Expert choice for probability basics
When you want to find probability basics, you may need to consider between many choices. Finding the best probability basics is not an easy task. In this post, we create a very short list about top 6 the best probability basics for you. You can check detail product features, product specifications and also our voting for each product. Let’s start with following top 6 probability basics:
Best probability basics
1. The Little Purple Probability Book: Master the Thinking Skills to Succeed in Basic Probability
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Used Book in Good ConditionDescription
Fine-tune your numerical mindset with a quantitative review that serves as a tool for perceiving probability in a new way. Whether you're a high school student, college student, or a test-prep candidate, this book's wealth of explanations and insights makes it a perfect learning companion.Enjoy the benefits of your own short course in probability:
*Be able to think conceptually by understanding how key problems "fit" within the main topics of probability, permutations, combinations, and enumerations.
*Master basic probability using a simple "flowchart" to identify the correct formulas.
*Understand when to "add" probabilities and when to "multiply" probabilities.
*Be able to distinguish between events that are independent versus not independent and events that are mutually exclusive versus not mutually exclusive.
*Grasp key differences between permutations and combinations and look for key words such as "arrangements" or "selections" to indicate the correct problem type.
*Solve tricky permutation problems that involve repeated letters or numbers.
*Approach probability problems with a newfound confidence and competency.
This book is focused on those thinking skills that are essential for mastering basic probability. Such thinking skills make it much more likely that a person will be able to approach the subject in a conceptual way, understand the "how" and "why" of problem solving, and grasp those key principles that act as themes to bind related problems. These skills combine the science of math with the art of numbers.
2. Basic Probability Theory (Dover Books on Mathematics)
Description
This introduction to more advanced courses in probability and real analysis emphasizes the probabilistic way of thinking, rather than measure-theoretic concepts. Geared toward advanced undergraduates and graduate students, its sole prerequisite is calculus.
Taking statistics as its major field of application, the text opens with a review of basic concepts, advancing to surveys of random variables, the properties of expectation, conditional probability and expectation, and characteristic functions. Subsequent topics include infinite sequences of random variables, Markov chains, and an introduction to statistics. Complete solutions to some of the problems appear at the end of the book.
Taking statistics as its major field of application, the text opens with a review of basic concepts, advancing to surveys of random variables, the properties of expectation, conditional probability and expectation, and characteristic functions. Subsequent topics include infinite sequences of random variables, Markov chains, and an introduction to statistics. Complete solutions to some of the problems appear at the end of the book.
3. Basic Concepts of Probability and Statistics (Classics in Applied Mathematics)
Description
Basic Concepts of Probability and Statistics provides a mathematically rigorous introduction to the fundamental ideas of modern statistics for readers without a calculus background. It is the only book at this level to introduce readers to modern concepts of hypothesis testing and estimation, covering basic concepts of finite, discrete models of probability and elementary statistical methods. Although published in 1970, it maintains a modern outlook, especially with such topics as models and model building, simple random and stratified survey sampling, experimental design, and nonparametric tests and its discussion of power. The book covers a wide range of applications in manufacturing, biology, and social science, including demographics, political science, and sociology. Each section offers extensive problem sets, with selected answers provided. Among the topics covered that readers may not expect in an elementary text are optimal design and a statement and proof of the fundamental (Neyman-Pearson) lemma for hypothesis testing.4. Graphing, Statistics, & Probability, 6-8+: Inventive Exercises to Sharpen Skills and Raise Achievement (Basic/Not Boring series)
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ISBN13: 9780865304468Condition: New
Notes: BRAND NEW FROM PUBLISHER! 100% Satisfaction Guarantee. Tracking provided on most orders. Buy with Confidence! Millions of books sold!
Description
This set of standards-based reproducible activity pages is basic, not boring. In Graphing and Statistics students develop skills as they step into a world of daredevil activities and wild fun. They will interpret and draw conclusions from data, describe permutations of sets, and find the probability of independent and dependent events. An assessment and a glossary are included.5. Probability Concepts in Engineering Planning and Design, Basic Principles (Probability Concepts in Engineering Planning & Design) (Volume 1)
Description
Ships out immediately with tracking number! always within 24 hours. This book is in solid condition with minimal highlighting or signs of use. Feel free to contact us with any further inquiries6. A Basic Course in Probability Theory (Universitext)
Description
This text develops the necessary background in probability theory underlying diverse treatments of stochastic processes and their wide-ranging applications. In this second edition, the text has been reorganized for didactic purposes, new exercises have been added and basic theory has been expanded. General Markov dependent sequences and their convergence to equilibrium is the subject of an entirely new chapter. The introduction of conditional expectation and conditional probability very early in the text maintains the pedagogic innovation of the first edition; conditional expectation is illustrated in detail in the context of an expanded treatment of martingales, the Markov property, and the strong Markov property. Weak convergence of probabilities on metric spaces and Brownian motion are two topics to highlight. A selection of large deviation and/or concentration inequalities ranging from those of Chebyshev, CramerChernoff, BahadurRao, to Hoeffding have been added, with illustrative comparisons of their use in practice. This also includes a treatment of the BerryEsseen error estimate in the central limit theorem.
The authors assume mathematical maturity at a graduate level; otherwise the book is suitable for students with varying levels of background in analysis and measure theory. For the reader who needs refreshers, theorems from analysis and measure theory used in the main text are provided in comprehensive appendices, along with their proofs, for ease of reference.
Rabi Bhattacharya is Professor of Mathematics at the University of Arizona. Edward Waymire is Professor of Mathematics at Oregon State University. Both authors have co-authored numerous books, including a series of four upcoming graduate textbooks in stochastic processes with applications.
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