Analysis of Variance; Design; and Regression: Linear Modeling for Unbalanced Data (2nd Edition) eBook

Specifications

Book Description

(PDF) presents linear structures for modeling data with a focus on how to include specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book is titled Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, and it is in its second edition. It is available for download. The ebook performs a careful analysis on a limited number of data sets by utilizing technologies that are easily scalable to a greater amount of data. The tools can also be used with smaller relevant data sets that are derived from larger data sets.

What's New in the Second Edition

• Analyses of split plots that lack balance
• Examination of factors that are homologous
• Generalized linear models with further extensions
• Reorganized with a primary emphasis on skewed data
• The concepts of nonparametric and lasso regression are broken down here.
• On the author's website, you may find the code for R, Minitab®, and SAS.
• The general additive model and the generalized additive model are both introduced here.
• Analyses that were previously balanced were reworked using methodologies for data that was not balanced.

The book can be utilized in a variety of classes, such as an advanced course in analysis of variance (ANOVA) or data analysis for upper-division statistics students, as well as a yearlong graduate course on regression for students and graduate students in other subjects. When working with unbalanced data, it lays a significant emphasis on correctly comprehending the diverse range of computer output that is presented.

Reviews

“… written in a straightforward and understandable manner… a fantastic choice for a statistical methods textbook aimed at graduate students beginning their studies… a useful resource for people working in the field.” ? Zentralblatt für Mathematik

Because this book is primarily intended for students, it contains illustrated examples and activities in each chapter. The fact that it provides traditional tools for future approaches in the big data sector is the most important aspect of this ebook. According to the author, “the machine learning techniques are instantly founded on the fundamental statistical procedures.” ? Marina Gorunescu (Craiova)

NOTE: This purchase comes with a PDF version of the booklet “Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data,” which is the second edition of the book. There are no access codes contained within.