## Similar

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.

New York Times Bestseller

“Not so different in spirit from the way public intellectuals like John Kenneth Galbraith once shaped discussions of economic policy and public figures like Walter Cronkite helped sway opinion on the Vietnam War…could turn out to be one of the more momentous books of the decade.”

—New York Times Book Review

"Nate Silver's The Signal and the Noise is The Soul of a New Machine for the 21st century."

—Rachel Maddow, author of Drift

"A serious treatise about the craft of prediction—without academic mathematics—cheerily aimed at lay readers. Silver's coverage is polymathic, ranging from poker and earthquakes to climate change and terrorism."

—New York Review of Books

Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of FiveThirtyEight.com.

Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.

In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science.

Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.

With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.

From the Trade Paperback edition.

By showing us the true nature of chance and revealing the psychological illusions that cause us to misjudge the world around us, Mlodinow gives us the tools we need to make more informed decisions. From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.

From the Trade Paperback edition.

The Essentials For Dummies Series

Dummies is proud to present our new series, The Essentials For Dummies. Now students who are prepping for exams, preparing to study new material, or who just need a refresher can have a concise, easy-to-understand review guide that covers an entire course by concentrating solely on the most important concepts. From algebra and chemistry to grammar and Spanish, our expert authors focus on the skills students most need to succeed in a subject.

Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

The roller coaster of romance is hard to quantify; defining how lovers might feel from a set of simple equations is impossible. But that doesn’t mean that mathematics isn’t a crucial tool for understanding love.

Love, like most things in life, is full of patterns. And mathematics is ultimately the study of patterns—from predicting the weather to the fluctuations of the stock market, the movement of planets or the growth of cities. These patterns twist and turn and warp and evolve just as the rituals of love do.

In The Mathematics of Love, Dr. Hannah Fry takes the reader on a fascinating journey through the patterns that define our love lives, applying mathematical formulas to the most common yet complex questions pertaining to love: What’s the chance of finding love? What’s the probability that it will last? How do online dating algorithms work, exactly? Can game theory help us decide who to approach in a bar? At what point in your dating life should you settle down?

From evaluating the best strategies for online dating to defining the nebulous concept of beauty, Dr. Fry proves—with great insight, wit, and fun—that math is a surprisingly useful tool to negotiate the complicated, often baffling, sometimes infuriating, always interesting, mysteries of love.

Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.

You’ll learn how to:

Wrangle—transform your datasets into a form convenient for analysisProgram—learn powerful R tools for solving data problems with greater clarity and easeExplore—examine your data, generate hypotheses, and quickly test themModel—provide a low-dimensional summary that captures true "signals" in your datasetCommunicate—learn R Markdown for integrating prose, code, and resultsThe 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 protocolPacked 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.

But Hand is no believer in superstitions, prophecies, or the paranormal. His definition of "miracle" is thoroughly rational. No mystical or supernatural explanation is necessary to understand why someone is lucky enough to win the lottery twice, or is destined to be hit by lightning three times and still survive. All we need, Hand argues, is a firm grounding in a powerful set of laws: the laws of inevitability, of truly large numbers, of selection, of the probability lever, and of near enough.

Together, these constitute Hand's groundbreaking Improbability Principle. And together, they explain why we should not be so surprised to bump into a friend in a foreign country, or to come across the same unfamiliar word four times in one day. Hand wrestles with seemingly less explicable questions as well: what the Bible and Shakespeare have in common, why financial crashes are par for the course, and why lightning does strike the same place (and the same person) twice. Along the way, he teaches us how to use the Improbability Principle in our own lives—including how to cash in at a casino and how to recognize when a medicine is truly effective.

An irresistible adventure into the laws behind "chance" moments and a trusty guide for understanding the world and universe we live in, The Improbability Principle will transform how you think about serendipity and luck, whether it's in the world of business and finance or you're merely sitting in your backyard, tossing a ball into the air and wondering where it will land.

1,001 Statistics Practice Problems For Dummies takes you beyond the instruction and guidance offered in Statistics For Dummies to give you a more hands-on understanding of statistics. The practice problems offered range in difficulty, including detailed explanations and walk-throughs.

In this series, every step of every solution is shown with explanations and detailed narratives to help you solve each problem. With the book purchase, you’ll also get access to practice statistics problems online. This content features 1,001 practice problems presented in multiple choice format; on-the-go access from smart phones, computers, and tablets; customizable practice sets for self-directed study; practice problems categorized as easy, medium, or hard; and a one-year subscription with book purchase.

Offers on-the-go access to practice statistics problems Gives you friendly, hands-on instruction 1,001 statistics practice problems that range in difficulty1,001 Statistics Practice Problems For Dummies provides ample practice opportunities for students who may have taken statistics in high school and want to review the most important concepts as they gear up for a faster-paced college class.

Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.

Learn basic concepts of measurement and probability theory, data management, and research designDiscover basic statistical procedures, including correlation, the t-test, the chi-square and Fisher’s exact tests, and techniques for analyzing nonparametric dataLearn advanced techniques based on the general linear model, including ANOVA, ANCOVA, multiple linear regression, and logistic regressionUse and interpret statistics for business and quality improvement, medical and public health, and education and psychologyCommunicate with statistics and critique statistical information presented by othersThe assumption that metrics comparing us to an average—like GPAs, personality test results, and performance review ratings—reveal something meaningful about our potential is so ingrained in our consciousness that we don’t even question it. That assumption, says Harvard’s Todd Rose, is spectacularly—and scientifically—wrong.

In The End of Average, Rose, a rising star in the new field of the science of the individual shows that no one is average. Not you. Not your kids. Not your employees. This isn’t hollow sloganeering—it’s a mathematical fact with enormous practical consequences. But while we know people learn and develop in distinctive ways, these unique patterns of behaviors are lost in our schools and businesses which have been designed around the mythical “average person.” This average-size-fits-all model ignores our differences and fails at recognizing talent. It’s time to change it.

Weaving science, history, and his personal experiences as a high school dropout, Rose offers a powerful alternative to understanding individuals through averages: the three principles of individuality. The jaggedness principle (talent is always jagged), the context principle (traits are a myth), and the pathways principle (we all walk the road less traveled) help us understand our true uniqueness—and that of others—and how to take full advantage of individuality to gain an edge in life.

Read this powerful manifesto in the ranks of Drive, Quiet, and Mindset—and you won’t see averages or talent in the same way again.

Drawing from Moskowitz's original research, as well as studies from fellow economists such as bestselling author Richard Thaler, the authors look at: the influence home-field advantage has on the outcomes of games in all sports and why it exists; the surprising truth about the universally accepted axiom that defense wins championships; the subtle biases that umpires exhibit in calling balls and strikes in key situations; the unintended consequences of referees' tendencies in every sport to "swallow the whistle," and more.

Among the insights that Scorecasting reveals:

Why Tiger Woods is prone to the same mistake in high-pressure putting situations that you and I areWhy professional teams routinely overvalue draft picks The myth of momentum or the "hot hand" in sports, and why so many fans, coaches, and broadcasters fervently subscribe to itWhy NFL coaches rarely go for a first down on fourth-down situations--even when their reluctance to do so reduces their chances of winning.

In an engaging narrative that takes us from the putting greens of Augusta to the grid iron of a small parochial high school in Arkansas, Scorecasting will forever change how you view the game, whatever your favorite sport might be.

From the Hardcover edition.

Advanced stats give hockeyÍs powerbrokers an edge, and now fans can get in on the action. Stat Shot is a fun and informative guide hockey fans can use to understand and enjoy what analytics says about team building, a playerÍs junior numbers, measuring faceoff success, recording save percentage, the most one-sided trades in history, and everything you ever wanted to know about shot-based metrics. Acting as an invaluable supplement to traditional analysis, Stat Shot can be used to test the validity of conventional wisdom, and to gain insight into what teams are doing behind the scenes „ or maybe what they should be doing.

Whether looking for a reference for leading-edge research and hard-to-find statistical data, or for passionate and engaging storytelling, Stat Shot belongs on every serious hockey fanÍs bookshelf.

“No one is better at making the recondite accessible and exciting.” —Bill Bryson

Brain Pickings and Kirkus Best Science Book of the Year

Every week seems to throw up a new discovery, shaking the foundations of what we know. But are there questions we will never be able to answer—mysteries that lie beyond the predictive powers of science? In this captivating exploration of our most tantalizing unknowns, Marcus du Sautoy invites us to consider the problems in cosmology, quantum physics, mathematics, and neuroscience that continue to bedevil scientists and creative thinkers who are at the forefront of their fields.

At once exhilarating, mind-bending, and compulsively readable, The Great Unknown challenges us to consider big questions—about the nature of consciousness, what came before the big bang, and what lies beyond our horizons—while taking us on a virtuoso tour of the great breakthroughs of the past and celebrating the men and women who dared to tackle the seemingly impossible and had the imagination to come up with new ways of seeing the world.

This book is ideal for anyone who likes puzzles, brainteasers, games, gambling, magic tricks, and those who want to apply math and science to everyday circumstances. Several hacks in the first chapter alone-such as the "central limit theorem,", which allows you to know everything by knowing just a little-serve as sound approaches for marketing and other business objectives. Using the tools of inferential statistics, you can understand the way probability works, discover relationships, predict events with uncanny accuracy, and even make a little money with a well-placed wager here and there.

Statistics Hacks presents useful techniques from statistics, educational and psychological measurement, and experimental research to help you solve a variety of problems in business, games, and life. You'll learn how to:

Play smart when you play Texas Hold 'Em, blackjack, roulette, dice games, or even the lotteryDesign your own winnable bar bets to make money and amaze your friendsPredict the outcomes of baseball games, know when to "go for two" in football, and anticipate the winners of other sporting events with surprising accuracyDemystify amazing coincidences and distinguish the truly random from the only seemingly random--even keep your iPod's "random" shuffle honestSpot fraudulent data, detect plagiarism, and break codesHow to isolate the effects of observation on the thing observedWhether you're a statistics enthusiast who does calculations in your sleep or a civilian who is entertained by clever solutions to interesting problems, Statistics Hacks has tools to give you an edge over the world's slim odds.

Packed with fresh and practical examples appropriate for a range of degree-seeking students, Statistics II For Dummies helps any reader succeed in an upper-level statistics course. It picks up with data analysis where Statistics For Dummies left off, featuring new and updated examples, real-world applications, and test-taking strategies for success. This easy-to-understand guide covers such key topics as sorting and testing models, using regression to make predictions, performing variance analysis (ANOVA), drawing test conclusions with chi-squares, and making comparisons with the Rank Sum Test.

addresses tasks that nearly every SAS programmer needs to do - that is, make

sure that data errors are located and corrected. This book develops and

demonstrates data cleaning programs and macros that you can use as written or

modify for your own special data cleaning needs.

Bassetti, a client, friend, and student of John Magee, one of the original authors, has converted the material on the craft of manual charting with TEKNIPLAT chart paper to modern computer software methods. In actuality, none of Magee’s concepts have proven invalid and some of his work predated modern concepts such as beta and volatility. In addition, Magee described a trend-following procedure that is so simple and so elegant that Bassetti has adapted it to enable the general investor to use it to replace the cranky Dow Theory. This procedure, called the Basing Points procedure, is extensively described in the new Tenth Edition along with new material on powerful moving average systems and Leverage Space Portfolio Model generously contributed by the formidable analyst, Ralph Vince., author of Handbook of Portfolio Mathematics.

See what’s new in the Tenth Edition:

Chapters on replacing Dow Theory Update of Dow Theory Record Deletion of extraneous material on manual charting New chapters on Stops and Basing Points New material on moving average systems New material on Ralph Vince’s Leverage Space Portfolio Model

So much has changed since the first edition, yet so much has remained the same. Everyone wants to know how to play the game. The foundational work of the discipline of technical analysis, this book gives you more than a technical formula for trading and investing, it gives you the knowledge and wisdom to craft long-term success.

The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the traditional graphics functions in the base package and introduce more sophisticated graphical displays available through the lattice and ggplot2 packages. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and fielding measures. Each chapter contains exercises that encourage readers to perform their own analyses using R. All of the datasets and R code used in the text are available online.

This book helps readers answer questions about baseball teams, players, and strategy using large, publically available datasets. It offers detailed instructions on downloading the datasets and putting them into formats that simplify data exploration and analysis. Through the book’s various examples, readers will learn about modern sabermetrics and be able to conduct their own baseball analyses.

- Calculating descriptive statistics

- Measures of central tendency: mean, median, and mode

- Probability

- Variance analysis

- Inferential statistics

- Hypothesis testing

- Organizing data into statistical charts and tables

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

· Downloadable data sets

· Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more

· Additional material for data analysis

RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time.

Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer’s memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R’s package system and debugging toolsPractice and apply R programming concepts as you learn themHate math? No sweat. You’ll be amazed at how little you need. Like math? Optional "Equation Blackboard" sections reveal the mathematical foundations of statistics right before your eyes. If you need to understand, evaluate, or use statistics in business, academia, or anywhere else, this is the book you've been searching for!

It focuses on genuine research studies, active learning, and effective use of technology. Simulations and randomization tests introduce statistical inference, yielding a strong conceptual foundation that bridges students to theory-based inference approaches. Repetition allows students to see the logic and scope of inference. This implementation follows the GAISE recommendations endorsed by the American Statistical Association.

Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more.

R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide.

Covers downloading, installing, and configuring R Includes tips for getting data in and out of R Offers advice on fitting regression models and ANOVA Provides helpful hints for working with graphicsR For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.

Amy Langville and Carl Meyer provide the first comprehensive overview of the mathematical algorithms and methods used to rate and rank sports teams, political candidates, products, Web pages, and more. In a series of interesting asides, Langville and Meyer provide fascinating insights into the ingenious contributions of many of the field's pioneers. They survey and compare the different methods employed today, showing why their strengths and weaknesses depend on the underlying goal, and explaining why and when a given method should be considered. Langville and Meyer also describe what can and can't be expected from the most widely used systems.

The science of rating and ranking touches virtually every facet of our lives, and now you don't need to be an expert to understand how it really works. Who's #1? is the definitive introduction to the subject. It features easy-to-understand examples and interesting trivia and historical facts, and much of the required mathematics is included.

Among the topics included are how to combine plot statements to create custom graphs; customizing graph axes, legends, and insets; advanced features, such as annotation and attribute maps; tips and tricks for creating the optimal graph for the intended usage; real-world examples from the health and life sciences domain; and ODS styles.

The procedures in "Statistical Graphics Procedures by Example" are specifically designed for the creation of analytical graphs. That makes this book a must-read for analysts and statisticians in the health care, clinical trials, financial, and insurance industries. However, you will find that the examples here apply to all fields.

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice.

New to the Third Edition

Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code

The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

". . . [this book] should be on the shelf of everyone interested in . . . longitudinal data analysis."

—Journal of the American Statistical Association

Features newly developed topics and applications of the analysis of longitudinal data

Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of longitudinal data that can be applied across various fields of study, from the health and medical sciences to the social and behavioral sciences.

The authors incorporate their extensive academic and research experience along with various updates that have been made in response to reader feedback. The Second Edition features six newly added chapters that explore topics currently evolving in the field, including:

Fixed effects and mixed effects models Marginal models and generalized estimating equations Approximate methods for generalized linear mixed effects models Multiple imputation and inverse probability weighted methods Smoothing methods for longitudinal data Sample size and powerEach chapter presents methods in the setting of applications to data sets drawn from the health sciences. New problem sets have been added to many chapters, and a related website features sample programs and computer output using SAS, Stata, and R, as well as data sets and supplemental slides to facilitate a complete understanding of the material.

With its strong emphasis on multidisciplinary applications and the interpretation of results, Applied Longitudinal Analysis, Second Edition is an excellent book for courses on statistics in the health and medical sciences at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for researchers and professionals in the medical, public health, and pharmaceutical fields as well as those in social and behavioral sciences who would like to learn more about analyzing longitudinal data.

The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other.

Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R.

The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn:

The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory-efficient codeThis book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.

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.

Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics so you can understand key points and actually use them. Learn to present data visually with charts and plots; discover the difference between taking the average with mean, median, and mode, and why it's important; learn how to calculate probability and expectation; and much more.

Head First Statistics is ideal for high school and college students taking statistics and satisfies the requirements for passing the College Board's Advanced Placement (AP) Statistics Exam. With this book, you'll:

Study the full range of topics covered in first-year statisticsTackle tough statistical concepts using Head First's dynamic, visually rich format proven to stimulate learning and help you retain knowledge Explore real-world scenarios, ranging from casino gambling to prescription drug testing, to bring statistical principles to lifeDiscover how to measure spread, calculate odds through probability, and understand the normal, binomial, geometric, and Poisson distributionsConduct sampling, use correlation and regression, do hypothesis testing, perform chi square analysis, and more

Before you know it, you'll not only have mastered statistics, you'll also see how they work in the real world. Head First Statistics will help you pass your statistics course, and give you a firm understanding of the subject so you can apply the knowledge throughout your life.