Data Analysis

Abstract

• A short paragraph summary of the introduction, methods, results, and conclusions.

Introduction

• The introduction should introduce your general research question and your data

Methods

Describe your data.

• How many observations are there?
• What are the observations?
• What are the variables?
• Is there any missing data?

Describe your methods.

• (If missing data exists) How are you going to deal with missing data?
• What models are you going to fit?
• How are you going to evaluate whether the models meet their assumptions?
• If doing inference: What hypothesis tests are you going?
• If doing prediction: How will you determine which model is best?

Results

• Which model did you decide on?
• Demonstrate that this model fit the assumptions
• If doing inference
  • What are the \(\beta\) coefficients of that model? What are their confidence intervals?
  • How do you interpret these \(\beta\) coefficients in the context of this model?
  • What is the result of your hypothesis test?
• If doing prediction
  • What were the results of your “best” prediction model?
  • What is the equation for your prediction model?

Discussion & Conclusion

• Summarize what you’ve learned and why it matters

Appendix

• Include any code
• Include any additional plots / results that were used