Scott Pardo
Statistical Analysis of Empirical Data: Methods for Applied Sciences
Statistical Analysis of Empirical Data: Methods for Applied Sciences
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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 covers selecting data analytic methods and explaining the nature of analyses,with R code and sample datasets provided.
Format: Paperback / softback
Length: 277 pages
Publication date: 05 May 2021
Publisher: Springer Nature Switzerland AG
Researchers and students who employ empirical investigation in their work face the daunting task of selecting statistical methods for analysis, often needing to justify these choices. This comprehensive book is specifically tailored to readers with limited background in statistical methodology, providing guidance on defending their statistical decision-making in the realms of research and practice. Its primary objective is to assist students and scholars in finding the necessary information to select data analytic methods and confidently articulate their statistical research processes.
Each chapter begins with a thought-provoking conundrum related to the selection or explanation of an analysis. Throughout the chapter, the analysis is thoroughly described, accompanied by insightful justifications for the chosen method.
This volume, aimed at the non-specialist, serves as a valuable resource for courses on research methods and statistical applications across various biological, medical, life, social, and physical sciences. It will also be of immense benefit to academic and industrial researchers in engineering and the physical sciences, as it enhances their understanding of how to analyze empirical data effectively. While the book assumes a foundational education in calculus, it includes a brief review of fundamental concepts of probability and statistics, as well as a primer on some concepts in elementary calculus and matrix algebra. Additionally, R code and sample datasets are provided to facilitate a deeper understanding of the topics discussed.
Weight: 454g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030433307
Edition number: 1st ed. 2020
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