The Best Probability & Statistics Mathematics Books 2024

1. Statistics: An Introduction Using R (Paperback) by Michael J Crawley

9780470022986. New condition. Trade paperback. Language: English. Pages: 342. Trade paperback (US). Glued binding. 342 p. Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the authora s previous best--selling title Statistical Computing. aeo Features step--by--step instructions that assume no mathematics, statistics or programming background, helping the non--statistician to fully understand the methodology. aeo Uses a series of realistic examples, developing step--wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. aeo The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. aeo Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. aeo Includes numerous worked examples and exercises within each chapter. aeo Accompanied by a website featuring worked examples, data sets, exercises and solutions: ... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology -- but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

ISBN: 9780470022986 Condition: New Trade paperback Language: English Pages: 342 Trade paperback (US). Glued binding. 342 p. Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the authora s previous best--selling title Statistical Computing. aeo Features step--by--step instructions that assume no mathematics, statistics or programming background, helping the non--statistician to fully understand the methodology. aeo Uses a series of realistic examples, developing step--wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. aeo The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. aeo Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. aeo Includes numerous worked examples and exercises within each chapter. aeo Accompanied by a website featuring worked examples, data sets, exercises and solutions: ... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology -- but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

2. Decision Making under Uncertainty with RISKOptimizer : A Step-to-Step Guide Using Palisade's RISKOptimizer for Excellence 9781893281011

ISBN: 9781893281011 ISBN10: 1893281019 Contributors: Winston, Wayne L.,

Decision Making under Uncertainty with RISKOptimizer : A Step-to-Step Guide Using Palisade's RISKOptimizer for Excellence 9781893281011

3. Dover Books on Mathematics: Probability Theory (Paperback)

This introductory text features well-chosen problems and exercises that illustrate the algebras of events, discrete random variables, characteristic functions, and limit theorems. Prerequisites include knowledge of differential and integral calculus as well as the theory of real and complex functions. An extensive appendix introduces information theory. 1970 edition.

The founder of Hungary's Probability Theory School, A. Rényi made significant contributions to virtually every area of mathematics. This introductory text is the product of his extensive teaching experience and is geared toward readers who wish to learn the basics of probability theory, as well as those who wish to attain a thorough knowledge in the field. Based on the author's lectures at the University of Budapest, this text requires no preliminary knowledge of probability theory. Readers should, however, be familiar with other branches of mathematics, including a thorough understanding of the elements of the differential and integral calculus and the theory of real and complex functions. These well-chosen problems and exercises illustrate the algebras of events, discrete random variables, characteristic functions, and limit theorems. The text concludes with an extensive appendix that introduces information theory.