Sprint Challenge: Statistical Tests and Experiments
Introduction
The Sprint Challenge is your opportunity to demonstrate the statistical concepts you've learned throughout this sprint. You'll apply hypothesis testing with t-tests and chi-square tests, Bayesian reasoning, and linear regression techniques to real-world datasets.
Accessing the Challenge
Challenge Materials
- GitHub Repository: Access the notebook here
- Google Colab: Open in Google Colab (Make sure to Copy to your Google Drive)
Challenge Requirements
What You'll Demonstrate
This challenge will assess your ability to:
- Apply hypothesis testing concepts using t-tests on real-world data
- Implement chi-square tests for independence on categorical variables
- Use conditional probability and Bayesian reasoning to update prior beliefs
- Create and interpret linear regression models
- Calculate and analyze correlation coefficients
- Visualize relationships between variables
- Draw statistically sound conclusions from data analysis
Tips for Success
Preparation Advice
- Review all module content, especially the guided projects
- Make sure you understand the core concepts from each module
- Complete all module projects before attempting the sprint challenge
- Attend code-along sessions for additional practice
- Review your notes on hypothesis testing, Bayesian statistics, and linear regression
- Practice interpreting p-values, correlation coefficients, and regression parameters