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Hypothesis Testing in Python

中级技能水平
更新时间 2025年12月
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.
免费开始课程
PythonProbability & Statistics
4小时
15 视频
50 练习
3,750 经验值
58,937
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课程描述

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.The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos. The course glossary can be found on the right in the resources section. To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.

先决条件

Sampling in Python
1

Hypothesis Testing Fundamentals

How does hypothesis testing work and what problems can it solve? To find out, you’ll walk through the workflow for a one sample proportion test. In doing so, you'll encounter important concepts like z-scores, p-values, and false negative and false positive errors.
开始章节
2

Two-Sample and ANOVA Tests

In this chapter, you’ll learn how to test for differences in means between two groups using t-tests and extend this to more than two groups using ANOVA and pairwise t-tests.
开始章节
Hypothesis Testing in Python
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