Building Your First Classification Model in Python with Scikit-learn

Free Live ML Workshop #4 on Oct 1 - Register Now


Hypothesis Testing in Python


Hypothesis testing lets you answer questions about your datasets in a statistically rigorous way. In this course, you'll grow your Python analytical skills as you learn how and when to use common tests like t-tests, proportion tests, and chi-square tests. Working with real-world data, including Stack Overflow user feedback, you'll gain a deep understanding of how these tests work, and the key assumptions that underpin them.

You'll also discover how different tests are related using the “there is only one test" framework, before learning how to use non-parametric tests to go beyond the limitations of side-step the requirements of hypothesis tests.Read more.

This resource is offered by an affiliate partner. If you pay for training, we may earn a commission to support this site.

Career Relevance by Data Role

The techniques and tools covered in Hypothesis Testing in Python are most similar to the requirements found in Data Scientist job advertisements.

Similarity Scores (Out of 100)