David Freedman

This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.

Theory and Practice

Statistical Models

Statistics

Mendel, Inc

Estadística es, en la opinión de numerosos estadísticos y matemáticos, el mejor libro introductorio de estadística que se haya escrito en muchos años. En esta segunda edición, que ahora traducimos al castellano, los autores conservan el frescor y la intensidad de la primera edición, a la vez que actualizan los ejemplos y amplían la discusión de algunos temas puntuales. El libro está dirigido a estudiantes con escaso bagaje matemático. Pone el énfasis en la comprensión intuitiva, más que en la manipulación formal, y consigue convencer al estudiante de que la estadística, después de todo, no es una disciplina tan misteriosa. Por el entusiasmo con que los estudiantes responden a su adopción como libro de texto, por la selección de los ejemplos, por su inteligente planteamiento y por la claridad y corrección de sus explicaciones, Estadística se halla seguramente una o dos desviaciones típicas por encima de cualquier otro libro de texto. Traducción de Alicia Coduras y Toni Cuffí.

Estadística, 2ª ed.

Statistics$eDavid Freedman, Robert Pisani, Roger Purves

A long time ago I started writing a book about Markov chains, Brownian motion, and diffusion. I soon had two hundred pages of manuscript and my publisher was enthusiastic. Some years and several drafts later, I had a thousand pages of manuscript, and my publisher was less enthusiastic. So we made it a trilogy: Markov Chains Brownian Motion and Diffusion Approximating Countable Markov Chains familiarly - MC, B & D, and ACM. I wrote the first two books for beginning graduate students with some knowledge of probability; if you can follow Sections 10.4 to 10.9 of Markov Chains you're in. The first two books are quite independent of one another, and completely independent of the third. This last book is a monograph which explains one way to think about chains with instantaneous states. The results in it are supposed to be new, except where there are specific disclaim ers; it's written in the framework of Markov Chains. Most of the proofs in the trilogy are new, and I tried hard to make them explicit. The old ones were often elegant, but I seldom saw what made them go. With my own, I can sometimes show you why things work. And, as I will VB1 PREFACE argue in a minute, my demonstrations are easier technically. If I wrote them down well enough, you may come to agree.

Markov Chains

A long time ago I started writing a book about Markov chains, Brownian motion, and diffusion. I soon had two hundred pages of manuscript and my publisher was enthusiastic. Some years and several drafts later, I had a thousand pages of manuscript, and my publisher was less enthusiastic. So we made it a trilogy: Markov Chains Brownian Motion and Diffusion Approximating Countable Markov Chains familiarly - MC, B & D, and ACM. I wrote the first two books for beginning graduate students with some knowledge of probability; if you can follow Sections 10.4 to 10.9 of Markov Chains, you're in. The first two books are quite independent of one another, and completely independent of this one, which is a monograph explaining one way to think about chains with instantaneous states. The results here are supposed to be new, except when there are specific disclaimers. It's written in the framework of Markov chains; we wanted to reprint in this volume the MC chapters needed for reference. but this proved impossible. Most of the proofs in the trilogy are new, and I tried hard to make them explicit. The old ones were often elegant, but I seldom saw what made them go. With my own, I can sometimes show you why things work. And, as I will argue in a minute, my demonstrations are easier technically. If I wrote them down well enough, you may come to agree.

Approximating Countable Markov Chains

This book, part of a trilogy covering the field of Markov processes, provides a readable and constructive treatment of Markov chains. It contains some of the author's own research and many of the proofs are new. It includes material not usually available in textbooks, such as invariance principles for functionals of a Markov chain, Kolmogorov's inequality on the concentration function, the boundary, and the construction of a variety of continuous-time chains from their jump processes and holding times. (Author).

Harry Reichenbach

The Anatomy of Ballyhoo

Phantom Fame

Roger Purves

Renowned for its clear prose and no-nonsense emphasis on core concepts, Statistics covers fundamentals using real examples to illustrate the techniques.

Instructor's Manual

David Lane

A Workbook

Mathematical Methods in Statistics

Statistics teaches students how to think about statistical issues. It is written in clear, everyday language, without the equations that baffle non-mathematical readers. The techniques are all introduced through examples, showing how statistics has helped solve major problems in economics, education, genetics, medicine, physics, political science, psychology, and other fields.

Robert Pisani

Instructor's Manual for Statistics

A long time ago I started writing a book about Markov chains, Brownian motion, and diffusion. I soon had two hundred pages of manuscript and my publisher was enthusiastic. Some years and several drafts later, I had a thot:sand pages of manuscript, and my publisher was less enthusiastic. So we made it a trilogy: Markov Chains Brownian Motion and Diffusion Approximating Countable Markov Chains familiarly - Me, B & D, and ACM. I wrote the first two books for beginning graduate students with some knowledge of probability; if you can follow Sections 3.4 to 3.9 of Brownian Motion and Diffusion you're in. The first two books are quite independent of one another, and completely independent of the third. This last book is a monograph, which explains one way to think about chains with instantaneous states. The results in it are supposed to be new, except where there are spe cific disclaimers; it's written in the framework of Markov Chains. Most of the proofs in the trilogy are new, and I tried hard to make them explicit. The old ones were often elegant, but I seldom saw what made them go. With my own, I can sometimes show you why things work. And, as I will argue in a minute, my demonstrations are easier technically. If I wrote them down well enough, you may come to agree.

Brownian Motion and Diffusion

Terry P. Speed

Essays in Honor of David A. Freedman

Probability and Statistics

Statistics, 4/E

The Fourth Edition has been carefully revised and updated to reflect current data.

David Freedman

About

Books

Join the club