Download or read book Elementary Probability Models and Statistical Inference written by Douglas George Chapman and published by . This book was released on 1970 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete random variables and probability models; The binomial probability model; Point estimation and hypothesis testing for the binomial distribution; Random sampling, sampling distributions, summarization of data, and estimation of parameters; Continuous distributions, the normal probability model, and approximations; point estimation and hypothesis testing for the mean of a normal population; Confidence intervals; Joint probability models; Regression and correlation; Chi-square tests; Nonparametric tests.
Download or read book Instructor s Manual for Elementary Probability Models and Statistical Inference written by Douglas George Chapman and published by . This book was released on 1970 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Probability and Statistical Inference written by Miltiadis C. Mavrakakis and published by CRC Press. This book was released on 2021-03-28 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without sacrificing mathematical rigour, bridging the gap between the many excellent introductory books and the more advanced, graduate-level texts. The book introduces and explores techniques that are relevant to modern practitioners, while being respectful to the history of statistical inference. It seeks to provide a thorough grounding in both the theory and application of statistics, with even the more abstract parts placed in the context of a practical setting. Features: •Complete introduction to mathematical probability, random variables, and distribution theory. •Concise but broad account of statistical modelling, covering topics such as generalised linear models, survival analysis, time series, and random processes. •Extensive discussion of the key concepts in classical statistics (point estimation, interval estimation, hypothesis testing) and the main techniques in likelihood-based inference. •Detailed introduction to Bayesian statistics and associated topics. •Practical illustration of some of the main computational methods used in modern statistical inference (simulation, boostrap, MCMC). This book is for students who have already completed a first course in probability and statistics, and now wish to deepen and broaden their understanding of the subject. It can serve as a foundation for advanced undergraduate or postgraduate courses. Our aim is to challenge and excite the more mathematically able students, while providing explanations of statistical concepts that are more detailed and approachable than those in advanced texts. This book is also useful for data scientists, researchers, and other applied practitioners who want to understand the theory behind the statistical methods used in their fields.
Download or read book Elementary Probability Models and Statistical Inference by Douglas G Chapman and Ronald A Schaufele written by Douglas George Chapman and published by . This book was released on 1970 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A First Course in Probability Models and Statistical Inference written by James H.C. Creighton and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to new territory: A course in probability models and statistical inference. The concept of probability is not new to you of course. You've encountered it since childhood in games of chance-card games, for example, or games with dice or coins. And you know about the "90% chance of rain" from weather reports. But once you get beyond simple expressions of probability into more subtle analysis, it's new territory. And very foreign territory it is. You must have encountered reports of statistical results in voter sur veys, opinion polls, and other such studies, but how are conclusions from those studies obtained? How can you interview just a few voters the day before an election and still determine fairly closely how HUN DREDS of THOUSANDS of voters will vote? That's statistics. You'll find it very interesting during this first course to see how a properly designed statistical study can achieve so much knowledge from such drastically incomplete information. It really is possible-statistics works! But HOW does it work? By the end of this course you'll have understood that and much more. Welcome to the enchanted forest.
Download or read book Probability Theory and Statistical Inference written by Aris Spanos and published by Cambridge University Press. This book was released on 2019-09-19 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
Download or read book Probability Theory and Statistical Inference written by Aris Spanos and published by Cambridge University Press. This book was released on 1999-09-02 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt: This major new textbook is intended for students taking introductory courses in Probability Theory and Statistical Inference. The primary objective of this book is to establish the framework for the empirical modelling of observational (non-experimental) data. The text is extremely student-friendly, with pathways designed for semester usage, and although aimed primarily at students at second-year undergraduate level and above studying econometrics and economics, Probability Theory and Statistical Inference will also be useful for students in other disciplines which make extensive use of observational data, including Finance, Biology, Sociology and Psychology.
Download or read book Probability and Statistical Inference written by J.G. Kalbfleisch and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: A carefully written text, suitable as an introductory course for second or third year students. The main scope of the text guides students towards a critical understanding and handling of data sets together with the ensuing testing of hypotheses. This approach distinguishes it from many other texts using statistical decision theory as their underlying philosophy. This volume covers concepts from probability theory, backed by numerous problems with selected answers.
Download or read book Modelling Inference and Data Analysis written by Miltiadis C. Mavrakakis and published by Chapman and Hall/CRC. This book was released on 2014-12-15 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling, Inference and Data Analysis brings together key topics in mathematical statistics and presents them in a rigorous yet accessible manner. It covers aspects of probability, distribution theory and random processes that are fundamental to a proper understanding of inference. The book also discusses the properties of estimators constructed from a random sample of ends, with sections on methods for estimating parameters in time series models and computationally intensive inferential techniques. The text challenges and excites the more mathematically able students while providing an approachable explanation of advanced statistical concepts for students who struggle with existing texts.
Download or read book Models for Probability and Statistical Inference written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.
Download or read book Statistical Inference written by George Casella and published by CRC Press. This book was released on 2024-05-23 with total page 1746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.
Download or read book Probability and Statistical Inference written by J. G. Kalbfleisch and published by Springer. This book was released on 1979-12-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended as a text for an introductory course in probability and statistics at the second or third year university level. It emphasizes applications and logical principles rather than mathematical theory. A good background in freshman calcuius is suf ficient for most of the material presented. The book is in two parts. The first part (Chapters 1 - 8) deals with probability models and with mathematical methods for hand ling them. in the second part (Chapters 9 - 16), probability models are used as the basis for the analysis and interpretation of data. Several starred sections have been included as supplementary material. A large supply of practice problems is provided, and Appendix A con tains answers to about one-third of these. Computers and sophisticated pocket calculators are having a profound effect on statistical practice. Not only can the same ari thmetic be done in a fraction of the time, but more importantly, statistical methods which were previously not feasible because of the amount of calculation required now present no difficulties. In par ticular, the likelihood function itself and procedures closely related to it now give simple and immediate solutions to problems which twenty years ago would have required complicated approximate solutions of doubtful accuracy. One reason for writing this book was to draw at tention to these useful methods.
Download or read book Probably Not written by Lawrence N. Dworsky and published by John Wiley & Sons. This book was released on 2019-09-04 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A revised edition that explores random numbers, probability, and statistical inference at an introductory mathematical level Written in an engaging and entertaining manner, the revised and updated second edition of Probably Not continues to offer an informative guide to probability and prediction. The expanded second edition contains problem and solution sets. In addition, the book’s illustrative examples reveal how we are living in a statistical world, what we can expect, what we really know based upon the information at hand and explains when we only think we know something. The author introduces the principles of probability and explains probability distribution functions. The book covers combined and conditional probabilities and contains a new section on Bayes Theorem and Bayesian Statistics, which features some simple examples including the Presecutor’s Paradox, and Bayesian vs. Frequentist thinking about statistics. New to this edition is a chapter on Benford’s Law that explores measuring the compliance and financial fraud detection using Benford’s Law. This book: Contains relevant mathematics and examples that demonstrate how to use the concepts presented Features a new chapter on Benford’s Law that explains why we find Benford’s law upheld in so many, but not all, natural situations Presents updated Life insurance tables Contains updates on the Gantt Chart example that further develops the discussion of random events Offers a companion site featuring solutions to the problem sets within the book Written for mathematics and statistics students and professionals, the updated edition of Probably Not: Future Prediction Using Probability and Statistical Inference, Second Edition combines the mathematics of probability with real-world examples. LAWRENCE N. DWORSKY, PhD, is a retired Vice President of the Technical Staff and Director of Motorola’s Components Research Laboratory in Schaumburg, Illinois, USA. He is the author of Introduction to Numerical Electrostatics Using MATLAB from Wiley.
Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Download or read book An Introduction to Probability and Statistical Inference written by George G. Roussas and published by Academic Press. This book was released on 2014-09-25 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability models, statistical methods, and the information to be gained from them is vital for work in business, engineering, sciences (including social and behavioral), and other fields. Data must be properly collected, analyzed and interpreted in order for the results to be used with confidence. Award-winning author George Roussas introduces readers with no prior knowledge in probability or statistics to a thinking process to guide them toward the best solution to a posed question or situation. An Introduction to Probability and Statistical Inference provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. Content, examples, an enhanced number of exercises, and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities Reorganized material in the statistical portion of the book to ensure continuity and enhance understanding A relatively rigorous, yet accessible and always within the prescribed prerequisites, mathematical discussion of probability theory and statistical inference important to students in a broad variety of disciplines Relevant proofs where appropriate in each section, followed by exercises with useful clues to their solutions Brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises available to instructors in an Answers Manual
Download or read book Elementary Probability Models and Statisical Infer Ence written by Chapman and published by . This book was released on 1970-06-01 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A First Course in Probability Models and Statistical Inference written by and published by Springer. This book was released on 2012-11-05 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt:
