Hypothesis Testing in Python
|
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests 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 and supply-chain data for medical supply shipments, you’ll gain a deep understanding of how these tests work and the key assumptions that underpin them. You’ll also discover how non-parametric tests can be used to go beyond the limitations of traditional hypothesis tests.
User Reviews
Be the first to review “Hypothesis Testing in Python”
Related Products
Introduction to Regression with statsmodels in Python
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.
Hierarchical and Mixed Effects Models in R
In this course you will learn to fit hierarchical models with random effects.
Intro to Statistics
Gain a foundational understanding of statistical concepts and their application in data analysis.
Foundations of Probability in R
In this course, you'll learn about the concepts of random variables, distributions, and conditioning.
Hypothesis Testing in R
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Statistics
Delve into statistical theory and its applications in data analysis and research methodologies.
There are no reviews yet.