Introduction

This text is an informal beginner’s guide to the basics of statistics needed to conduct tests of statistical significance for simple experimental, quasi-experimental, and correlational research designs. Many free and open textbooks exist for more theoretical and traditional versions of introductory statistics, with more standard notation. This one is designed to be consistent with the approachable way I aim to teach the use of statistical analysis tools to students of psychology and the social sciences. The text is very informal and conversational, because it spawned from my written-out scripts to record brief video lessons.

Over the years, many students have been surprised by the fact that they actually enjoy learning statistics when presented simply, as a decision-making tool, and supported by engaging examples. If you are a student approaching statistics for the first time, I hope that is your experience with this resource.

In general in this textbook, I choose conceptual formulas with simplified notation. Learning to calculate by hand with less-intimidating formulas is intended to lead you through practice to conceptual inference. Much evidence in the literature of teaching statistics supports this approach. Although some students of statistics are fortunate enough to make mental leaps straight to the abstract, most of us require a more hands-on approach with several examples to make the key cognitive connections.

The material here is of my own creation, with some images and resources borrowed from other open-source materials. Please use this resource if you like. I do appreciate attribution, because it took me a long time to collect and develop some of these explanations, analogies, examples, and flow of logic.

First edition note: This book is bare basics so far. Some day I will hopefully add in the interactive exercises and demonstrations my students use to apply concepts and procedures as we go. My dream is to build exercises and examples for this simplified notation style and also a more traditional style, so students can see they are equivalent. I also hope someday to rework the videos I have created as a companion so they are suitable for embedding in the text. Corrections and suggestions for revisions are welcome.

Dedication: I dedicate this project to Dr. Bryan Hendricks, statistics prof extraordinaire, who worked for years in the University of Wisconsin system. As his teaching assistant, I learned from a master. Rest in peace, Dr. H.