This book introduces you to the world of data science. It reveals the proper way to do data science. It covers essential statistical and programming techniques to help you understand data science from a broad perspective. Not only that, but it provides a theoretical, technical, and mathematical foundation for problem-solving using data...

Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems. Introducing...

Google Analytics is a free tool used by millions of Web site owners across the globe to track how visitors interact with their Web sites, where they arrive from, and which visitors drive the most revenue and sales...

Neural Networks, Second Edition provides a complete introduction to neural networks. It describes what they are, what they can do, and how they do it. While some scientific background is assumed, the reader is not expected to have any prior knowledge of neural networks. These networks are explained and discussed by means of examples, so that...

This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is...

When I began writing this book, I spent quite a bit of time searching for a good quote to start things off. I ended up with two. R is a wonderfully flexible platform and language for exploring, visualizing, and understanding data. I chose the quote from Alice in Wonderland to capture the flavor of statistical analysis today—an...

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)―classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is...