Statistical inference

Interactive SAS tutorials supporting the OpenIntro Introduction to Modern Statistics textbook.

Statistical inference

This tutorial builds on statistical inference ideas we’ve learned about so far and applies them to different data scenarios. We will review how to conduct statistical inference in these scenarios using both simulation-based methods as well as mathematical methods based on the central limit theorem. We will encounter several new point estimates and a couple new distributions. In each case, the inference ideas remain the same: determine which point estimate or test statistic is useful, identify an appropriate distribution for the point estimate or test statistic, and apply the ideas of inference.

Learning objectives

Lessons

In each of the lessons below, you will learn how to (a) calculate a confidence interval and (b) perform a hypothesis test for the parameter of interest. Each of the lessons focuses on a different data scenario—one proportion, difference in two proportions, one mean, difference in two means, etc. We will introduce new statistics and distributions as needed.

Inference for a single proportion

Inference for a difference in two proportions

Chi-squared test of independence

Chi-squared goodness of fit test

Bootstrapping for estimating a parameter

Introducing the t-distribution

Inference for difference in two means

Comparing many means

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