Books like Sampling methods by Pascal Ardilly

A practical guide to Bayesian statistical analysis that prioritizes computation, model checking, and data‑collection design, with examples spanning regression, hierarchical, robust, generalized linear, and mixture models.

Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of these simulation techniques, with incorporation of the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation. There are five completely new chapters that cover Monte Carlo control, reversible jump, slice sampling, sequential Monte Carlo, and perfect sampling. There is a more in-depth coverage of Gibbs sampling, which is now contained in three consecutive chapters. The development of Gibbs sampling starts with slice sampling and its connection with the fundamental theorem of simulation, and builds up to two-stage Gibbs sampling and its theoretical properties. A third chapter covers the multi-stage Gibbs sampler and its variety of applications. Lastly, chapters from the previous edition have been revised towards easier access, with the examples getting more detailed coverage. This textbook is intended for a second year graduate course, but will also be useful to someone who either wants to apply simulation techniques for the resolution of practical problems or wishes to grasp the fundamental principles behind those methods. The authors do not assume familiarity with Monte Carlo techniques (such as random variable generation), with computer programming, or with any Markov chain theory (the necessary concepts are developed in Chapter 6). A solutions manual, which covers approximately 40% of the problems, is available for instructors who require the book for a course. --back cover

A step-by-step guide to qualitative research methods and analysis for researchers and students in the social sciences, providing practical advice and technical expertise in understanding and interpreting qualitative data.

A step-by-step guide for anyone challenged by the many subtleties of sampling particulate materials. The only comprehensive document merging the famous works of P. Gy, I. Visman, and C.O. Ingamells into a single theory in a logical way - the most advanced book on sampling that can be used by all sampling practitioners around the world.

Intended for students who want to learn sampling theory at an intermediate level, and for research workers who need to be familiar with the developments in the subject. Can also serve as a reference work for the practicing statistician.

Applied Statistics is a comprehensive textbook that teaches statistical methods for economics, management, and social science applications, featuring exercises and problem sets for practical learning.