Böcker av Kilem Li Gwet

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.

This book presents basic statistical concepts, and methods with a particular emphasis on their meaning, and practicality in real life. Many introductory statistics texts do not provide the practical motivations behind the techniques, nor the reasons why the techniques were formulated the way they are. With the specific approach used in this book, the motive behind the statistical concepts and methods being described is put forward. The main purpose of the methods will be kept before the reader, and used as often as needed to justify each step taken. A particular effort is made towards reconciling statistical logic and common sense, with the objective of gaining insight into the real value of the statistical solution.