Sprint Challenge

Sprint Challenge Overview

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.

Challenge Setup

To get started with the Sprint Challenge, follow these steps:

1. Access the Jupyter notebook using the links below.
2. Complete all tasks in the notebook, demonstrating your understanding of the sprint concepts.
3. Submit your completed challenge according to the provided instructions.

Challenge Expectations

The Sprint Challenge is designed to test your mastery of the following key concepts:

• Hypothesis testing with t-tests: Applying t-tests to real-world data and interpreting results
• Chi-square tests: Implementing chi-square tests for independence on categorical variables
• Bayesian statistics: Using conditional probability and Bayesian reasoning to update prior beliefs
• Linear regression: Creating and interpreting linear regression models
• Correlation analysis: Calculating and analyzing correlation coefficients
• Data visualization: Visualizing relationships between variables
• Statistical interpretation: Drawing statistically sound conclusions from data analysis

What to Expect

The Sprint Challenge will involve working with real-world datasets and demonstrating your ability to:

1. Apply hypothesis testing concepts using t-tests on real-world data
2. Implement chi-square tests for independence on categorical variables
3. Use conditional probability and Bayesian reasoning to update prior beliefs
4. Create and interpret linear regression models
5. Calculate and analyze correlation coefficients
6. Visualize relationships between variables
7. Draw statistically sound conclusions from data analysis