Time to completeApprox. 10 hours
Certificate of completionIncluded with paid plans
About this course
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.
Syllabus6 lessons • 6 projects • 3 quizzes
Hands-on learningDon’t just watch or read about someone else coding — write your own code live in our online, interactive platform. You’ll even get AI-driven recommendations on what you need to review to help keep you on track.
Projects in this course
Heart Disease Research Part IInvestigate risk factors for heart disease using descriptive statistics and hypothesis tests.
Heart Disease Research Part IIInvestigate risk factors for heart disease using descriptive statistics and hypothesis tests.
A/B Testing at Nosh Mish MoshNosh Mish Mosh is a food startup with a cool new idea. Help them make data driven decisions by analyzing their user base.
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Practice ProjectsGuided projects that help you solidify the skills and concepts you're learning.
AssessmentsAuto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
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Frequently asked questions about Hypothesis Testing with Python
After drawing conclusions from data, you have to make sure it’s correct, and hypothesis testing involves using statistical methods to validate our results.