This course will begin by introducing the basic concepts of how to describe and visualize data, the fundamentals of using statistics to make inferences, and the logic of null hypothesis testing. Various types of hypothesis tests will be introduced, along with criteria for selecting which is appropriate for different study conditions. As an extension of null hypothesis significance tests, you will learn about how to interpret effect sizes and confidence intervals, along with statistical power, before being introduced to alternatives to null hypothesis significance testing.

In this first section of the course, the fundamental concept of the variable is introduced and explained, along with some of the basic statistical methods we use to describe and summarize variables in data sets.

In this module, we move on from descriptive statistics like the mean and standard deviation into inferential statistics, which help us use sample data to draw inferences about the populations the samples represent.

In this section of the course, we consider the role of null hypothesis significance testing in psychological research, some objections that have been raised to that approach, and some alternative approaches that have been proposed.

Review the main ideas from the previous module, organized by learning objectives (LOs).

This module provides a variety of information and tools from the American Psychological Association (APA) that will help inspire you as you complete your coursework and plan your career goals. Explore APA resources on various psychological issues and scholarly research and writing; a list of sites providing valuable resources on diversity, equity, and inclusion in psychology education and in the professional community; resources on a career in psychology; and links to career opportunities at the APA.