Statistical Analysis of Empirical Data : Methods for Applied Sciences

Scott Pardo

ISBN 10: 3030433307 / ISBN 13: 9783030433307

Published by Springer International Publishing, 2021

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical methodology who seek guidance in defending their statistical decision-making in the worlds of research and practice. It is devoted to helping students and scholars find the information they need to select data analytic methods, and to speak knowledgeably about their statistical research processes. Each chapter opens with a conundrum relating to the selection of an analysis, or to explaining the nature of an analysis. Throughout the chapter, the analysis is described, along with some guidance in justifying the choices of that particular method.Designed to offer statistical knowledge to the non-specialist, this volume can be used in courses on research methods, or for courses on statistical applications to biological, medical, life, social, or physical sciences. It will also be useful to academic and industrial researchers in engineering and in the physical sciences who will benefit from a stronger understanding of how to analyze empirical data. The book is written for those with foundational education in calculus. However, a brief review of fundamental concepts of probability and statistics, together with a primer on some concepts in elementary calculus and matrix algebra, is included. R code and sample datasets are provided.

Seller Inventory # 9783030433307

Bibliographic Details

• Title: Statistical Analysis of Empirical Data : Methods for Applied Sciences
• Publisher: Springer International Publishing
• Publication Date: 2021
• Language: English
• ISBN 10: 3030433307
• ISBN 13: 9783030433307
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 16D millimeters 235 millimeters width by 155 millimeters height by 16 millimeters depth
• Weight: 446 grams

About this title

Synopsis

Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical methodology who seek guidance in defending their statistical decision-making in the worlds of research and practice. It is devoted to helping students and scholars find the information they need to select data analytic methods, and to speak knowledgeably about their statistical research processes. Each chapter opens with a conundrum relating to the selection of an analysis, or to explaining the nature of an analysis. Throughout the chapter, the analysis is described, along with some guidance in justifying the choices of that particular method.

Designed to offer statistical knowledge to the non-specialist, this volume can be used in courses on research methods, or for courses on statistical applications to biological, medical, life, social, or physical sciences. It will also be useful to academic and industrial researchers in engineering and in the physical sciences who will benefit from a stronger understanding of how to analyze empirical data. The book is written for those with foundational education in calculus. However, a brief review of fundamental concepts of probability and statistics, together with a primer on some concepts in elementary calculus and matrix algebra, is included. R code and sample datasets are provided.

About the Author

Scott A. Pardo, Ph.D., is a professional statistician, having worked in a wide variety of industrial contexts, including the U.S. Army Information Systems Command, satellite systems engineering, pharmaceutical development, and medical devices. He is the author of Empirical Modeling and Data Analysis for Engineers and Applied Scientists (Springer 2016). He is a Six Sigma Master Black Belt, an Accredited Professional Statistician (PStat™), and holds a Ph.D. in Industrial and Systems Engineering from the University of Southern California.