A self-study guide for practicing engineers, scientists, and students, this book offers practical, worked-out examples on continuous and discrete probability for problem-solving courses. It is filled with handy diagrams, examples, and solutions that greatly aid in the comprehension of a variety of probability problems.

A self-study guide for practicing engineers, scientists, and students, this book offers practical, worked-out examples on continuous and discrete probability for problem-solving courses. It is filled with handy diagrams, examples, and solutions that greatly aid in the comprehension of a variety of probability problems.

This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Intended as a first course in probability at post-calculus level, this book is of special interest to students majoring in computer science as well as in mathematics. Since calculus is used only occasionally in the text, students who have forgotten their calculus can nevertheless easily understand the book, and its slow, gentle style and clear exposition will also appeal. Basic concepts such as counting, independence, conditional probability, random variables, approximation of probabilities, generating functions, random walks and Markov chains are all clearly explained and backed by many worked exercises. The 1,196 numerical answers to the 405 exercises, many with multiple parts, are included at the end of the book, and throughout, there are various historical comments on the study of probability. These include biographical information on such famous contributors as Fermat, Pascal, the Bernoullis, DeMoivre, Bayes, Laplace, Poisson, and Markov. Of interest to a wide range of readers and useful in many undergraduate programs.

Probability and Measure Theory, Second Edition, is a text for a graduate-level course in probability that includes essential background topics in analysis. It provides extensive coverage of conditional probability and expectation, strong laws of large numbers, martingale theory, the central limit theorem, ergodic theory, and Brownian motion. Clear, readable style Solutions to many problems presented in text Solutions manual for instructors Material new to the second edition on ergodic theory, Brownian motion, and convergence theorems used in statistics No knowledge of general topology required, just basic analysis and metric spaces Efficient organization

I know how you feel. Why should I have to take this test? I'm not going to be a math teacher! Thousands of others have felt the same way. We have found that this workbook will increase your chances of passing the test exponentially! This is a workbook to enable you to pass the Core Academic Skills for Educators: Mathematics (5732). You can now use a calculator for this test but, of course, they have made it harder. Now you have to memorize a lot of formulas but, don't worry, I will provide them all for you in this book. There are questions with multiple correct answers and there are questions where you have to fill in the blank. Samples of each type of question are included in the book. Core Math Made Easy is written in very clear and easy to understand language. The four chapters cover the four sections of the test: Number & Quantity, Algebra & Functions, Geometry, and Probability and Statistics. There are samples of each type of question on the test and answer keys that guide you through each problem in detail. At the end of each section, you will find sample test questions and explanations. Core Math Made Easy is currently being used as the textbook for the workshops at George Mason University. - Publisher.

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

An intuitive, yet precise introduction to probability theory, stochastic processes, statistical inference, and probabilistic models used in science, engineering, economics, and related fields. This is the currently used textbook for an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students, and for a leading online class on the subject. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains a number of more advanced topics, including transforms, sums of random variables, a fairly detailed introduction to Bernoulli, Poisson, and Markov processes, Bayesian inference, and an introduction to classical statistics. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis is explained intuitively in the main text, and then developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems.

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

REA's FTCE Mathematics 6-12 (026) Test Prep with Online Tests Gets You Certified and in the Classroom! Updated Third Edition This new third edition of our FTCE Mathematics 6-12 test prep is designed to help you master the competencies tested on this challenging exam. It's perfect for teacher education students and career-changing professionals who are need certification to teach mathematics in Florida's secondary schools. Written by Sandra Rush, M.A., math test expert, author, tutor, and private test-prep coach, our test prep covers all the relevant topics, with expert score-raising strategies developed just for the FTCE Math test. Our targeted review covers the 10 competencies tested: knowledge of algebra, advanced algebra, functions, geometry, coordinate geometry, trigonometry, statistics and probability, calculus, mathematical reasoning, and instruction and assessment. End-of-chapter practice reinforces key concepts and helps you evaluate your overall understanding of the subject. An online diagnostic test pinpoints your strengths and weaknesses so you can focus your study on the topics where you need the most review. Two full-length practice tests (available in the book and online) offer realistic practice and are balanced to include every type of question and skill tested on the actual exam. Our online tests are offered in a timed format with automatic scoring and diagnostic feedback to help you zero in on the topics and types of questions that give you trouble now, so you can succeed on test day. This test prep is a must-have for teacher certification candidates in Florida! REA's book + online prep packages are teacher-recommended and are proven to be the extra support teacher candidates need to pass their challenging certification exams.