Statistical analysis of empirical data : methods for applied sciences / Scott Pardo.
Pardo, Scott.
2020
QA276
Available Online

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Title Statistical analysis of empirical data : methods for applied sciences / Scott Pardo.
Author Pardo, Scott.
ISBN 9783030433284
3030433285
9783030433277
3030433277
DOI https://doi.org/10.1007/978-3-030-43328-4
Publication Details Cham : Springer, 2020.
Language English
Description 1 online resource (278 pages)
Item Number 10.1007/978-3-030-43328-4 doi
Call Number QA276
Dewey Decimal Classification 519.5
Summary 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Description based on print version record.
Available in Other Form Statistical Analysis of Empirical Data : Methods for Applied Sciences
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Chapter 1: Fundamentals
Chapter 2: Sample Statistics are NOT Parameters
Chapter 3: Confidence
Chapter 4: Multiplicity and Multiple Comparisons
Chapter 5: Power and the Myth of Sample Size Determination
Chapter 6: Regression and Model Fitting with Collinearity
Chapter 7: Overparameterization
Chapter 8: Ignoring Error Control Factors and Experimental Design
Chapter 9: Generalized Linear Models
Chapter 10: Mixed Models and Variance Components
Chapter 11: Models, Models Everywhere...Model Selection
Chapter 12: Bayesian Analyses
Chapter 13: The Acceptance Sampling Game
Chapter 14: Nonparametric Statistics
A Strange Name
Chapter 15: Autocorrelated Data and Dynamic Systems
Chapter 16: Multivariate Analysis and Classification
Chapter 17: Time-to-Event: Survival and Life Testing
Index.

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