Congratulations!

Experimental Design in Python

James Chapman

Curriculum Manager, DataCamp

Chapter 1

• Experiment and data setup
• Normal data

Chapter 2

• Experiment and data setup
• Normal data
• Factorial and randomized block designs
• Covariate adjustment

Chapter 3

• Experiment and data setup
• Normal data
• Factorial and randomized block designs
• Covariate adjustment
• Picking the right hypothesis test
• Post-hoc analysis
• P-values, alpha, and test errors
• Power analysis

Chapter 4

• Experiment and data setup
• Normal data
• Factorial and randomized block designs
• Covariate adjustment
• Picking the right hypothesis test
• Post-hoc analysis
• P-values, alpha, and test errors
• Data storytelling with experiments
• Transformations and nonparametric tests

What next?

Real-world projects:

• Hypothesis Testing with Men's and Women's Soccer Matches
• Hypothesis Testing in Healthcare
• Experimental Design Project

 

Applied statistics courses:

• A/B Testing in Python
• Analyzing Survey Data in Python
• Bayesian Data Analysis in Python
• Foundations of Inference in Python

Congratulations!

Experimental Design in Python