Hypothesis Testing with 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.

Syllabus

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