Loading...

7.04 Step-by-step plan

Course video 54 of 57

In this module we’ll talk about statistical hypotheses. They form the main ingredients of the method of significance testing. An hypothesis is nothing more than an expectation about a population. When we conduct a significance test, we use (just like when we construct a confidence interval) sample data to draw inferences about population parameters. The significance test is, therefore, also a method of inferential statistics. We’ll show that each significance test is based on two hypotheses: the null hypothesis and the alternative hypothesis. When you do a significance test, you assume that the null hypothesis is true unless your data provide strong evidence against it. We’ll show you how you can conduct a significance test about a mean and how you can conduct a test about a proportion. We’ll also demonstrate that significance tests and confidence intervals are closely related. We conclude the module by arguing that you can make right and wrong decisions while doing a test. Wrong decisions are referred to as Type I and Type II errors.

О Coursera

На онлайн-курсах, специализациях и дипломных программах у вас будут первоклассные преподаватели из лучших университетов и учебных заведений мира.

Community
Join a community of 40 million learners from around the world
Certificate
Earn a skill-based course certificate to apply your knowledge
Career
Gain confidence in your skills and further your career