Mind on Statistics - Standalone Book

by Jessica M. Utts

MIND ON STATISTICS, Fifth Edition, helps you develop a conceptual understanding of statistical ideas and shows you how to find meaning in data. The authors-who are committed to changing any preconception you may have about statistics being boring-engage your curiosity with intriguing questions, and explain statistical topics in the context of interesting, useful examples and case studies. You'll develop your statistical intuition by focusing on analyzing data and interpreting results, rather than on mathematical formulation. As a result, you'll build both your statistical literacy and your understanding of statistical methodology.

Genres: Textbooks

768 pages, Hardcover

First published January 1, 2001

About the author

Jessica M. Utts is professor of statistics at University of California, Irvine, known particularly for her statistical evaluations of parapsychological claims. She serves on the executive board of the International Remote Viewing Association (IRVA).

Reviews

[Jerzy]

Suggested in Nicholson & Ridgway's rejoinder to White & Godard:

"We also agree that most textbooks on statistics place too much emphasis on NHST (without specifying the situations where NHST is and is not appropriate), and too little emphasis on issues of design (such as sampling) and how the interpretation of outcomes of NHST should be expressed. Mind on Statistics (Utts and Heckard, 2015) is an example of a textbook where key issues in NHST are addressed properly."

[Kellyanne]

Just the right level of detail, with explanation/examples well spaced to hold interest. Never having done anything beyond very basic statistics, this book was easy to work through and stepped through the content with enough depth but without overloading me. Really pleased.

[Isaac]

A decent overview with lots of examples, but not much substance or rigor. Could be suitable if struggling, but may get too tedious.

[Trang]

Great book for undergrad level: very well organized with detailed examples, summaries, and applications without overwhelming students. The math could be more rigorous, but felt right for an intro to stats class.