Beyond the T-Test

Scott A. Pardo

ISBN 10: 3031844815 / ISBN 13: 9783031844812

Published by Springer, 2026

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This book was inspired by years of questions asked by non-statistical professionals, from social scientists, public policy analysts, regulatory affairs specialists, engineers, and physical scientists. It provides them with both an intuitive explanation of many common statistical methods and enough mathematical background to help them justify those methods to others, such as regulatory agencies. It provides an introduction to commonly used methods that are not covered in a first elementary statistics course, such as partial least squares, MCMC, and neural networks. It also provides R code for making all the computations described in the text.As a textbook, it could be used as a second course instatistics for non-statisticians, in fields such as social sciences, public policy, engineering, chemistry, and physics. Many first-year graduate students have had an elementary statistics course, but were not exposed to enough of the mathematics to justify the application of those methods. Furthermore, they often encounter methods and concepts not touched upon in their first statistics course. This book provides the tools required to give a deeper understanding of statistical methods without being all about theorems and proofs.

Seller Inventory # 9783031844812

Bibliographic Details

• Title: Beyond the T-Test
• Publisher: Springer
• Publication Date: 2026
• Language: English
• ISBN 10: 3031844815
• ISBN 13: 9783031844812
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 17D millimeters 235 millimeters width by 155 millimeters height by 17 millimeters depth
• Weight: 476 grams

About this title

Synopsis

This book was inspired by years of questions asked by non-statistical professionals, from social scientists, public policy analysts, regulatory affairs specialists, engineers, and physical scientists. It provides them with both an intuitive explanation of many common statistical methods and enough mathematical background to help them justify those methods to others, such as regulatory agencies. It provides an introduction to commonly used methods that are not covered in a first elementary statistics course, such as partial least squares, MCMC, and neural networks. It also provides R code for making all the computations described in the text.

As a textbook, it could be used as a second course in statistics for non-statisticians, in fields such as social sciences, public policy, engineering, chemistry, and physics. Many first-year graduate students have had an elementary statistics course, but were not exposed to enough of the mathematics to justify the application of those methods. Furthermore, they often encounter methods and concepts not touched upon in their first statistics course. This book provides the tools required to give a deeper understanding of statistical methods without being all about theorems and proofs.

About the Author

Scott Pardo has worked in a wide variety of application areas, from The U.S. Army (Communications), to satellite systems and the Space Transportation System, combat simulation, cardiac pacemaker development, blood collection tubes, pharmaceuticals, and blood glucose measurement devices. He has worked on applications in R&D, manufacturing, quality, process simulation and development, analytic chemistry, and clinical trials.