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Beginner's Guide to Principal Components: Applications with Microsoft Excel by Kilem Li Gwet

Beginner's Guide to Principal Components: Applications with Microsoft Excel

by Kilem Li Gwet
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Book cover type: Paperback
  • ISBN13: 9781792354625
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Agreestat Analytics
  • Publisher Imprint: Agreestat Analytics
  • Publication Date:
  • Pages: 148
  • Original Price: GBP 22.56
  • Language: English
  • Edition: N/A
  • Item Weight: 362 grams
  • BISAC Subject(s): Probability & Statistics / Multivariate Analysis

Are you facing the challenge of analyzing complex datasets filled with correlated variables? Beginner's Guide to Principal Components introduces you to Principal Component Analysis (PCA), a powerful statistical method that simplifies data analysis by reducing dimensionality and revealing underlying patterns. By transforming your data into uncorrelated principal components, PCA allows you to replace dozens of variables with just a few key carefully constructed composite indicators, making your analysis clearer and more effective.


This book is designed for those new to PCA, offering a practical, step-by-step introduction without diving too deep into advanced mathematics. Some familiarity with linear algebra will help you grasp the concepts fully, but this guide emphasizes practical application over theoretical complexity. With clear explanations and hands-on examples, you'll learn how to compute principal components using Microsoft Excel, supported by a free downloadable Excel template for easy implementation.


Whether you're a researcher, student, or data analyst, this book bridges the gap between theory and application, providing you with the tools to apply PCA to real-world problems confidently. By the end, you'll understand how PCA works, how to compute it, and how to leverage it to make more informed, data-driven decisions.


Take control of your data and transform your analysis with PCA using this accessible, beginner-friendly guide!


    This book introduces the Excel template pca.xlsm, which can be downloaded for free from the link https: //agreestat.com/books/pca/pca.xlsm. I expect Excel users to find it useful for implementing the different techniques discussed in this book.

Gwet, Kilem Li: - Kilem Li Gwet, PhD, received his doctorate in Mathematics from Carleton University's School of Mathematics and Statistics, Ottawa (Canada), in 1997. His research focused on the design and analysis of statistical surveys. Over the years, his research interests have expanded to include inter-rater reliability, a field in which he has authored numerous influential books and papers. His work on inter-rater reliability can be explored through his profile on ResearchGate.Dr. Gwet's expertise in multivariate data analysis led him to apply Principal Component Analysis (PCA) to inter-rater reliability data. This experience inspired him to author his first book on PCA, which offers a mathematically rigorous yet practical approach using Microsoft Excel for implementation. His work on PCA provides a valuable resource for researchers and analysts seeking to understand and apply this important statistical technique.Dr. Gwet is always open to feedback and inquiries. You can reach him at gwet@agreestat.com, and he will respond promptly.

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