Data Analysis in the Psychological Sciences: A Practical, Applied, Multimedia Approach

Reviewed by J. Marlie Henry, Adjunct Faculty, University of Saint Francis on 8/22/25

Comprehensiveness rating: 5 see less

The content is consistent with the purpose of the book. It provides sufficient content as an introductory text and includes a complete glossary. This is not an exhaustive statistics text but does provide content aligned with its purpose.

Content Accuracy rating: 5

Content is accurate and free of error throughout. There are no inappropriate biases evident.

Relevance/Longevity rating: 5

The text is currently relevant with up-to-date content. Given its approach and structure, any needed updates to maintain relevancy would seem to be doable.

Clarity rating: 5

This is a very approachable and clearly written text. It does use necessary statistical jargon but not without context. Terms are explained as simply and approachably as possible while also advancing deeper meaning. That is commendable, as it is not an easy task with this content.

Consistency rating: 5

The text flows conceptually and is internally consistent.

Modularity rating: 5

The unit-framework of this text makes it very easy to use in part or whole. The units seem to be conceptually contained even though they do flow sequentially and meaningfully. So, it could be reorganized as needed or used in parts to supplement other materials.

Organization/Structure/Flow rating: 5

The topics are organized logically such that they do flow in a conceptually meaningful manner.

Interface rating: 3

In part, this was easy to navigate. However, it was not without error. Ensuring the links are accurate and lead to resources successfully would strengthen this book. For illustration, see the Mean and Sample Standard Deviation section for a number of links that lead to tinyurl/cloudfront.net sessions that are not accessible. In addition, links that open in a new page can help ensure the reader remains engaged in reading the book rather than leading the reader away from the book entirely.

Grammatical Errors rating: 5

There were no significant issues with grammatical errors.

Cultural Relevance rating: 5

The text examples seemed appropriate. The text did not seem to be culturally insensitive or offensive in any way.

This is a very promising and approachable text. Approachability in this content area is not an easy task. So, that is commendable. Editing to correct navigational issues would strengthen the text.

Reviewed by Ruth Casper, Instructor, Rochester Community & Technical College on 6/15/23

Comprehensiveness rating: 3 see less

This brief book covers the main concepts of statistical analysis, explains descriptive statistics very well, and explains how to use Excel and R to conduct data analysis. It contains a glossary but no index. It does not provide information on inferential statistics (t-test, ANOVA), as the authors plan to cover these topics in a future textbook.

Content Accuracy rating: 5

Although I am not familiar with R (I have used SPSS and JASP), the content appears to be accurate and unbiased.

Relevance/Longevity rating: 5

Using R for data analysis is currently quite popular, so the timing if this textbook is great. And Excel is standard software, so information about Excel is appropriate.

Clarity rating: 4

I found the book very easy to follow. Some of the bolded terms were not defined in the text; however, they were covered in the glossary.

Consistency rating: 5

There are no concerns with consistency.

Modularity rating: 5

The text is easy to read, with the occasional "boxed information" to highlight concepts. Additional boxes are used for practice items.

Organization/Structure/Flow rating: 5

The organization is logical, and the topics flow well.

Interface rating: 4

Some of the boxes' layout is a bit off; perhaps this occurred when saving it as a pdf. For example, the word "Hours" might be divided into two lines, with "Ho" on the first line and "urs" on the second line. The authors provide links to helpful videos explaining how to perform tasks in Excel and R.

Grammatical Errors rating: 5

There are minimal issues concerning grammar.

Cultural Relevance rating: 5

No concerns here.

This textbook is very readable and brief. However, since it was designed to cover descriptive statistics and correlation, it does not address t-tests, ANOVA, factorial designs, and Chi-Square. Once the authors' next book comes out (covering these topics), this would be a fine resource for the instructor who uses R as a statistical analysis software package.