# An Introduction to Psychological Statistics

Garett C. Foster, University of Missouri-St. Louis

David Lane, Rice University

David Scott, Rice University

Mikki Hebl, Rice University

Rudy Guerra, Rice University

Dan Osherson, Rice University

Heidi Zimmer, University of Houston

Copyright Year: 2018

Publisher: University of Missouri - St. Louis

Language: English

## Formats Available

## Conditions of Use

Attribution-NonCommercial-ShareAlike

CC BY-NC-SA

## Reviews

The text is designed to be an introductory text for psychological statistics. As such, it begins with what statistics is, why we study statistics, and then covers basic material. It provides a nice introduction to the necessary foundational... read more

The text is designed to be an introductory text for psychological statistics. As such, it begins with what statistics is, why we study statistics, and then covers basic material. It provides a nice introduction to the necessary foundational material that will be referenced throughout the remainder of the text. The text contains a very detailed table of contents that uses clickable links for specific pages throughout the pdf. Although they are referenced through figures throughout the text, I believe it would have been beneficial to include the relevant statistical tables at the end of the book with a clickable link from the table of contents. I found it a bit odd that snippets of the tables were embedded throughout the text as figures rather than just including the full tables at the end.

In general, the content was accurate. There were a few instances where the material was oddly worded or a confusing. For example, when covering hypothesis testing, an example claims that because temperature is allowed to vary 1 degree in either direction means that the standard deviation must be 1. This is not how standard deviation is defined and can be misleading to students. Later in the text, when interpreting a correlation of -1, the authors state “as X goes up by some amount, Y goes down by the same amount, consistently”. This is an inaccurate interpretation of correlation. X and Y are more than likely on different scales, so they would not change by the same amount. This is a very important distinction as correlation quantifies the relationship of standardized scores, while slope considers the scales of the variables. It was easy to single out one or two cases because the almost the entirety of the text is accurate.

I think the content itself is up-to-date and will not need much updating. The only pieces that may need updating are those that show how to present the results. I believe it was intended to be APA style which may require updating if the APA guidelines change. I also liked the section on misleading graphics – not always included in introductory statistics books- so it was nice to see in this text. I think knowing about data visualization techniques will be a very useful skill for all students, especially in the era of big data.

The text was quite clear. The authors’ voices and senses of humor come out throughout the text making it a very enjoyable read.

In general, material is consistent. The authors do a great job of building on previous material, without the need to constantly flip between pages. There was one frustrating inconsistency. In learning statistics, it is essential that notation be kept consistent and accurate. Unfortunately, one of the most common values, sample size, was inconsistently labeled. It was the case where the same paragraph would flip between “N” and “n”. Besides sample size, there were peculiar notation choices. For example, when labeling the number of groups using subscript j, why count from 1, …, k? This seems like unconventional notation when the authors could have simply used j = 1, …, J. Other than these minor inconsistencies, the authors did a great job throughout.

The text can be divided into smaller sections as written. It would be hard to selectively chose sections to cover and not others because of the comprehensive nature of the material. However, these chapters can be selectively used if an instructor wanted to supplement their course without adapting the entire text. I am not advocating this, as I think the text would be suitable as a whole for a course, but it is possible.

I believe the authors had a logical flow to their presentation of material. They have also designed the text (as in the above comment) in a way so that pieces can be moved around to cater to the instructor.

Some of the images are a bit blurry. They were still interpretable, but it was a bit distracting. Navigation was easy – especially as I read it on my e-reader – which I think will be a big benefit to students (using tablets, e-readers, PCs, or printing the text).

There were no noticeable grammatical errors.

I don’t see any cultural bias in the text or exercises sets. Although not necessarily cultural, I like how this text is inclusive to those with color deficiencies. For example, when describing a graph with multiple colored lines, the authors also reference the position of each line on the graph. This is not only useful for those with color deficiencies but also for those who read the text on an e-reader that doesn’t have color.

I really enjoyed reading through the text and thought it was comprehensive enough for a full semester introductory psychological statistics course. If I were to adapt this text for my course, which I am strongly considering, I will have to supplement with exercises. The exercises at the end of each chapter are most likely not particularly interesting for psychology students nor do they tap into any higher thinking besides simple recall and application. They are useful practice of the basics but will not provide any indication of advanced learning. I also really enjoyed the graphics for regression that talk through the linear model. I thought these were very helpful to students. Again, I thought this text is great and am strongly considering adapting it.

We currently use Gravetter & Walleneau and this book seems to cover nearly all of the same material. The main topic that this text does not cover is factorial ANOVA, which is an important and complex topic for undergraduates. However, our... read more

We currently use Gravetter & Walleneau and this book seems to cover nearly all of the same material. The main topic that this text does not cover is factorial ANOVA, which is an important and complex topic for undergraduates. However, our current book focuses solely on calculating Factorial ANOVA and not on interpreting main effects and interactions so I have to supplement our current book significantly, so it would not change my teaching approach. It provides the definitional formula for the standard deviation which I find more useful than other texts. Good table of contents but no index or glossary. This book seems like a very good OER option, so our current plan is adopt this text for next year.

As far as I can tell, all of the content seems to be accurate, formulas are accurate, and the material is unbiased

There may need to be some updates to the examples, but the content overall is very timeless.

I primarily made this judgment by looking at one of the hardest topics for students to understand in statistics: Central Limit Theorem. This book has a very good explanation and in some ways is superior to Gravetter et al. There are excellent graphs that explain how sample size affects the variability of the normal curve. My main purpose for using a statistics textbook is so that students have access to a reference source, but also to provide practice problems. The problems are good, but not as many as I would like. Plus I think in order to get the answers to the even questions you have to contact the author of the book because instructor information is not easy to access (good if you plan on using those questions for homework).

I did not notice any issues with terminology -- the topics build easily from each other and use previous knowledge to help students follow along.

The text has distinct chapters and subheadings, and some reference to previous chapters is necessary in a statistics book. The book is not overly self-referential.

The text follows the order of most psychological statistics textbooks - it is logical and builds from each chapter. The order is exactly the order in which I cover the material (correlation and chi square at the end).

It is visually appealing, the graphs and charts are well done. The text is clear and easy to read.

I did not notice any errors.

I did not notice any issues with cultural relevance. The book has very good and universal examples that are applicable to Psychology students.

## Table of Contents

- Prologue: A letter to my students
- Chapter 1: Introduction
- Chapter 2: Describing Data using Distributions and Graphs
- Chapter 3: Measures of Central Tendency and Spread
- Chapter 4: z-score and the Standard Normal Distribution
- Chapter 5: Probability
- Chapter 6: Sampling Distributions
- Chapter 7: Introduction to Hypothesis Testing
- Chapter 8: Introduction to t-tests
- Chapter 9: Repeated Measures
- Chapter 10: Independent Samples
- Chapter 11: Analysis of Variance
- Chapter 12: Correlations
- Chapter 13: Linear Regression
- Chapter 14: Chi-square
- Epilogue: A Brave New World

## About the Book

We are constantly bombarded by information, and finding a way to filter that information in an objective way is crucial to surviving this onslaught with your sanity intact. This is what statistics, and logic we use in it, enables us to do. Through the lens of statistics, we learn to find the signal hidden in the noise when it is there and to know when an apparent trend or pattern is really just randomness. The study of statistics involves math and relies upon calculations of numbers. But it also relies heavily on how the numbers are chosen and how the statistics are interpreted.

## About the Contributors

### Authors

**Garett C. Foster**, University of Missouri-St. Louis

**David Lane**, Rice University

**David Scott**, Rice University

**Mikki Hebl**, Rice University

**Rudy Guerra**, Rice University

**Dan Osherson**, Rice University

**Heidi Zimmer**, University of Houston, Downtown Campus