Individual Project: Data Analysis & Presentation

The goal of the individual project is to give you the opportunity to find a dataset that interests you, analyze it using the tools we’ve learned in class, and present your findings to your peers.

Goals

  1. Data Acquisition: Find a dataset that is interesting to you. This could be from a public repository (e.g., Kaggle, TidyTuesday, government data) or data you have collected yourself.
  2. Data Cleaning: Demonstrate your ability to clean and prepare data for analysis.
  3. Exploratory Data Analysis (EDA): Use summary statistics and visualizations to understand the structure and relationships in your data.
  4. Communication: Effectively communicate your findings through a presentation.

Deliverables

1. Quarto Document

You will submit a Quarto document (.qmd) and the rendered HTML file. This document should contain all the code used for your analysis, along with narrative text explaining your steps and findings.

  • Introduction: Briefly describe the dataset and why you chose it.
  • Data Preparation: Show how you loaded and cleaned the data.
  • Analysis: Present your visualizations and summary statistics. Explain what they show.
  • Conclusion: Summarize your main takeaways.

2. Presentation

You will give a 5-minute presentation to the class.

  • Slides: You are required to use slides for your presentation. You can create them using Quarto (Revealjs), PowerPoint, Google Slides, or any other tool you prefer.
  • Content: Focus on the most interesting findings from your analysis. Do not walk us through your code line-by-line; focus on the insights.

Timeline

  • Proposal Due: [Date TBD] mechanism to submit dataset chioce.
  • Project Due: End of Term.
  • Presentations: Final week of class.

Grading Rubric

Category Description Points
Data Preparation Data is loaded correctly, cleaned, and tidy. 20
Analysis & Viz Appropriate visualizations and summary stats are used. 30
Narrative The Quarto doc is well-written and explains the analysis clearly. 20
Presentation Clear, engaging, and within the time limit. 20
Creativity/Effort Dataset choice and depth of analysis. 10
Total 100

Resources for Data