Introduction to Bayesian Scientific Computing: Ten Lectures on Subjective Computing (Surveys and Tutorials in the Applied Mathematical Sciences)
This book has been written for undergraduate and graduate students in various disciplines of mathematics. The authors, internationally recognized experts in their field, have developed a superior teaching and learning tool that makes it easy to grasp new concepts and apply them in practice. The book’s highly accessible approach makes it particularly ideal if you want to become acquainted with the Bayesian approach to computational science, but do not need to be fully immersed in detailed statistical analysis.
The concept of user stories has its roots as one of the main tenets of Extreme Programming. In simple terms, user stories represent an effective means of gathering requirements from the customer (roughly akin to use cases). This book describes user stories and demonstrates how they can be used to properly plan, manage, and test software development projects. The book highlights both successful and unsuccessful implementations of the concept, and provides sets of questions and exercises that drive home its main points. After absorbing the lessons in this book, readers will be able to introduce user stories in their organizations as an effective means of determining precisely what is required of a software application.
Real-world problems and data sets are the backbone of this book, which provides a unique approach to the topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information about mixed effects models, applications of the MIXED procedure, regression diagnostics with the corresponding IML procedure code, and covariance structures. The authors’ approach to the information will aid professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding high-resolution output accompany sample problems, and clear explanations of SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples.