Project Final Report

I306 Statistics for Informatics

Overview

The final report synthesizes all your previous work into a cohesive statistical analysis. You will also extend your analysis with regression modeling.

Due: End of Week 15 Points: 50

Report Structure

Your final report should be a polished document that could be understood by someone unfamiliar with your previous milestones. Use echo: false in your code chunks so that only output (not code) appears in the final document.

1. Introduction (5 points)

  • Introduce your dataset and its context
  • State your research questions
  • Explain why these questions are interesting or important

2. Data Description (5 points)

Summarize your dataset:

  • Source and collection method
  • Key variables used in your analysis
  • Any data cleaning or transformations performed

(You may build on and adapt content from Milestone 1)

3. Exploratory Analysis (10 points)

Present your most informative visualizations:

  • Include 3-4 key figures developed or adapted from Milestone 2
  • Each figure should have a caption and interpretation
  • Focus on visualizations that set up your statistical analyses

4. Statistical Analysis (10 points)

Present your inferential analyses:

  • Include your hypothesis test(s) and confidence interval(s) from Milestone 3
  • Clearly state conclusions in context
  • Discuss any limitations

5. Regression Analysis (15 points)

Extend your analysis with regression modeling:

  • Fit at least one regression model (linear or logistic, as appropriate)
  • Interpret coefficients in context
  • Assess model fit and assumptions
  • Discuss what the model reveals about your research questions

6. Conclusions (5 points)

  • Summarize your key findings in both statistical (what are the numbers?) and substantive (what do they mean?) terms
  • Discuss limitations of your analysis
  • Suggest directions for future analysis and research

Formatting Requirements

  • Use professional formatting throughout
  • All figures and tables should have captions
  • Use echo: false to hide code

Submission

Submit your .qmd source file and rendered output (PDF or HTML) to Canvas by the due date.

Grading Rubric

Component Points Criteria
Introduction 5 Clear context and research questions
Data Description 5 Complete, accurate description
Exploratory Analysis 10 Effective visualizations with interpretations
Statistical Analysis 10 Correct methods, valid interpretations
Regression Analysis 15 Appropriate model, correct interpretation
Conclusions 5 Thoughtful synthesis with limitations

Tips

  • This is synthesis of the project milestones, but should be more cohesive and developed, addressing any feedback on your milestones
  • Tell a coherent story from introduction to conclusion
  • Proofread carefully—this is a professional document