Hypothesis Testing with Python

Learn to plan, implement, and interpret a hypothesis test in Python.

In this course, you'll learn to plan, implement, and interpret a hypothesis test in Python. Hypothesis testing is used to address questions about a population based on a subset from that population. For example, A/B testing is a framework for learning about consumer behavior based on a small sample of consumers.

This course assumes some preexisting knowledge of Python, including the NumPy and pandas libraries.

• Introduction to Hypothesis Testing: Find out what you'll learn in this course and why it's important.
• Informational: Introduction to Hypothesis Testing
• Article: Descriptive vs. Inferential Statistics
• Hypothesis testing: Testing a Sample Statistic: Learn about hypothesis testing and implement binomial and one-sample t-tests in Python.
• Article: The Central Limit Theorem
• Article: Introduction to Hypothesis Testing (Simulating a One-Sample T-Test)
• Lesson: One-Sample T-Tests in SciPy
• Lesson: Simulating a Binomial Test
• ExternalResource: Scipy Statistical Functions | Python
• Lesson: Significance Thresholds
• Quiz: Hypothesis testing for a Sample Statistic
• Project: Heart Disease Research Part I
• Hypothesis Testing: Testing an Association: Learn about hypothesis tests that can be used to evaluate whether there is an association between two variables.
• Lesson: Hypothesis Testing: Associations
• Quiz: Hypothesis Testing: Associations
• Project: Heart Disease Research Part II
• Experimental Design: Learn to design an experiment to make a decision using a hypothesis test.
• Article: How to Choose a Hypothesis Test
• Lesson: A/B Testing: Sample Size Calculators
• Lesson: Sample Size Determination with Simulation
• Quiz: Sample Size Determination
• Project: A/B Testing at Nosh Mish Mosh
• Hypothesis Testing Projects: Practice your hypothesis testing skills with some additional projects!
• Project: Familiar: A Study In Data Analysis
• Project: FetchMaker
• Project: Analyzing Farmburg's A/B Test