Introduction

Confounds, reliability, interval and ratio data, random assignment, extraneous variables—these terms should all sound familiar to you, but unless you have recently reviewed your notes from your previous research methods courses, you might be feeling a bit rusty on what they actually mean. A lot of this chapter will review what you learned in previous research methods courses. However, there are a few concepts that students often find tricky to fully grasp. Recognizing and defining these key terms is often much easier than applying and generating examples of them.

Furthermore, this chapter will start to highlight the connection between research methods and statistics, which is often overlooked in introductory research methods and statistics classes. Understanding how the two are connected will help you to understand why we do the things we do, both when designing studies and when analyzing our data.

This chapter also will provide a refresher on the scientific research process and on how to critique and design experimental and correlational studies.

But, first, let’s meet Muddled Max. Max is a zealous but novice researcher who needs some help with research design. Max joins us today with their first idea. Max has noticed at parties that redheads often have clusters of people around them who want to talk. Max wondered: Do redheads appear more friendly than other people?

Max asks 20 people from their social circle to rate the images below in terms of their friendliness (on a scale from 1 = “not at all friendly” to 5 = “very friendly”).

Images for Hair Colour Study

Ten friends rate image A and ten friends rate image B. Max then analyzes the results.

• Figure A. Woman taking photo while showing smile by Gabriel Silvério, via Unsplash, is used under the Unsplash License.
• Figure B. Girl sitting at a table in a library and reading a book by Yaroslav Shuraev, via Pexels, is used under the Pexels License.

References

[reference citations for this section?]