I am writing a case study about a specific phenomenon to answer how and why questions. I use interviews and observations as the main source of data collection.
However, before the project starts and ends, there will be an employee survey (3 groups of question with 5 questions in each group: corporate, team, and individual level)
Conditions: The case study is mainly qualitative. The quantitative survey is used to get a first big picture about employees opinion, hoping that results will improve after the project.
We use a likert scale ranging from strongly agree to strongly disagree. The survey is online, so we do not know if the person is female or male, age, etc.
Does anyone know how to use these kind of quantitative data in a case study?
Is it regression or just basic statistics and means?
Does it make sense to come up with hypothesis and to check them after the end of the project?
Again, the quantitative data is just a supplement in my case. But on the other hand, it gives us an introduction to the case, employees opinion about the overall situation and areas of focus and emphasis to improve. In addition, in my qualitative interviews, I challenge with 1 or 2 question with the results of the quantitative survey and how managers are going to improve the situation.
I used basic statistics and means. I used this method as I did not collect as much quantitative data as I would have liked, so I thought that basic descriptive statistics was the best representation of my own data given lower numbers of participants. I presented most of this data using frequency tables. Like you, I also used the quantitative survey to provide an introduction to the case and areas of focus, in a similar way to what you have suggested above. It became my first data set and provided an overview to the case.
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