#### Suggested Content for Raw Data and Prospective Analysis Section

1. What will your data look like? First, who, what, how many? Then, how could it be characterized in terms of cases x variables at the most abstract/simple level (e.g., "I interviewed 16 adoptees about their hobbies, educational plans, and favorite colors.").
2. State your research question in terms of concepts (see this slide show on "conceptualization" for a reminder).
1. If it makes sense, distinguish “dependent” from “independent” concepts, causes from effects, structures from behaviors from attitudes? Even if you are not doing a classic research design, talk about the mechanism of causes and effects that your data is "about."
2. If you are looking at narratives and processes talk about them conceptually
3. From concepts into variables (i.e., a thing that can take on different values)
1. What are the variables associated with your concepts?
2. How will you operationalize your concepts? How will you get from ideas to your actual fieldwork/data collection to a data matrix?
4. B. What values can they take on?
5. C. Measurable with single “question,” “item,” or “observation” or need a scale/index?
6. 3. What variables do you expect you will use to define your population and sample? What variations in your independent variables do you want to be sure to have included in your study?
7. A. What is going to be the best way to make sure you get this kind of variation? In other words, what are the pros and cons of different sampling strategies for your project?
8. 4. What univariate frequencies do you expect to find? Try expressing these in terms of percentiles, means and modes and medians, dispersion, skewness, etc.
9. A. Draw the pictures. Explain what they mean. Why are they shaped as they are?
10. 5. What bivariate relationships are potentially of interest given your research questions?
11. A. Sketch tables and scatterplots.
12. B. Describe the quadrants.
13. C. Show us how these illustrate the comparisons you are interested in.
14. 6. Sketch the overall correlation matrix and fill it in with your expectations (e.g., +, -, or 0) of how you think your different variables are related.
15. 7. How has this exercise caused you to change how you are thinking about your project?