Beginner's Guide to Principal Components - Gwet, Kilem Li
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The Beginner's Guide to Principal Components is a book that introduces beginner readers to the field of principal component analysis. Principal component analysis was invented in the beginning of the twentieth century and has been extensively used by statisticians and social scientists. It has found new applications in the era of big data and artificial intelligence. With a growing number of users of principal component analysis, comes the need to present the materials for a broader audience with limited mathematical background, but with a clear desire to understand how the techniques work.…mehr

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Produktbeschreibung
The Beginner's Guide to Principal Components is a book that introduces beginner readers to the field of principal component analysis. Principal component analysis was invented in the beginning of the twentieth century and has been extensively used by statisticians and social scientists. It has found new applications in the era of big data and artificial intelligence. With a growing number of users of principal component analysis, comes the need to present the materials for a broader audience with limited mathematical background, but with a clear desire to understand how the techniques work. This book does not require a strong background in linear algebra. All concepts related to linear or matrix algebra and needed to understand the principal components will be introduce at a basic level. However, any prior exposure to linear or matrix algebra will be helpful. The more you want to understand principal components, the deeper you need to delve into the underlying mathematics. ¿ One can use any of the software products that implement principal component analysis, without having to worry about the underlying mathematics. However, I advise that you develop some understanding of the logic and the mechanics of principal component analysis before you start crunching numbers. ¿ This book introduces the Excel template pca.xlsm, which can be downloaded for free at https://agreestat.com/books/pca/pca.xlsm. I expect Excel users to find it useful for implementing the different techniques discussed in this book. Non Excel users have a few free alternative options such as the R software.
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Autorenporträt
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.