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| probability lifesaver: The Probability Lifesaver Steven J. Miller, 2017-05-16 The essential lifesaver for students who want to master probability For students learning probability, its numerous applications, techniques, and methods can seem intimidating and overwhelming. That's where The Probability Lifesaver steps in. Designed to serve as a complete stand-alone introduction to the subject or as a supplement for a course, this accessible and user-friendly study guide helps students comfortably navigate probability's terrain and achieve positive results. The Probability Lifesaver is based on a successful course that Steven Miller has taught at Brown University, Mount Holyoke College, and Williams College. With a relaxed and informal style, Miller presents the math with thorough reviews of prerequisite materials, worked-out problems of varying difficulty, and proofs. He explores a topic first to build intuition, and only after that does he dive into technical details. Coverage of topics is comprehensive, and materials are repeated for reinforcement—both in the guide and on the book's website. An appendix goes over proof techniques, and video lectures of the course are available online. Students using this book should have some familiarity with algebra and precalculus. The Probability Lifesaver not only enables students to survive probability but also to achieve mastery of the subject for use in future courses. A helpful introduction to probability or a perfect supplement for a course Numerous worked-out examples Lectures based on the chapters are available free online Intuition of problems emphasized first, then technical proofs given Appendixes review proof techniques Relaxed, conversational approach |
| probability lifesaver: The Probability Lifesaver Steven J. Miller, 2017-05-16 The essential lifesaver for students who want to master probability For students learning probability, its numerous applications, techniques, and methods can seem intimidating and overwhelming. That's where The Probability Lifesaver steps in. Designed to serve as a complete stand-alone introduction to the subject or as a supplement for a course, this accessible and user-friendly study guide helps students comfortably navigate probability's terrain and achieve positive results. The Probability Lifesaver is based on a successful course that Steven Miller has taught at Brown University, Mount Holyoke College, and Williams College. With a relaxed and informal style, Miller presents the math with thorough reviews of prerequisite materials, worked-out problems of varying difficulty, and proofs. He explores a topic first to build intuition, and only after that does he dive into technical details. Coverage of topics is comprehensive, and materials are repeated for reinforcement—both in the guide and on the book's website. An appendix goes over proof techniques, and video lectures of the course are available online. Students using this book should have some familiarity with algebra and precalculus. The Probability Lifesaver not only enables students to survive probability but also to achieve mastery of the subject for use in future courses. A helpful introduction to probability or a perfect supplement for a course Numerous worked-out examples Lectures based on the chapters are available free online Intuition of problems emphasized first, then technical proofs given Appendixes review proof techniques Relaxed, conversational approach |
| probability lifesaver: 100 Years of Math Milestones: The Pi Mu Epsilon Centennial Collection Stephan Ramon Garcia, Steven J. Miller, 2019-06-13 This book is an outgrowth of a collection of 100 problems chosen to celebrate the 100th anniversary of the undergraduate math honor society Pi Mu Epsilon. Each chapter describes a problem or event, the progress made, and connections to entries from other years or other parts of mathematics. In places, some knowledge of analysis or algebra, number theory or probability will be helpful. Put together, these problems will be appealing and accessible to energetic and enthusiastic math majors and aficionados of all stripes. Stephan Ramon Garcia is WM Keck Distinguished Service Professor and professor of mathematics at Pomona College. He is the author of four books and over eighty research articles in operator theory, complex analysis, matrix analysis, number theory, discrete geometry, and other fields. He has coauthored dozens of articles with students, including one that appeared in The Best Writing on Mathematics: 2015. He is on the editorial boards of Notices of the AMS, Proceedings of the AMS, American Mathematical Monthly, Involve, and Annals of Functional Analysis. He received four NSF research grants as principal investigator and five teaching awards from three different institutions. He is a fellow of the American Mathematical Society and was the inaugural recipient of the Society's Dolciani Prize for Excellence in Research. Steven J. Miller is professor of mathematics at Williams College and a visiting assistant professor at Carnegie Mellon University. He has published five books and over one hundred research papers, most with students, in accounting, computer science, economics, geophysics, marketing, mathematics, operations research, physics, sabermetrics, and statistics. He has served on numerous editorial boards, including the Journal of Number Theory, Notices of the AMS, and the Pi Mu Epsilon Journal. He is active in enrichment and supplemental curricular initiatives for elementary and secondary mathematics, from the Teachers as Scholars Program and VCTAL (Value of Computational Thinking Across Grade Levels), to numerous math camps (the Eureka Program, HCSSiM, the Mathematics League International Summer Program, PROMYS, and the Ross Program). He is a fellow of the American Mathematical Society, an at-large senator for Phi Beta Kappa, and a member of the Mount Greylock Regional School Committee, where he sees firsthand the challenges of applying mathematics. |
| probability lifesaver: All the Math You Missed Thomas A. Garrity, 2021-07-01 Beginning graduate students in mathematical sciences and related areas in physical and computer sciences and engineering are expected to be familiar with a daunting breadth of mathematics, but few have such a background. This bestselling book helps students fill in the gaps in their knowledge. Thomas A. Garrity explains the basic points and a few key results of all the most important undergraduate topics in mathematics, emphasizing the intuitions behind the subject. The explanations are accompanied by numerous examples, exercises and suggestions for further reading that allow the reader to test and develop their understanding of these core topics. Featuring four new chapters and many other improvements, this second edition of All the Math You Missed is an essential resource for advanced undergraduates and beginning graduate students who need to learn some serious mathematics quickly. |
| probability lifesaver: Bioinformatics Research and Applications Xuan Guo, Serghei Mangul, Murray Patterson, Alexander Zelikovsky, 2023-10-07 This book constitutes the refereed proceedings of the 19th International Symposium on Bioinformatics Research and Applications, ISBRA 2023, held in Wrocław, Poland, during October 9–12, 2023. The 28 full papers and 16 short papers included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: reconciling inconsistent molecular structures from biochemical databases; radiology report generation via visual recalibration and context gating-aware; sequence-based nanobody-antigen binding prediction; and hist2Vec: kernel-based embeddings for biological sequence classification. |
| probability lifesaver: Transition To Proofs Simon Rubinstein-salzedo, 2023-07-19 This textbook is aimed at transitioning high-school students who have already developed proficiency in mathematical problem solving from numerical-answer problems to proof-based mathematics. It serves to guide students on how to write and understand mathematical proofs. It covers proof techniques that are commonly used in several areas of mathematics, especially number theory, combinatorics, and analysis. In addition to just teaching the mechanics of proofs, this book showcases key materials in these areas, thus introducing readers to interesting mathematics along with proof techniques. |
| probability lifesaver: The Mathematics of Encryption Margaret Cozzens, Steven J. Miller, 2013-09-05 How quickly can you compute the remainder when dividing by 120143? Why would you even want to compute this? And what does this have to do with cryptography? Modern cryptography lies at the intersection of mathematics and computer sciences, involving number theory, algebra, computational complexity, fast algorithms, and even quantum mechanics. Many people think of codes in terms of spies, but in the information age, highly mathematical codes are used every day by almost everyone, whether at the bank ATM, at the grocery checkout, or at the keyboard when you access your email or purchase products online. This book provides a historical and mathematical tour of cryptography, from classical ciphers to quantum cryptography. The authors introduce just enough mathematics to explore modern encryption methods, with nothing more than basic algebra and some elementary number theory being necessary. Complete expositions are given of the classical ciphers and the attacks on them, along with a detailed description of the famous Enigma system. The public-key system RSA is described, including a complete mathematical proof that it works. Numerous related topics are covered, such as efficiencies of algorithms, detecting and correcting errors, primality testing and digital signatures. The topics and exposition are carefully chosen to highlight mathematical thinking and problem solving. Each chapter ends with a collection of problems, ranging from straightforward applications to more challenging problems that introduce advanced topics. Unlike many books in the field, this book is aimed at a general liberal arts student, but without losing mathematical completeness. |
| probability lifesaver: Mathematics of Optimization: How to do Things Faster Steven J. Miller, 2017-12-20 Optimization Theory is an active area of research with numerous applications; many of the books are designed for engineering classes, and thus have an emphasis on problems from such fields. Covering much of the same material, there is less emphasis on coding and detailed applications as the intended audience is more mathematical. There are still several important problems discussed (especially scheduling problems), but there is more emphasis on theory and less on the nuts and bolts of coding. A constant theme of the text is the “why” and the “how” in the subject. Why are we able to do a calculation efficiently? How should we look at a problem? Extensive effort is made to motivate the mathematics and isolate how one can apply ideas/perspectives to a variety of problems. As many of the key algorithms in the subject require too much time or detail to analyze in a first course (such as the run-time of the Simplex Algorithm), there are numerous comparisons to simpler algorithms which students have either seen or can quickly learn (such as the Euclidean algorithm) to motivate the type of results on run-time savings. |
| probability lifesaver: An Invitation to Modern Number Theory Steven J. Miller, Ramin Takloo-Bighash, 2020-07-21 In a manner accessible to beginning undergraduates, An Invitation to Modern Number Theory introduces many of the central problems, conjectures, results, and techniques of the field, such as the Riemann Hypothesis, Roth's Theorem, the Circle Method, and Random Matrix Theory. Showing how experiments are used to test conjectures and prove theorems, the book allows students to do original work on such problems, often using little more than calculus (though there are numerous remarks for those with deeper backgrounds). It shows students what number theory theorems are used for and what led to them and suggests problems for further research. Steven Miller and Ramin Takloo-Bighash introduce the problems and the computational skills required to numerically investigate them, providing background material (from probability to statistics to Fourier analysis) whenever necessary. They guide students through a variety of problems, ranging from basic number theory, cryptography, and Goldbach's Problem, to the algebraic structures of numbers and continued fractions, showing connections between these subjects and encouraging students to study them further. In addition, this is the first undergraduate book to explore Random Matrix Theory, which has recently become a powerful tool for predicting answers in number theory. Providing exercises, references to the background literature, and Web links to previous student research projects, An Invitation to Modern Number Theory can be used to teach a research seminar or a lecture class. |
| probability lifesaver: The Calculus Lifesaver Adrian Banner, 2009-11-28 For many students, calculus can be the most mystifying and frustrating course they will ever take. The Calculus Lifesaver provides students with the essential tools they need not only to learn calculus, but to excel at it. All of the material in this user-friendly study guide has been proven to get results. The book arose from Adrian Banner's popular calculus review course at Princeton University, which he developed especially for students who are motivated to earn A's but get only average grades on exams. The complete course will be available for free on the Web in a series of videotaped lectures. This study guide works as a supplement to any single-variable calculus course or textbook. Coupled with a selection of exercises, the book can also be used as a textbook in its own right. The style is informal, non-intimidating, and even entertaining, without sacrificing comprehensiveness. The author elaborates standard course material with scores of detailed examples that treat the reader to an inner monologue--the train of thought students should be following in order to solve the problem--providing the necessary reasoning as well as the solution. The book's emphasis is on building problem-solving skills. Examples range from easy to difficult and illustrate the in-depth presentation of theory. The Calculus Lifesaver combines ease of use and readability with the depth of content and mathematical rigor of the best calculus textbooks. It is an indispensable volume for any student seeking to master calculus. Serves as a companion to any single-variable calculus textbook Informal, entertaining, and not intimidating Informative videos that follow the book--a full forty-eight hours of Banner's Princeton calculus-review course--is available at Adrian Banner lectures More than 475 examples (ranging from easy to hard) provide step-by-step reasoning Theorems and methods justified and connections made to actual practice Difficult topics such as improper integrals and infinite series covered in detail Tried and tested by students taking freshman calculus |
| probability lifesaver: Introduction to Probability Charles Miller Grinstead, James Laurie Snell, 2012-10-30 This text is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject. |
| probability lifesaver: Naked Statistics: Stripping the Dread from the Data Charles Wheelan, 2013-01-07 A New York Times bestseller Brilliant, funny…the best math teacher you never had. —San Francisco Chronicle Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called sexy. From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life. |
| probability lifesaver: First Look At Rigorous Probability Theory, A (2nd Edition) Jeffrey S Rosenthal, 2006-11-14 This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail. |
| probability lifesaver: Probability and Measure Patrick Billingsley, 2017 Now in its new third edition, Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining the unique approach of the previous editions, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory and measure theory is then developed and applied to probability. Probability and Measure provides thorough coverage of probability, measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes. The Third Edition features an improved treatment of Brownian motion and the replacement of queuing theory with ergodic theory.· Probability· Measure· Integration· Random Variables and Expected Values· Convergence of Distributions· Derivatives and Conditional Probability· Stochastic Processes |
| probability lifesaver: Benford's Law Steven J. Miller, 2015-05-26 Benford's law states that the leading digits of many data sets are not uniformly distributed from one through nine, but rather exhibit a profound bias. This bias is evident in everything from electricity bills and street addresses to stock prices, population numbers, mortality rates, and the lengths of rivers. Here, Steven Miller brings together many of the world’s leading experts on Benford’s law to demonstrate the many useful techniques that arise from the law, show how truly multidisciplinary it is, and encourage collaboration. Beginning with the general theory, the contributors explain the prevalence of the bias, highlighting explanations for when systems should and should not follow Benford’s law and how quickly such behavior sets in. They go on to discuss important applications in disciplines ranging from accounting and economics to psychology and the natural sciences. The contributors describe how Benford’s law has been successfully used to expose fraud in elections, medical tests, tax filings, and financial reports. Additionally, numerous problems, background materials, and technical details are available online to help instructors create courses around the book. Emphasizing common challenges and techniques across the disciplines, this accessible book shows how Benford’s law can serve as a productive meeting ground for researchers and practitioners in diverse fields. |
| probability lifesaver: Introduction to Probability Models Sheldon M. Ross, 2007 Rosss classic bestseller has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries. |
| probability lifesaver: Math Smart Junior Marcia Lerner, 1995 Written by the author of the award-winning adult version of Math Smart, this fun and useful guide includes quizzes, drills, and a glossary of terms and concepts. |
| probability lifesaver: America's lifesaver & guardian of the seas , 2003 |
| probability lifesaver: Voyage au pays des probas - Cours et exercices corrigés Bernhard Elsner Bernhard, 2021-06-08 |
| probability lifesaver: The Humongous Book of Statistics Problems Robert Donnelly, W. Michael Kelley, 2009-12-01 A brain explains? most math and science study guides are dry and difficult, but this is the exception. Following the successful, 'The Humongous Books', in calculus and algebra, bestselling author Mike Kelley takes a typical statistics workbook, full of solved problems, and writes notes in the margins, adding missing steps and simplifying concepts and solutions. By learning how to interpret and solve problems as they are presented in statistics courses, students prepare to solve those difficult problems that were never discussed in class but are always on exams. ? With annotated notes and explanations of missing steps throughout, like no other statistics workbook on the market ? An award-winning former math teacher whose website (calculus-help.com) reaches thousands every month, providing exposure for all his books |
| probability lifesaver: Introduction to Probability Models, Student Solutions Manual (e-only) Sheldon M. Ross, 2010-01-01 Introduction to Probability Models, Student Solutions Manual (e-only) |
| probability lifesaver: Statistical Inference Via Convex Optimization Anatoli Juditsky, Arkadi Nemirovski, 2020-04-07 This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences. Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems—sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals—demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems. Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text. |
| probability lifesaver: Introduction to Probability Dimitri Bertsekas, John N. Tsitsiklis, 2008-07-01 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. |
| probability lifesaver: Fat Chance Benedict Gross, Joe Harris, Emily Riehl, 2019-05-31 In a world where we are constantly being asked to make decisions based on incomplete information, facility with basic probability is an essential skill. This book provides a solid foundation in basic probability theory designed for intellectually curious readers and those new to the subject. Through its conversational tone and careful pacing of mathematical development, the book balances a charming style with informative discussion. This text will immerse the reader in a mathematical view of the world, giving them a glimpse into what attracts mathematicians to the subject in the first place. Rather than simply writing out and memorizing formulas, the reader will come out with an understanding of what those formulas mean, and how and when to use them. Readers will also encounter settings where probabilistic reasoning does not apply or where intuition can be misleading. This book establishes simple principles of counting collections and sequences of alternatives, and elaborates on these techniques to solve real world problems both inside and outside the casino. Pair this book with the HarvardX online course for great videos and interactive learning: https://harvardx.link/fat-chance. |
| probability lifesaver: Introduction to Probability Joseph K. Blitzstein, Jessica Hwang, 2014-07-24 Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment. |
| probability lifesaver: Statistics for Linguists: An Introduction Using R Bodo Winter, 2019-10-30 Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details. It contains many applied examples using the R statistical programming environment. Written in an accessible tone and style, this text is the ideal main resource for graduate and advanced undergraduate students of Linguistics statistics courses as well as those in other fields, including Psychology, Cognitive Science, and Data Science. |
| probability lifesaver: SAT Power Math The Princeton Review, 2014-12-16 THE PRINCETON REVIEW GETS RESULTS! Ace the SAT math sections with 10 need-to-know essential topics for acing the exam. This eBook edition is formatted for on-screen viewing with cross-linked questions, answers, and explanations. In our number-crunching world, basic math knowledge is a must—especially for acing tests like the SAT. For many people, though, math is confusing and often anxiety inducing. That’s why we’ve created SAT Power Math, which uses a simple, straightforward approach to break down and explain complicated math concepts and common problems. This book is your powerful tool for building essential math skills for the SAT, school, and beyond. Everything You Need to Help Achieve a High Math Score. • Comprehensive review of math topics like algebra, geometry, and statistics • Strategies for cracking the most common question types found on the SAT • A glossary of key math terms at the end of every chapter Practice Your Way to Perfection. • Practice drills for every math topic covered in the book • Detailed step-by-step answer explanations • Targeted strategies to help you score high on the math section of the SAT |
| probability lifesaver: SPSS Survival Manual Julie Pallant, The SPSS Survival Manual throws a lifeline to students and researchers grappling with this data analysis software. In this thoroughly revised edition of her bestselling text, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Pallant discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report. For both beginners and experienced users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is an essential guide. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. In this fourth edition all chapters have been updated to accommodate changes to SPSS procedures, screens and output. A number of additional techniques (McNemar's Test, Cochran's Q Test) have been included in the non-parametric statistics chapter. 'An excellent introduction to using SPSS for data analysis... It provides a self-contained resource itself, with more than simply (detailed and clear) step-by-step descriptions of statistical procedures in SPSS. There is also a wealth of tips and advice, and for each statistical technique a brief, but consistently reliable, explanation is provided.' - Associate Professor George Dunbar, Department of Psychology, University of Warwick 'This book is recommended as ESSENTIAL to all students completing research projects - minor and major.' - John Roodenburg, Faculty of Education, Monash University |
| probability lifesaver: Math Smart Marcia Lerner, 2001 Whether you're checking out at the supermarket or cashing in at the stock market, you need a command of basic math to survive in today's number crunching world. But most people have problems with math. A decimal here and an exponent there and you've gone from a balanced checkbook to a multi-trillion-dollar national debt. That's why The Princeton Review created Math Smart. Math Smart's approach is easy to follow. We'll show you how to perform basic math operations like addition, subtraction, multiplication, and division. Once you've got that down, Math Smart will teach you how to handle the scary stuff like exponents, square roots, geometry, and algebra. How does Math Smart work? It teaches you user-friendly techniques that break down complicated problems and equations into their basic parts. You won't waste your time memorizing dozens of long formulas and equations. We don't promise you'll love math, but after reading Math Smart, you'll never be crunched by numbers again. |
| probability lifesaver: Statistics For Dummies Deborah J. Rumsey, 2016-05-19 The fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance. |
| probability lifesaver: Schaum's Outline of Theory and Problems of Probability SI (metric) Edition Seymour Lipschutz, 1987 |
| probability lifesaver: Understanding Analysis Stephen Abbott, 2012-12-06 Understanding Analysis outlines an elementary, one-semester course designed to expose students to the rich rewards inherent in taking a mathematically rigorous approach to the study of functions of a real variable. The aim of a course in real analysis should be to challenge and improve mathematical intuition rather than to verify it. The philosophy of this book is to focus attention on the questions that give analysis its inherent fascination. Does the Cantor set contain any irrational numbers? Can the set of points where a function is discontinuous be arbitrary? Are derivatives continuous? Are derivatives integrable? Is an infinitely differentiable function necessarily the limit of its Taylor series? In giving these topics center stage, the hard work of a rigorous study is justified by the fact that they are inaccessible without it. |
| probability lifesaver: Turbulent Flows Stephen B. Pope, 2000-08-10 This is a graduate text on turbulent flows, an important topic in fluid dynamics. It is up-to-date, comprehensive, designed for teaching, and is based on a course taught by the author at Cornell University for a number of years. The book consists of two parts followed by a number of appendices. Part I provides a general introduction to turbulent flows, how they behave, how they can be described quantitatively, and the fundamental physical processes involved. Part II is concerned with different approaches for modelling or simulating turbulent flows. The necessary mathematical techniques are presented in the appendices. This book is primarily intended as a graduate level text in turbulent flows for engineering students, but it may also be valuable to students in applied mathematics, physics, oceanography and atmospheric sciences, as well as researchers and practising engineers. |
| probability lifesaver: The Summer Seekers Sarah Morgan, 2021-05-18 “The Summer Seekers is the ultimate road trip book.”—Susan Wiggs, #1 New York Times bestselling author Get swept into a summer of sunshine, soul-searching and shameless matchmaking with this delightfully bighearted road-trip adventure by USA TODAY bestselling author Sarah Morgan! Kathleen is eighty years old. After she has a run-in with an intruder, her daughter wants her to move into a residential home. But she’s not having any of it. What she craves—what she needs—is adventure. Liza is drowning in the daily stress of family life. The last thing she needs is her mother jetting off on a wild holiday, making Liza long for a solo summer of her own. Martha is having a quarter-life crisis. Unemployed, unloved and uninspired, she just can’t get her life together. But she knows something has to change. When Martha sees Kathleen’s advertisement for a driver and companion to share an epic road trip across America with, she decides this job might be the answer to her prayers. She's not the world's best driver, but anything has to be better than living with her parents. And traveling with a stranger? No problem. Anyway, how much trouble can one eighty-year-old woman be? As these women embark on the journey of a lifetime, they all discover it's never too late to start over… Find out what happens when a career-driven woman exchanges her briefcase for a Christmas-kissed cottage in USA Today bestselling author Sarah Morgan's heartwarming story, The Holiday Cottage! More captivating stories by Sarah Morgan: The Holiday Cottage The Summer Swap The Book Club Hotel The Island Villa Snowed In For Christmas |
| probability lifesaver: Hybrid Feedback Control Ricardo G. Sanfelice, 2021-01-12 Hybrid systems are those that-unlike classical systems-exhibit both discrete changes, or jumps, and continuous changes, or flow. The canonical example of a hybrid system is a bouncing ball: the ball's speed changes continuously between bounces, but there is a discrete jump in velocity each time the ball impacts the ground. Hybrid systems feature widely across disciplines, including in biology, computer science, and mechanical engineering; examples range from fireflies to self-driving cars. Although classical control theory provides powerful tools for analyzing systems that exhibit either flow or jumps, it is ill-equipped to handle hybrid systems, which feature both behaviors. In Hybrid Feedback Control, Ricardo Sanfelice presents a self-contained introduction to the control of hybrid systems, and develops new tools for their design and analysis. This monograph uses hybrid systems notation to present a new, unified control theory framework, thus filling an important gap in the control theory literature. In addition to presenting this theoretical framework, the book also includes a variety of examples and exercises, a Matlab toolbox, and a summary at the beginning of each chapter. The book was originally used in a series of lectures on the topic, and will find a modest amount of crossover course use. The book will also find use outside the field of control, particularly in dynamical systems theory, applied mathematics, and computer science-- |
| probability lifesaver: Opt Art Robert Bosch (mathématicien), 2019-11-12 Bosch provides a lively and accessible introduction to the geometric, algebraic, and algorithmic foundations of optimization. He presents classical applications, such as the legendary Traveling Salesman Problem, and shows how to adapt them to make optimization art--opt art. art. |
| probability lifesaver: Russia's Life-saver Albert Loren Weeks, 2004-01-01 Russia's Life-Saver brilliantly examines the diplomatic rationale for and results of the U.S. decision to grant over $12 billion in Lend-Lease aid to Soviet Russia during World War II. Author Albert L. Weeks wields many facts and statistics never before published in the U.S. Of particular interest is the statement by Soviet Army Marshal Georgy K. Zhukov that U.S. Lend-Lease aid was indispensable, despite Soviet propaganda that sought to minimize its importance. |
| probability lifesaver: Introductory Statistics Prem S. Mann, 2010-02-02 When it comes to learning statistics, Mann delivers the information that business professionals need. The new edition incorporates the most up-to-date methods and applications to present the latest information in the field. It focuses on explaining how to apply the concepts through case studies and numerous examples. Data integrated throughout the chapters come from a wide range of disciplines and media sources. Over 200 examples are included along with marginal notes and step-by-step solutions. The Decide for Yourself feature also helps business professionals explore real-world problems and solutions. |
| probability lifesaver: Calculus 2 Simplified Oscar E. Fernandez, 2025-04-01 From the author of Calculus Simplified, an accessible, personalized approach to Calculus 2 Second-semester calculus is rich with insights into the nature of infinity and the very foundations of geometry, but students can become overwhelmed as they struggle to synthesize the range of material covered in class. Oscar Fernandez provides a “Goldilocks approach” to learning the mathematics of integration, infinite sequences and series, and their applications—the right depth of insights, the right level of detail, and the freedom to customize your student experience. Learning calculus should be an empowering voyage, not a daunting task. Calculus 2 Simplified gives you the flexibility to choose your calculus adventure, and the right support to help you master the subject. Provides an accessible, user-friendly introduction to second-semester college calculus The unique customizable approach enables students to begin first with integration (traditional) or with sequences and series (easier) Chapters are organized into mini lessons that focus first on developing the intuition behind calculus, then on conceptual and computational mastery Features more than 170 solved examples that guide learning and more than 400 exercises, with answers, that help assess understanding Includes optional chapter appendixes Comes with supporting materials online, including video tutorials and interactive graphs |
| probability lifesaver: Let's Play Math Denise Gaskins, 2012-09-04 |
Probability - Wikipedia
Probability is a branch of mathematics and statistics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the …
Probability - Math is Fun
How likely something is to happen. Many events can't be predicted with total certainty. The best we can say is how likely they are to happen, using the idea of probability. When a coin is tossed, …
Probability - Formula, Calculating, Find, Theorems, Examples
Probability is all about how likely is an event to happen. For a random experiment with sample space S, the probability of happening of an event A is calculated by the probability formula n (A)/n (S).
7.5: Basic Concepts of Probability - Mathematics LibreTexts
Define probability including impossible and certain events. Calculate basic theoretical probabilities. Calculate basic empirical probabilities. Distinguish among theoretical, empirical, and subjective …
Probability Definition in Math - BYJU'S
Probability is a measure of the likelihood of an event to occur. Many events cannot be predicted with total certainty. We can predict only the chance of an event to occur i.e., how likely they are …
How To Calculate Probability - Math Steps, Examples & Questions
Free how to calculate probability math topic guide, including step-by-step examples, free practice questions, teaching tips and more!
What is Probability? Definition, Types, Formula, & Examples
Apr 7, 2025 · Probability is defined as the measure of how likely an event is to happen, usually expressed as a value between zero and one. A Probability of zero indicates that the event is …
Probability in Maths - GeeksforGeeks
May 16, 2025 · In this section, you will explore the fundamental concepts of probability, key formulas, conditional probability, and Bayes' Theorem. By the end, you'll have a clear …
Probability | Brilliant Math & Science Wiki
A probability is a number that represents the likelihood of an uncertain event. Probabilities are always between 0 and 1, inclusive. The larger the probability, the more likely the event is to …
Probability - Definition, Formula, Types, Terms, Solved Problems
Jan 15, 2021 · Probability is defined as the possibility of an event to occur. The formula for Probability is given as the ratio of the number of favorable events to the total number of possible …
Probability - Wikipedia
Probability is a branch of mathematics and statistics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 …
Probability - Math is Fun
How likely something is to happen. Many events can't be predicted with total certainty. The best we can say is how likely they are to happen, using the idea of probability. When a coin is …
Probability - Formula, Calculating, Find, Theorems, Examples
Probability is all about how likely is an event to happen. For a random experiment with sample space S, the probability of happening of an event A is calculated by the probability formula n …
7.5: Basic Concepts of Probability - Mathematics LibreTexts
Define probability including impossible and certain events. Calculate basic theoretical probabilities. Calculate basic empirical probabilities. Distinguish among theoretical, empirical, …
Probability Definition in Math - BYJU'S
Probability is a measure of the likelihood of an event to occur. Many events cannot be predicted with total certainty. We can predict only the chance of an event to occur i.e., how likely they …
How To Calculate Probability - Math Steps, Examples & Questions
Free how to calculate probability math topic guide, including step-by-step examples, free practice questions, teaching tips and more!
What is Probability? Definition, Types, Formula, & Examples
Apr 7, 2025 · Probability is defined as the measure of how likely an event is to happen, usually expressed as a value between zero and one. A Probability of zero indicates that the event is …
Probability in Maths - GeeksforGeeks
May 16, 2025 · In this section, you will explore the fundamental concepts of probability, key formulas, conditional probability, and Bayes' Theorem. By the end, you'll have a clear …
Probability | Brilliant Math & Science Wiki
A probability is a number that represents the likelihood of an uncertain event. Probabilities are always between 0 and 1, inclusive. The larger the probability, the more likely the event is to …
Probability - Definition, Formula, Types, Terms, Solved Problems
Jan 15, 2021 · Probability is defined as the possibility of an event to occur. The formula for Probability is given as the ratio of the number of favorable events to the total number of …
