**Author**: Robert V. Hogg,Joeseph McKean,Allen T Craig

**Publisher:**Pearson Higher Ed

**ISBN:**1292037628

**Category:**Mathematics

**Page:**656

**View:**5256

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# Search Results for: introduction-to-mathematical-statistics-pearson-new-international-edition

**Author**: Robert V. Hogg,Joeseph McKean,Allen T Craig

**Publisher:** Pearson Higher Ed

**ISBN:** 1292037628

**Category:** Mathematics

**Page:** 656

**View:** 5256

Introduction to Mathematical Statistics, Seventh Edition, provides students with a comprehensive introduction to mathematical statistics. Continuing its proven approach, the Seventh Edition has been updated with new examples, exercises, and content for an even stronger presentation of the material.
*Pearson New International Edition*

**Author**: Robert V. Hogg,Allen T. Craig,Joseph W. McKean

**Publisher:** N.A

**ISBN:** 9781292024998

**Category:** Mathematical statistics

**Page:** 656

**View:** 1190

Introduction to Mathematical Statistics, Seventh Edition, provides students with a comprehensive introduction to mathematical statistics. Continuing its proven approach, the Seventh Edition has been updated with new examples, exercises, and content for an even stronger presentation of the material.

**Author**: Richard J. Larsen,Morris L. Marx

**Publisher:** Pearson

**ISBN:** 0134114248

**Category:** Mathematics

**Page:** 768

**View:** 2118

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For courses in Mathematical Statistics Introducing the principles of statistics and data modeling Introduction to Mathematical Statistics and Its Applications , 6th Edition is a high-level calculus student’s first exposure to mathematical statistics. This book provides students who have already taken three or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a two-semester course, the book touches on both statistics and experimental design, which teaches students various ways to analyze data. It gives computational-minded students a necessary and realistic exposure to identifying data models.

**Author**: Richard J. Larsen,Morris L. Marx

**Publisher:** Pearson Higher Ed

**ISBN:** 1292036729

**Category:** Mathematics

**Page:** 744

**View:** 813

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 theFifth 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.

**Author**: John A. Rice

**Publisher:** Cengage Learning

**ISBN:** 0534399428

**Category:** Mathematics

**Page:** 688

**View:** 1039

This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts that are set in abstract settings. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

**Author**: Robert V. Hogg,Elliot A. Tanis

**Publisher:** N.A

**ISBN:** 9781292024783

**Category:** Mathematical statistics

**Page:** 640

**View:** 1184

Written by two leading statisticians, this applied introduction to the mathematics of probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.

**Author**: Irwin Miller,Marylees Miller

**Publisher:** Pearson

**ISBN:** 0134291670

**Category:** Mathematics

**Page:** 544

**View:** 1435

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. John E. Freund's Mathematical Statistics with Applications , Eighth Edition, provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage that reflects the latest in statistical thinking, the teaching of statistics, and current practices.
*with Applications in R*

**Author**: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani

**Publisher:** Springer Science & Business Media

**ISBN:** 1461471389

**Category:** Mathematics

**Page:** 426

**View:** 8275

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
*Student solutions manual*

**Author**: Richard J. Larsen,Morris L. Marx

**Publisher:** N.A

**ISBN:** 9780130310156

**Category:** Mathematical statistics

**Page:** 111

**View:** 3449

*An Introduction to Likelihood Based Inference*

**Author**: Richard J. Rossi

**Publisher:** John Wiley & Sons

**ISBN:** 1118771168

**Category:** Mathematics

**Page:** 448

**View:** 1505

Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are uniquely based on the likelihood function This book addresses mathematical statistics for upper-undergraduates and first year graduate students, tying chapters on estimation, confidence intervals, hypothesis testing, and statistical models together to present a unifying focus on the likelihood function. It also emphasizes the important ideas in statistical modeling, such as sufficiency, exponential family distributions, and large sample properties. Mathematical Statistics: An Introduction to Likelihood Based Inference makes advanced topics accessible and understandable and covers many topics in more depth than typical mathematical statistics textbooks. It includes numerous examples, case studies, a large number of exercises ranging from drill and skill to extremely difficult problems, and many of the important theorems of mathematical statistics along with their proofs. In addition to the connected chapters mentioned above, Mathematical Statistics covers likelihood-based estimation, with emphasis on multidimensional parameter spaces and range dependent support. It also includes a chapter on confidence intervals, which contains examples of exact confidence intervals along with the standard large sample confidence intervals based on the MLE's and bootstrap confidence intervals. There’s also a chapter on parametric statistical models featuring sections on non-iid observations, linear regression, logistic regression, Poisson regression, and linear models. Prepares students with the tools needed to be successful in their future work in statistics data science Includes practical case studies including real-life data collected from Yellowstone National Park, the Donner party, and the Titanic voyage Emphasizes the important ideas to statistical modeling, such as sufficiency, exponential family distributions, and large sample properties Includes sections on Bayesian estimation and credible intervals Features examples, problems, and solutions Mathematical Statistics: An Introduction to Likelihood Based Inference is an ideal textbook for upper-undergraduate and graduate courses in probability, mathematical statistics, and/or statistical inference.

**Author**: Scott Hartshorn

**Publisher:** Lulu Press, Inc

**ISBN:** 1329854128

**Category:** Education

**Page:** N.A

**View:** 7821

Bayes theorem describes the probability of an event based on other information that might be relevant. Essentially, you are estimating a probability, but then updating that estimate based on other things that you know. This book is designed to give you an intuitive understanding of how to use Bayes Theorem. It starts with the definition of what Bayes Theorem is, but the focus of the book is on providing examples that you can follow and duplicate. Most of the examples are calculated in Excel, which is useful for updating probability if you have dozens or hundreds of data points to roll in.

**Author**: Simon Wood

**Publisher:** Cambridge University Press

**ISBN:** 1107071054

**Category:** Business & Economics

**Page:** 258

**View:** 9354

Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

**Author**: Jun Shao

**Publisher:** Springer Science & Business Media

**ISBN:** 0387282769

**Category:** Mathematics

**Page:** 360

**View:** 573

The exercises are grouped into seven chapters with titles matching those in the author's Mathematical Statistics. Can also be used as a stand-alone because exercises and solutions are comprehensible independently of their source, and notation and terminology are explained in the front of the book. Suitable for self-study for a statistics Ph.D. qualifying exam.

**Author**: Elliot A. Tanis,Robert V. Hogg

**Publisher:** Prentice Hall

**ISBN:** N.A

**Category:** Mathematics

**Page:** 359

**View:** 6069

This innovative new introduction to Mathematical Statistics covers the important concept of estimation at a point much earlier (Chapter 2) than others on this subject. Applies mathematical statistics to topics such as insurance, Pap smear tests, estimating the number of whales in an ocean, fitting models, filling 12 ounce containers, environmental issues, and results in certain sporting events. Includes summaries of the most important aspects of discrete distributions, continuous distributions, confidence intervals, and tests of hypotheses. Provides computer applications for data analysis and also for theoretical solutions such as simulation and bootstrapping. A comprehensive reference for individuals who need to brush up on their knowledge of statistics.

**Author**: William Wade,W. R. Wade

**Publisher:** Math Classics

**ISBN:** 9780134707624

**Category:** Mathematics

**Page:** 696

**View:** 2046

Originally published in 2010, reissued as part of Pearson's modern classic series.
*Becoming a Psychological Detective*

**Author**: Stephen F. Davis,Randolph A. Smith

**Publisher:** Prentice Hall

**ISBN:** 9780131505117

**Category:** Psychology

**Page:** 610

**View:** 6332

Using student research projects and drawing parallels with detective work, "An Introduction to Research Methods and Statistics" engages the reader and encourages active involvement. The authors use a lively, conversational tone that makes the material accessible and inviting. This text also provides special pedagogical features to facilitate learning.
*Decision Making and Analysis*

**Author**: Robert A. Stine,Dean P. Foster

**Publisher:** Pearson

**ISBN:** 9780134497167

**Category:** Business & Economics

**Page:** 912

**View:** 6629

For one- and two-semester courses in introductory business statistics. Understand Business. Understand Data. The 3rd Edition of Statistics for Business: Decision Making and Analysis emphasizes an application-based approach, in which readers learn how to work with data to make decisions. In this contemporary presentation of business statistics, readers learn how to approach business decisions through a 4M Analytics decision making strategy-motivation, method, mechanics and message-to better understand how a business context motivates the statistical process and how the results inform a course of action. Each chapter includes hints on using Excel, Minitab Express, and JMP for calculations, pointing the reader in the right direction to get started with analysis of data. Also available with MyLab Statistics MyLab(tm) Statistics from Pearson is the world's leading online resource for teaching and learning statistics; it integrates interactive homework, assessment, and media in a flexible, easy-to-use format. MyLab Statistics is a course management system that helps individual students succeed. It provides engaging experiences that personalize, stimulate, and measure learning for each student. Tools are embedded to make it easy to integrate statistical software into the course. Note: You are purchasing a standalone product; MyLab(tm)does not come packaged with this content. Students, if interested in purchasing this title with MyLab, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab, search for: 013450867X / 9780134508672 Statistics for Business: Decision Making and Analysis Plus MyLab Statistics with Pearson eText Package consists of: 0134497163 / 9780134497167 Statistics for Business: Decision Making and Analysis 032192147X / 9780321921475 MyLab Statistics for Business Statistics -- Glue-In Access Card 0321929713 / 9780321929716 MyLab Statistics for Business Statistics Sticker

**Author**: Morris H. DeGroot,Mark J. Schervish

**Publisher:** Pearson College Division

**ISBN:** 9780321500465

**Category:** Mathematics

**Page:** 893

**View:** 4814

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.

**Author**: Morris H. DeGroot,Mark J. Schervish

**Publisher:** Pearson Higher Ed

**ISBN:** 1292037679

**Category:** Mathematics

**Page:** 848

**View:** 8267

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Probability & Statistics, Fourth Edition, was written for a one- or two-semester probability and statistics course. This course is offered primarily at four-year institutions and taken mostly by sophomore and junior level students majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.

**Author**: Dennis D. Wackerly,William Mendenhall,Richard L. Scheaffer

**Publisher:** Cengage Learning

**ISBN:** 9780495385080

**Category:** Matematisk statistik

**Page:** 912

**View:** 2983

The authors present the theory of statistics in the context of practical problem solving and real world applications. This practical approach helps you discover the nature of statistics and comprehend its essential role in scientific research.--

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