Applied Regression Analysis (Wiley Series in Probability and Statistics Book 326) 3rd Edition by Norman R. Draper (PDF)

Description

An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among variables. This classic text, with its emphasis on clear, thorough presentation of concepts and applications, offers a complete, easily accessible introduction to the fundamentals of regression analysis. Assuming only a basic knowledge of elementary statistics, Applied Regression Analysis, Third Edition focuses on the fitting and checking of both linear and nonlinear regression models, using small and large data sets, with pocket calculators or computers. This Third Edition features separate chapters on multicollinearity, generalized linear models, mixture ingredients, geometry of regression, robust regression, and resampling procedures. Extensive support materials include sets of carefully designed exercises with full or partial solutions and a series of true/false questions with answers. All data sets used in both the text and the exercises can be found on the companion disk at the back of the book. For analysts, researchers, and students in university, industrial, and government courses on regression, this text is an excellent introduction to the subject and an efficient means of learning how to use a valuable analytical tool. It will also prove an invaluable reference resource for applied scientists and statisticians.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐I used this book as a reference for an advanced statistics for finance class that I took. Applied Regression has a really good balance between the theoretical foundation of least squares and the application. The introduction to the linear algebra of least squares is particularly gentle. The authors introduce all of the linear algebra that you’ll need to know. They also provide some background for least squares as a mapping into the column space of X. But the theory never becomes over whelming.As the title suggests, the book is about regression analysis. In addition to multivariate least squares, the book covers advanced linear regression topics like ridge regression.The book could be criticized for being dated in that it does not give examples in R or Matlab. However, the material that is covered is timeless. Regardless of the mathematics software you use, the foundation is the same and this book provides a good in-depth introduction to the regression analysis.A good complement to this book (which I also used in my advanced statistics class) is

⭐which shows how to build most of the models discussed Applied Regression in R.

⭐Nice product

⭐Fantastic! Excellent book! Excellent seller!!!

⭐I am really surprised that this book shipped from India was of really good quality, the paper is white, solid and thick, the book was brand new.Highly recommend this place!

⭐nice little review of linear algebra and good into to matrix-based regression in ch 4

⭐I received a book from India; what is pictured was not the book I received. The content of the book from India is different than the content printed in the U.S. so right now I am out $30 for nothing.

⭐Is a kind of book nice to have because review all topics in regresión and plus, Furthermore a great examples are used

⭐Very good product

⭐The book is a great asset to improve knowledge about regression analysis, specially for students. I personally recommend it to all applied biology and life science students.

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