Pre-Course Self Assessment

  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: When and Why Do We Need Themes?

  Module One: When and Why Do We Need Themes?

  

  This module will help you to:

  1. Recognize why themes matter in qualitative research
  2. Identify the types of data that generate themes
• Module Two: Organizing and Transcribing Your Data

  Module Two: Organizing and Transcribing Your Data

  

  This module will help you to:

  1. Effectively organize your data to be ready for transcription
  2. Decide on the best approach to transcribe your data
  3. Take the necessary steps to create powerful transcriptions
• Module Three: The Basics of Developing Codes

  Module Three: The Basics of Developing Codes

  

  This module will help you to:

  1. Identify the different approaches to coding
  2. Evaluate which approach is most suitable for analyzing your own data
• Module Four: How Do I Develop Codes?

  Module Four: How Do I Develop Codes?

  

  This module will help you to:

  1. Identify meaningful data to create appropriate codes
  2. Use techniques to develop codes
• Module Five: How Do I Categorize Codes?

  Module Five: How Do I Categorize Codes?

  

  This module will help you to:

  1. Organize codes into categories
  2. Develop categories for data analysis
• Module Six: Finding Meaningful Themes

  Module Six: Finding Meaningful Themes

  

  This module will help you to:

  1. Analyze your categories to find themes
  2. Evaluate themes against your data
  3. Use evidence from your data to support your themes
• References and Glossary of Key Terms

  References and 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

  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

  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

  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

  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.