Data Analysis Presentation

Data AnalysisRWJF || GRC

Available SoftwareQuantitative

R

SPSS

STATA

Qualitative

NVivo

Atlas.ti

The Big Problem

How do you ask a question that a computer can answer?

Asking the right question

Are you looking for descriptive statistics?

Are you looking for confirmation/refutation of a hypothesis?

Asking the right question

Descriptive statistics are perhaps the easiest to structure.

Quantitative: Central tendency, quartiles, data range

Qualitative: Frequent words, reoccurring themes

Hypothesis testing requires additional steps

Formulate hypothesis prior to test, have a clear null and alternative established

Asking the right question

H0: There is no difference/relationship

Ha: There is a difference/relationship

Asking the right question

Quantitative

Regression

Is there a relationship between variable X and Y?

Asking the right question

Quantitative

Difference

Is there a difference between variable X and Y?

Asking the right question

Many problems with any kind of data analysis software stem from impossible to answer questions.

Asking the right question

Simplify Questions

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

Simplify Questions

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

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.

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.

Simplify Questions

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

Choosing your Software

Quantitative

R

Pros: Most flexibility, free, customized software

Cons: Very difficult to learn

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.

Choosing your Software

Quantitative

STATA

Pros: Allows for syntax-based do-files that create consistent change tracking

Cons: Expensive, can be difficult use

Choosing your Software

Quantitative

Excel

Pros: Ubiquitous, somewhat smaller learning curve

Cons: Fundamental limitations in formulas

Choosing your Software

Qualitative

NVivo

Pros: Can structure qualitative data

Cons: Expensive, can be difficult use

Choosing your Software

Qualitative

ATLAS.ti

Pros: Can structure qualitative data

Cons: Expensive, can be difficult use

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.

Where does software fit in?Quantitative

Hypothesis

Test (Software)

Conclusion

Theory

Where does software fit in?Qualitative

Data

Conclusion

Patterns/Theory

Analysis (Software)