3.1 Learning goals

• Survey design, internal consistency, validity – you want your data to be high-quality
• Where/how to get quantitative data
• Descriptive statistics: mean, median, mode, SD, all of it graphically
• Structure of quantitative data: Unit of observation, variables (IV and DV)
• T-tests
• Correlation analyses
• Regressions
• Achieve basic competency in the R software for statistical analysis.

3.2 Before class

• Excel Activity

3.3 In class

3.4 After class

3.5 Notes

• Types of RQs: educational intervention pre-post, survey (patients, GCs, healthcare providers, patient-provider interactions); pre-post for t-test
• Removed learning goals: Chi-2, ANOVA
• How to deal with missing data

4.1 Learning goals

• Structure of qualitative data
• Grounded (development of) theory – methodology (when would you not use GT? to test a very specific hypothesis in a survey)
• How to interview effecitvely: interviewer effect, open-ended, saturation
• Types of qualitative methods: interview, focus group (rare), open-ended survey questions or narrative responses
• Basic qualitative analysis: coding, themes/codes lead to buckets.

4.2 Before class

4.3 In class

4.4 After class

• Practice interview

4.5 Notes

5.1 Learning goals

5.2 Before class

5.3 In class

5.4 After class

5.5 Notes

6.1 Learning goals

6.2 Before class

• Journal club-style seminar course in previous week will feature related article(s).

6.3 In class

6.4 After class

6.5 Notes

• Figure out what HE744 does for mixed methods
• A lot of projects and literature have some survey questions and a series of open-ended questions that students want to do some coding with. Sometimes just a combination of free text entry and open ended questions. Sometimes more abbreviated survey is used, with people opting in to, say, telephone interviews.