**K. S. Krishnamoorthi, V. Ram Krishnamoorthi, Arunkumar Pennathur**

September 14, 2018

The third edition of this textbook improves on the strengths of the earlier editions both in content and presentation. Of the important features of the textbook is the inclusion of examples from real-world to illustrate use of quality methods in problem solving. A thorough revision is made of the...

**Saeed Ghahramani**

September 04, 2018

"The 4th edition of Ghahramani's book is replete with intriguing historical notes, insightful comments, and well-selected examples/exercises that, together, capture much of the essence of probability. Along with its Companion Website, the book is suitable as a primary resource for a first course in...

**Yihui Xie, J.J. Allaire, Garrett Grolemund**

July 17, 2018

R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive...

**Ambrose Lo**

June 27, 2018

The proliferation of financial derivatives over the past decades, options in particular, has underscored the increasing importance of derivative pricing literacy among students, researchers, and practitioners. Derivative Pricing: A Problem-Based Primer demystifies the essential derivative pricing...

**Kevin J. Keen**

May 18, 2018

Praise for the First Edition "The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is...

**Annette J. Dobson, Adrian G. Barnett**

April 13, 2018

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection,...

**Ronald K. Pearson**

April 06, 2018

Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to...

**David A. Harville**

March 13, 2018

Linear Models and the Relevant Distributions and Matrix Algebra provides in-depth and detailed coverage of the use of linear statistical models as a basis for parametric and predictive inference. It can be a valuable reference, a primary or secondary text in a graduate-level course on linear models...

**Marcello Pagano, Kimberlee Gauvreau**

February 16, 2018

This edition is a reprint of the second edition published in 2000 by Brooks/Cole and then Cengage Learning. Principles of Biostatistics is aimed at students in the biological and health sciences who wish to learn modern research methods. It is based on a required course offered at the Harvard...

**Max Vercruyssen, Hal W. Hendrick**

February 05, 2018

Now in its fourth edition, Behavioral Research and Analysis: An Introduction to Statistics within the Context of Experimental Design presents an overview of statistical methods within the context of experimental design. It covers fundamental topics such as data collection, data analysis,...

**Athanasios Christou Micheas**

January 24, 2018

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks;...

**William M. Mendenhall, Terry L. Sincich**

November 28, 2017

This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitably, once these students graduate and are employed, they will be involved in the collection and analysis of data and will be required to think...