The following Methods of Research Data Analysis MCQs have been compiled by our experts through research, in order to test your knowledge of the subject of Methods of Research Data Analysis. We encourage you to answer these 10+ multiple-choice questions to assess your proficiency.
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A. You are no longer finding “new” themes in your data
B. You are continuing to see recurring patterns
C. You have enough data to sufficiently answer your questions
D. All of these
A. You are no longer finding “new” themes in your data
B. You are continuing to see recurring patterns
C. You have enough data to sufficiently answer your questions
D. All of these
A. True
B. False
A. There is so much of it, it can be overwhelming
B. It comes from multiple sources
C. Creating a structure helps the data to make sense
D. All of the above
A. To establish the depth and breadth of the project
B. To know when it is time to “get out”
C. To get paid in a timely fashion
D. All of the above
A. When you are at a midpoint in the study
B. When you have an early data collection point
C. Before you begin your study as a theory
D. After your first memo of analysis
A. Be close to your work, which helps with analysis
B. Check for accuracy of what has happened because you were there
C. Recall the subtleties and nuances of the methodology
D. All of the above
A. Not bad if you can afford it
B. Adds another layer of interpretation of the data
C. Can be viewed as practical in certain circumstances
D. Good practice for beginner researchers.
A. Become conscious and aware of yourself as a researcher
B. Ask yourself questions regarding limits of your data
C. Ask yourself and reflect upon the data thus far and your influence on it
D. All of the above
A. True
B. False
A. True
B. False
A. Change codes all the time
B. Read, analyze, question, write and re-write passages to understand the data
C. Explain to others what you are doing and why
D. Check for validity in your study.
A. Read through your entire data set in a structured way
B. Read through your entire data set in an unstructured way
C. Code your data along the way
D. Discuss emergent themes with your colleagues.
A. An overarching theme or “meta-theme”
B. Ideas you had not considered
C. Typos that need to be fixed
D. Mistakes you made along the way.
A. Represent your data
B. Are organized, identify chunks of passages with a word or idea
C. Are color coordinated using highlighters
D. Are generated from the date
A. Further develop each broad category into subcategories
B. Merge a couple of the categories and elaborate on the others
C. Connect all of the codes to a broader set of understandings
D. Add more codes
A. “Some of those codes will be collapsed as you think this through”
B. “Some of those codes will be related to the theory you studied”
C. “Don’t worry about this because the codes will be refined as you go along with further analysis”
D. All of the above