Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners. As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software. This book is part of the SAS Press program.
This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques.
Written for data analysts working in all industries, graduate students, and consultants, Statistical Programming with SAS/IML Software includes numerous code snippets and more than 100 graphs. This book is part of the SAS Press program.
Data Management, Statistical Analysis, and Graphics, Second Edition Ken Kleinman, Nicholas J. Horton ... Pace 1. NA NA O. OO O : OO : OO 2. 73 O : 21 : 56 1316 2. 69 O : 22 : 17 Average. Pace . . secs. Climb . . feet. Calories 1.
The book suggests codes that are easy to understand, so they can be replicated or adapted for other purposes. As such, this book provides a great resource for people with beginner to intermediate knowledge in SAS.
This book also explains how to write R code directly in the SAS code editor for seamless integration between the two tools.
Applied mixed models in medicine, 3rd ed., Statistics in Practice, Wiley, Hoboken, NJ. Carlin, Bradley P. and Thomas A. Louis. 2000. Empirical bayes: Past, present and future, Journal of the American Statistical Association 95, no.
This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
This book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP.
This book also features recommendations from clinical trial experts and a discussion of relevant regulatory guidelines.
This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the ...