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.
Autorenporträt
I received my PhD in Mathematics from Carleton University's School of Mathematics and Statistics, Ottawa (Canada) in 1997. My specialization was the design and analysis of statistical surveys. In the past few years however, I devoted considerable time and energy to the field of inter-rater reliability analysis, in which I published several papers and books (for some of my works in this field see https://www.researchgate.net/profile/Kilem_Gwet). It is after successfully using principal components to analyze multivariate inter-rater reliability data that I first considered writing this book. I wanted a book that shows step by step how principal components are calculated, what they represent, how they must be used and what their limitations are. These are some of the reasons why I wrote this book, which I hope you will find useful.