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Introduction to Mathematical Statistics, Fifth Edition

Introduction to Mathematical Statistics, Fifth Edition PDF Author: Robert V. Hogg
Publisher:
ISBN: 9780132089357
Category : Mathematical statistics
Languages : en
Pages : 88

Book Description


Introduction to Mathematical Statistics, Fifth Edition

Introduction to Mathematical Statistics, Fifth Edition PDF Author: Robert V. Hogg
Publisher:
ISBN: 9780132089357
Category : Mathematical statistics
Languages : en
Pages : 88

Book Description


Introduction to Mathematical Statistics and Its Applications

Introduction to Mathematical Statistics and Its Applications PDF Author: Richard J. Larsen
Publisher: Pearson Higher Ed
ISBN: 1292036729
Category : Mathematics
Languages : en
Pages : 741

Book Description
Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout the 5th Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

Introduction to Mathematical Statistics

Introduction to Mathematical Statistics PDF Author: Robert V. Hogg
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 584

Book Description
The fifth edition of text offers a careful presentation of the probability needed for mathematical statistics and the mathematics of statistical inference. Offering a background for those who wish to go on to study statistical applications or more advanced theory, this text presents a thorough treatment of the mathematics of statistics.

Introduction to Mathematical Statistics

Introduction to Mathematical Statistics PDF Author: Paul G. Hoel
Publisher:
ISBN: 9780471403685
Category : Mathematical statistics
Languages : en
Pages : 409

Book Description
Probability; Nature of statistical methods; Empirical frequency distributions of one variable; Theoretical frequency distributions of one variable; Elementary sampling theory for one variable; Correlation and regression; Theoretical frequency distributions for correlation and regression; General principles for testing hypotheses and for estimation; Testing goodness of fit; Small sample distributions; Statistical design in experiments; Nonparametric methods.

Introduction to Probability and Statistics for Engineers and Scientists

Introduction to Probability and Statistics for Engineers and Scientists PDF Author: Sheldon M. Ross
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 532

Book Description
Elements of probability; Random variables and expectation; Special; random variables; Sampling; Parameter estimation; Hypothesis testing; Regression; Analysis of variance; Goodness of fit and nonparametric testing; Life testing; Quality control; Simulation.

Mathematical Statistics with Applications in R

Mathematical Statistics with Applications in R PDF Author: Kandethody M. Ramachandran
Publisher: Elsevier
ISBN: 012417132X
Category : Mathematics
Languages : en
Pages : 826

Book Description
Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

Loss Models

Loss Models PDF Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 0470391332
Category : Business & Economics
Languages : en
Pages : 758

Book Description
An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.

Introduction to Mathematical Logic

Introduction to Mathematical Logic PDF Author: Elliot Mendelsohn
Publisher: Springer Science & Business Media
ISBN: 1461572886
Category : Science
Languages : en
Pages : 351

Book Description
This is a compact mtroduction to some of the pnncipal tOpICS of mathematical logic . In the belief that beginners should be exposed to the most natural and easiest proofs, I have used free-swinging set-theoretic methods. The significance of a demand for constructive proofs can be evaluated only after a certain amount of experience with mathematical logic has been obtained. If we are to be expelled from "Cantor's paradise" (as nonconstructive set theory was called by Hilbert), at least we should know what we are missing. The major changes in this new edition are the following. (1) In Chapter 5, Effective Computability, Turing-computabIlity IS now the central notion, and diagrams (flow-charts) are used to construct Turing machines. There are also treatments of Markov algorithms, Herbrand-Godel-computability, register machines, and random access machines. Recursion theory is gone into a little more deeply, including the s-m-n theorem, the recursion theorem, and Rice's Theorem. (2) The proofs of the Incompleteness Theorems are now based upon the Diagonalization Lemma. Lob's Theorem and its connection with Godel's Second Theorem are also studied. (3) In Chapter 2, Quantification Theory, Henkin's proof of the completeness theorem has been postponed until the reader has gained more experience in proof techniques. The exposition of the proof itself has been improved by breaking it down into smaller pieces and using the notion of a scapegoat theory. There is also an entirely new section on semantic trees.

An Introduction to Mathematical Statistics and Its Applications

An Introduction to Mathematical Statistics and Its Applications PDF Author: Richard J. Larsen
Publisher: Pearson
ISBN: 9780321693945
Category : Mathematical statistics
Languages : en
Pages : 0

Book Description
Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout the Fifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice.

Probability

Probability PDF Author: Rick Durrett
Publisher: Cambridge University Press
ISBN: 113949113X
Category : Mathematics
Languages : en
Pages :

Book Description
This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The fourth edition begins with a short chapter on measure theory to orient readers new to the subject.