1. Data Analysis
RWJF || GRC

2. Available Software
Quantitative
R
SPSS
STATA
Qualitative
NVivo
Atlas.ti

3. The Big Problem
How do you ask a question that a computer can answer?

4. Asking the right question
Are you looking for descriptive statistics?
Are you looking for confirmation/refutation of a hypothesis?

5. Asking the right question
Descriptive statistics are perhaps the
easiest to structure.
Quantitative: Central tendency,
quartiles, data range
Qualitative: Frequent words,
reoccurring themes

6. Asking the right question
Hypothesis testing requires
additional steps
Formulate hypothesis prior
to test, have a clear null and
alternative established

7. Asking the right question
H0: There is no difference/
relationship
Ha: There is a difference/
relationship

8. Asking the right question
Quantitative
Regression
Is there a relationship between variable X and Y?

9. Asking the right question
Quantitative
Difference
Is there a difference between variable X and Y?

10. Asking the right question
Many problems with any kind of data analysis software stem from
impossible to answer questions.

11. Simplify Questions
Break your question down to individual steps, as small as you can
go.

12. Simplify Questions
“I need to test the GPA of students who scored below a 26 on the
ACT vs. those who scored above.”

13. Simplify Questions
To answer this question, you need a software function that can
order the data, split it, and test the variables you need.
It can be hard to find one program that does all that - but it can be
easier if you break the problem up into its components.

14. Simplify Questions
“I need to test the GPA of students
who scored below a 26 on the ACT
vs. those who scored above.”
• Break the question down into individual steps:
1. Sort the data by lowest to highest ACT
2. Divide into ACT scores below 26 and
scores above
3. Run a two-sample T-test on the GPA’s from
each group.

15. Simplify Questions
Data analysis is a lot easier when each step is made smaller.

16. Choosing your Software
Quantitative
R
Pros: Most flexibility, free, customized software
Cons: Very difficult to learn

17. Choosing your Software
Quantitative
SPSS
Pros: User friendly, frequently used, allows for infinite
cases, has drop-down commands.
Cons: Expensive, can be difficult to interpret results.

18. Choosing your Software
Quantitative
STATA
Pros: Allows for syntax-based do-files that create
consistent change tracking
Cons: Expensive, can be difficult use

19. Choosing your Software
Quantitative
Excel
Pros: Ubiquitous, somewhat smaller learning curve
Cons: Fundamental limitations in formulas

20. Choosing your Software
Qualitative
NVivo
Pros: Can structure qualitative data
Cons: Expensive, can be difficult use

21. Choosing your Software
Qualitative
ATLAS.ti
Pros: Can structure qualitative data
Cons: Expensive, can be difficult use

22. Moving towards your results
Research oftentimes can be broken down into two distinct kinds:
Quantitative – Confirms (Deductive)
Qualitative – Exploratory (Inductive)
In reality, this differentiation is not concrete.

23. Where does software fit in?
Quantitative
Theory
Hypothesis
Test (Software)
Conclusion

24. Where does software fit in?
Qualitative
Data
Analysis (Software)
Patterns/Theory
Conclusion