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Showing: 1-10 results of 6511

NOTE - This is a stand-alone book. Intended primarily for undergraduate courses in business statistics, this text also provides practical content to current and aspiring industry professionals.   Reducing the emphasis on doing computations, this practical text thoroughly integrates Microsoft Excel as a tool for analysis and presents statistical concepts in the context of the functional areas of business.

This book introduces the reader to the field of multiobjective optimization through problems with simple structures, namely those in which the objective function and constraints are linear. Fundamental notions as well as state-of-the-art advances are presented in a comprehensive way and illustrated with the help of numerous examples. Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided... more...

Designed for a one-semester advanced undergraduate or graduate course, Statistical Theory: A Concise Introduction clearly explains the underlying ideas and principles of major statistical concepts, including parameter estimation, confidence intervals, hypothesis testing, asymptotic analysis, Bayesian inference, and elements of decision theory. It introduces these topics on a clear intuitive level using illustrative examples in addition... more...

For courses in Introductory Statistics   Real data brings statistics to life From opinion polls and clinical trials to self-driving cars, statistics influences and shapes the world around us. Best-selling author Marty Triola is committed to keeping Elementary Statistics relentlessly current--with an unprecedented amount of up-to-the-minute real data--so that readers of all backgrounds understand the role of statistics in... more...

This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and... more...


Knowledge of statistics is essential in modern biology and medicine. Biologists and health professionals learn statistics best with real and interesting examples. The Analysis of Biological Data, Second Edition, by Whitlock and Schluter, teaches modern methods of statistics through the use of fascinating biological and medical cases. Readers consistently praise its clear and engaging writing and practical perspective. The second... more...

Everyone knows some of the basics of probability, perhaps enough to play cards. Beyond the introductory ideas, there are many wonderful results that are unfamiliar to the layman, but which are well within our grasp to understand and appreciate. Some of the most remarkable results in probability are those that are related to limit theorems--statements about what happens when the trial is repeated many times. The most famous of these is the Law of Large... more...

This is a revised version of  the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed at Lancaster, for use in the MatlabTM software environment (see Appendix G). Consequently, the present version... more...

Oehlert's text is suitable for either a service course for non-statistics graduate students or for statistics majors.  Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert's new book offers a superb balance of both analysis and design, presenting three practical themes to students: • when to use various designs • how to analyze the results • how to recognize... more...

C. Doleans-Dade: Stochastic processes and stochastic differential equations.- A. Friedman: Stochastic differential equations and applications.- D.W. Stroock, S.R.S. Varadhan: Theory of diffusion processes.- G.C. Papanicolaou: Wave propagation and heat conduction in a random medium.- C. Dewitt Morette: A stochastic problem in Physics.- G.S. Goodman: The embedding problem for stochastic matrices.