Probability And Statistics By Example Basic Probability And Statistics PDF Download
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Author | : Yu. M. Suhov |
Publisher | : Cambridge University Press |
Total Pages | : 477 |
Release | : 2014-09-22 |
Genre | : Mathematics |
ISBN | : 1107603587 |
Download Probability and Statistics by Example Book in PDF, ePub and Kindle
A valuable resource for students and teachers alike, this second edition contains more than 200 worked examples and exam questions.
Author | : F.M. Dekking |
Publisher | : Springer Science & Business Media |
Total Pages | : 485 |
Release | : 2006-03-30 |
Genre | : Mathematics |
ISBN | : 1846281687 |
Download A Modern Introduction to Probability and Statistics Book in PDF, ePub and Kindle
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books
Author | : Yuri Suhov |
Publisher | : Cambridge University Press |
Total Pages | : 477 |
Release | : 2014-09-22 |
Genre | : Mathematics |
ISBN | : 1316062201 |
Download Probability and Statistics by Example: Volume 1, Basic Probability and Statistics Book in PDF, ePub and Kindle
Probability and statistics are as much about intuition and problem solving as they are about theorem proving. Consequently, students can find it very difficult to make a successful transition from lectures to examinations to practice because the problems involved can vary so much in nature. Since the subject is critical in so many applications from insurance to telecommunications to bioinformatics, the authors have collected more than 200 worked examples and examination questions with complete solutions to help students develop a deep understanding of the subject rather than a superficial knowledge of sophisticated theories. With amusing stories and historical asides sprinkled throughout, this enjoyable book will leave students better equipped to solve problems in practice and under exam conditions.
Author | : Joseph Lawson Hodges |
Publisher | : |
Total Pages | : 412 |
Release | : 1964 |
Genre | : Mathematical statistics |
ISBN | : |
Download Basic Concepts of Probability and Statistics Book in PDF, ePub and Kindle
Author | : T. T. Soong |
Publisher | : John Wiley & Sons |
Total Pages | : 406 |
Release | : 2004-06-25 |
Genre | : Mathematics |
ISBN | : 0470868155 |
Download Fundamentals of Probability and Statistics for Engineers Book in PDF, ePub and Kindle
This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years. It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications. Explains the concept of probabilistic modelling and the process of model selection, verification and analysis. Definitions and theorems are carefully stated and topics rigorously treated. Includes a chapter on regression analysis. Covers design of experiments. Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields. Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.
Author | : Yu. M. Suhov |
Publisher | : |
Total Pages | : 0 |
Release | : 2005 |
Genre | : Mathematical statistics |
ISBN | : |
Download Probability and Statistics by Example: Basic probability and statistics Book in PDF, ePub and Kindle
Author | : Michael J. Evans |
Publisher | : Macmillan |
Total Pages | : 704 |
Release | : 2004 |
Genre | : Mathematics |
ISBN | : 9780716747420 |
Download Probability and Statistics Book in PDF, ePub and Kindle
Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.
Author | : Darrin Speegle |
Publisher | : CRC Press |
Total Pages | : 644 |
Release | : 2021-11-26 |
Genre | : Business & Economics |
ISBN | : 1000504514 |
Download Probability, Statistics, and Data Book in PDF, ePub and Kindle
This book is a fresh approach to a calculus based, first course in probability and statistics, using R throughout to give a central role to data and simulation. The book introduces probability with Monte Carlo simulation as an essential tool. Simulation makes challenging probability questions quickly accessible and easily understandable. Mathematical approaches are included, using calculus when appropriate, but are always connected to experimental computations. Using R and simulation gives a nuanced understanding of statistical inference. The impact of departure from assumptions in statistical tests is emphasized, quantified using simulations, and demonstrated with real data. The book compares parametric and non-parametric methods through simulation, allowing for a thorough investigation of testing error and power. The text builds R skills from the outset, allowing modern methods of resampling and cross validation to be introduced along with traditional statistical techniques. Fifty-two data sets are included in the complementary R package fosdata. Most of these data sets are from recently published papers, so that you are working with current, real data, which is often large and messy. Two central chapters use powerful tidyverse tools (dplyr, ggplot2, tidyr, stringr) to wrangle data and produce meaningful visualizations. Preliminary versions of the book have been used for five semesters at Saint Louis University, and the majority of the more than 400 exercises have been classroom tested.
Author | : Bruce Hansen |
Publisher | : Princeton University Press |
Total Pages | : 417 |
Release | : 2022-06-28 |
Genre | : Business & Economics |
ISBN | : 0691236143 |
Download Probability and Statistics for Economists Book in PDF, ePub and Kindle
A comprehensive and up-to-date introduction to the mathematics that all economics students need to know Probability theory is the quantitative language used to handle uncertainty and is the foundation of modern statistics. Probability and Statistics for Economists provides graduate and PhD students with an essential introduction to mathematical probability and statistical theory, which are the basis of the methods used in econometrics. This incisive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of the mathematics that every economist needs to know. Covers probability and statistics with mathematical rigor while emphasizing intuitive explanations that are accessible to economics students of all backgrounds Discusses random variables, parametric and multivariate distributions, sampling, the law of large numbers, central limit theory, maximum likelihood estimation, numerical optimization, hypothesis testing, and more Features hundreds of exercises that enable students to learn by doing Includes an in-depth appendix summarizing important mathematical results as well as a wealth of real-world examples Can serve as a core textbook for a first-semester PhD course in econometrics and as a companion book to Bruce E. Hansen’s Econometrics Also an invaluable reference for researchers and practitioners
Author | : Norman Matloff |
Publisher | : CRC Press |
Total Pages | : 295 |
Release | : 2019-06-21 |
Genre | : Business & Economics |
ISBN | : 0429687117 |
Download Probability and Statistics for Data Science Book in PDF, ePub and Kindle
Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks. * Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture." * Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner. Prerequisites are calculus, some matrix algebra, and some experience in programming. Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.