Hypothesis Testing for Data Science

Learn to code frameworks that will support your hypotheses with statistical analysis.

 

Includes:
  • 2.8 Hours of Video
  • Certificate of Completion
  • Project Files
  • Closed Captions
Join 400,000 Satisfied Students
$50

Benefits

  • On-demand, 24/7 access
  • 2.8 hours of video
  • Certificate of completion
  • Project files and PDF notes
  • Closed captions

Overview

This title is part of the Data Science Mini-Degree

Hypotheses (explanations for things that are yet to be proved) are an important facet of data science, as they help to drive innovation and progress. This course will show you how to strengthen your hypotheses by supporting your claims with statistical evidence. From a foundational understanding of the concepts underlying hypothesis testing, to working through lots of different, practical examples, and even coding your own testing framework from the ground up, you will have everything that you need to create bullet-proof hypotheses.

In this course, you will learn:

  • Random Variables
  • Probability Distributions (including Gaussian/Normal Distributions)
  • z-tests
  • t-tests

About the Data Science Mini-Degree

The Data Science Mini-Degree is a collection of professional-grade online courses designed to take you from absolute beginner to industry-ready Data Scientist with Python. From the basics of reading and storing data, to using statistical analysis to solve real-world problems, and visualizing your data in beautiful plots and charts, this comprehensive curriculum features everything you need to get started in the industry.

https://www.youtube.com/watch?v=_bFvxfP4ov0&t=3s

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Curriculum

Requirements

Learn to code frameworks that will support your hypotheses with statistical analysis.

  • On-demand, 24/7 access
  • 2.8 hours of on-demand video
  • Certificate of completion
  • Closed captions

$50

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