Name: Hypothesis Testing
Price: -1 USD

Hypothesis Testing

Overview

Hypothesis testing is one of the most important topics in all of statistics because it tells us whether our conclusions are statistically significant. In this course, you will learn about the fundamental role statistics plays in hypothesis testing as well as how to implement statistical concepts in Python.

Syllabus

Introduction

In this lesson, we begin the course by meeting the instructors and giving a quick introduction to experimentation.

Normal Distribution Theory

In this lesson, you'll learn the mathematics behind moving from a coin flip to a normal distribution.

Sampling Distributions and the Central Limit Theorem

In this lesson, you'll learn all about the underpinning of confidence intervals and hypothesis testing - sampling distributions.

Confidence Intervals

In this lesson, you'll learn how to use sampling distributions and bootstrapping to create a confidence interval for any parameter of interest.

Hypothesis Testing

In this lesson, you'll learn the necessary skills to create and analyze the results of hypothesis testing.

A/B Tests

In this lesson, you'll work through a case study of how A/B testing works in the context of website metrics for an online education company.

Analyze A/B Test Results

You will be working to understand the results of an A/B test run by an e-commerce website. Your goal is to work through to help the company understand if they should implement the new page design.