A Primer on Data Management, Statistical Analysis, and Associated Techniques

Fields, Brandon

ISBN 13: 9798887159034

Published by Oryson Press, 2026

About this Item

Seller Inventory # I-9798887159034

Bibliographic Details

• Title: A Primer on Data Management, Statistical Analysis, and Associated Techniques
• Publisher: Oryson Press
• Publication Date: 2026
• Language: English
• ISBN 13: 9798887159034
• Binding: Hardcover
• Condition: New

About this title

Synopsis

A Primer on Data Management, Statistical Analysis, and Associated Techniques "A Primer on Data Management, Statistical Analysis, and Associated Techniques" addresses the critical need for robust data handling and analytical rigor in an increasingly data-driven world. Effective data management is paramount for ensuring data quality, accessibility, and integrity, while statistical analysis provides the tools to uncover insights and make evidence-based decisions. Navigating the complexities of diverse datasets, selecting appropriate methodologies, and interpreting findings accurately present significant challenges across scientific, business, and social domains. This book systematically explores foundational data management principles, including best practices and policy considerations. It delves into advanced statistical concepts such as the multivariate normal distribution, measurement theory, and both exploratory and confirmatory factor analysis for dimension reduction and model evaluation. Further topics include random variables, comprehensive data analysis techniques from collection to communication, fundamental statistical concepts, hypothesis testing, statistical inference, and the principles of data mining. The book also examines mediation and moderation effects in statistical modeling. This essential resource is designed for students, researchers, and professionals seeking a comprehensive understanding of data management and statistical analysis.

About the Author

Brandon Fields, PhD, is a Germany-based authority in data analysis and statistical methodologies. Their expertise encompasses data management, multivariate normal distribution, factor analysis, and data mining principles. They provide comprehensive insights into complex data techniques.