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.
Fooled by Randomness is the word-of-mouth sensation that will change the way you think about business and the world. Nassim Nicholas Taleb–veteran trader, renowned risk expert, polymathic scholar, erudite raconteur, and New York Times bestselling author of The Black Swan–has written a modern classic that turns on its head what we believe about luck and skill.
This book is about luck–or more precisely, about how we perceive and deal with luck in life and business. Set against the backdrop of the most conspicuous forum in which luck is mistaken for skill–the world of trading–Fooled by Randomness provides captivating insight into one of the least understood factors in all our lives. Writing in an entertaining narrative style, the author tackles major intellectual issues related to the underestimation of the influence of happenstance on our lives.
The book is populated with an array of characters, some of whom have grasped, in their own way, the significance of chance: the baseball legend Yogi Berra; the philosopher of knowledge Karl Popper; the ancient world’s wisest man, Solon; the modern financier George Soros; and the Greek voyager Odysseus. We also meet the fictional Nero, who seems to understand the role of randomness in his professional life but falls victim to his own superstitious foolishness.
However, the most recognizable character of all remains unnamed–the lucky fool who happens to be in the right place at the right time–he embodies the “survival of the least fit.” Such individuals attract devoted followers who believe in their guru’s insights and methods. But no one can replicate what is obtained by chance.
Are we capable of distinguishing the fortunate charlatan from the genuine visionary? Must we always try to uncover nonexistent messages in random events? It may be impossible to guard ourselves against the vagaries of the goddess Fortuna, but after reading Fooled by Randomness we can be a little better prepared.
PRAISE FOR FOOLED BY RANDOMNESS:
Named by Fortune One of the Smartest Books of All Time
A Financial Times Best Business Book of the Year
“[Fooled by Randomness] is to conventional Wall Street wisdom approximately what Martin Luther’s ninety-five theses were to the Catholic Church.”
–Malcolm Gladwell, author of Blink
“The book that rolled down Wall Street like a hand grenade.”
–Maggie Mahar, author of Bull! A History of the Boom, 1982—1999
“Fascinating . . . Taleb will grab you.”
–Peter L. Bernstein, author of Capital Ideas Evolving
“Recalls the best of scientist/essayists like Richard Dawkins . . . and Stephen Jay Gould.”
–Michael Schrage, author of Serious Play: How the World’s Best Companies Simulate to Innovate
“We need a book like this. . . . Fun to read, refreshingly independent-minded.”
–Robert J. Shiller, author of Irrational Exuberance
“Powerful . . . loaded with crackling little insights [and] extreme brilliance.”
New York Times Bestseller
A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life — and threaten to rip apart our social fabric
We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated.
But as Cathy O’Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.
Tracing the arc of a person’s life, O’Neil exposes the black box models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.
O’Neil calls on modelers to take more responsibility for their algorithms and on policy makers to regulate their use. But in the end, it’s up to us to become more savvy about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.
— Longlist for National Book Award (Non-Fiction)
— Goodreads, semi-finalist for the 2016 Goodreads Choice Awards (Science and Technology)
— Kirkus, Best Books of 2016
— New York Times, 100 Notable Books of 2016 (Non-Fiction)
— The Guardian, Best Books of 2016
— WBUR's "On Point," Best Books of 2016: Staff Picks
— Boston Globe, Best Books of 2016, Non-Fiction
This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without.Understand Lean Startup, analytics fundamentals, and the data-driven mindsetLook at six sample business models and how they map to new ventures of all sizesFind the One Metric That Matters to youLearn how to draw a line in the sand, so you’ll know it’s time to move forwardApply Lean Analytics principles to large enterprises and established products
This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates
Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions.
By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable.
Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women?
Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.
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.
It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills—and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These “bots” started with human programming and logic, but now their reach extends beyond what their creators ever expected.
In this fascinating, frightening book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge.
The May 2010 “Flash Crash” exposed Wall Street’s reliance on trading bots to the tune of a 998-point market drop and $1 trillion in vanished market value. But that was just the beginning. In Automate This, we meet bots that are driving cars, penning haiku, and writing music mistaken for Bach’s. They listen in on our customer service calls and figure out what Iran would do in the event of a nuclear standoff. There are algorithms that can pick out the most cohesive crew of astronauts for a space mission or identify the next Jeremy Lin. Some can even ingest statistics from baseball games and spit out pitch-perfect sports journalism indistinguishable from that produced by humans.
The interaction of man and machine can make our lives easier. But what will the world look like when algorithms control our hospitals, our roads, our culture, and our national security? What happens to businesses when we automate judgment and eliminate human instinct? And what role will be left for doctors, lawyers, writers, truck drivers, and many others?Who knows—maybe there’s a bot learning to do your job this minute.
Complexity surrounds us. We have too much email, juggle multiple remotes, and hack through thickets of regulations from phone contracts to health plans. But complexity isn’t destiny. Sull and Eisenhardt argue there’s a better way. By developing a few simple yet effective rules, people can best even the most complex problems.
In Simple Rules, Sull and Eisenhardt masterfully challenge how we think about complexity and offer a new lens on how to cope. They take us on a surprising tour of what simple rules are, where they come from, and why they work. The authors illustrate the six kinds o f rules that really matter - for helping artists find creativity and the Federal Reserve set interest rates, for keeping birds on track and Zipcar members organized, and for how insomniacs can sleep and mountain climbers stay safe.
Drawing on rigorous research and riveting stories, the authors ingeniously find insights in unexpected places, from the way Tina Fey codified her experience at Saturday Night Live into rules for producing 30 Rock (rule five: never tell a crazy person he’s crazy) to burglars’ rules for robbery (“avoid houses with a car parked outside”) to Japanese engineers mimicking the rules of slime molds to optimize Tokyo’s rail system. The authors offer fresh information and practical tips on fixing old rules and learning new ones.
Whether you’re struggling with information overload, pursuing opportunities with limited resources, or just trying to change your bad habits, Simple Rules provides powerful insight into how and why simplicity tames complexity.
We’re surrounded by fringe theories, fake news, and pseudo-facts. These lies are getting repeated. New York Times bestselling author Daniel Levitin shows how to disarm these socially devastating inventions and get the American mind back on track. Here are the fundamental lessons in critical thinking that we need to know and share now.
Investigating numerical misinformation, Daniel Levitin shows how mishandled statistics and graphs can give a grossly distorted perspective and lead us to terrible decisions. Wordy arguments on the other hand can easily be persuasive as they drift away from the facts in an appealing yet misguided way. The steps we can take to better evaluate news, advertisements, and reports are clearly detailed. Ultimately, Levitin turns to what underlies our ability to determine if something is true or false: the scientific method. He grapples with the limits of what we can and cannot know. Case studies are offered to demonstrate the applications of logical thinking to quite varied settings, spanning courtroom testimony, medical decision making, magic, modern physics, and conspiracy theories.
This urgently needed book enables us to avoid the extremes of passive gullibility and cynical rejection. As Levitin attests: Truth matters. A post-truth era is an era of willful irrationality, reversing all the great advances humankind has made. Euphemisms like “fringe theories,” “extreme views,” “alt truth,” and even “fake news” can literally be dangerous. Let's call lies what they are and catch those making them in the act.
Perform powerful data analysis with DAX for Microsoft SQL Server Analysis Services, Excel, and Power BI
Master core DAX concepts, including calculated columns, measures, and error handling Understand evaluation contexts and the CALCULATE and CALCULATETABLE functions Perform time-based calculations: YTD, MTD, previous year, working days, and more Work with expanded tables, complex functions, and elaborate DAX expressions Perform calculations over hierarchies, including parent/child hierarchies Use DAX to express diverse and unusual relationships Measure DAX query performance with SQL Server Profiler and DAX Studio
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.
How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way–like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one!
By reading this book, you will:
• Gain an understanding of the basics of data modeling, including tables, relationships, and keys
• Familiarize yourself with star schemas, snowflakes, and common modeling techniques
• Learn the importance of granularity
• Discover how to use multiple fact tables, like sales and purchases, in a complex data model
• Manage calendar-related calculations by using date tables
• Track historical attributes, like previous addresses of customers or manager assignments
• Use snapshots to compute quantity on hand
• Work with multiple currencies in the most efficient way
• Analyze events that have durations, including overlapping durations
• Learn what data model you need to answer your specific business questions
About This Book
• For Excel and Power BI users who want to exploit the full power of their favorite tools
• For BI professionals seeking new ideas for modeling data
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book.
Master business modeling and analysis techniques with Microsoft Excel 2016, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands on, scenario-focused guide helps you use Excel’s newest tools to ask the right questions and get accurate, actionable answers. This edition adds 150+ new problems with solutions, plus a chapter of basic spreadsheet models to make sure you’re fully up to speed.
Solve real business problems with Excel–and build your competitive advantageQuickly transition from Excel basics to sophisticated analytics Summarize data by using PivotTables and Descriptive Statistics Use Excel trend curves, multiple regression, and exponential smoothing Master advanced functions such as OFFSET and INDIRECT Delve into key financial, statistical, and time functions Leverage the new charts in Excel 2016 (including box and whisker and waterfall charts) Make charts more effective by using Power View Tame complex optimizations by using Excel Solver Run Monte Carlo simulations on stock prices and bidding models Work with the AGGREGATE function and table slicers Create PivotTables from data in different worksheets or workbooks Learn about basic probability and Bayes’ Theorem Automate repetitive tasks by using macros
Marketing Metrics: The Definitive Guide to Measuring Marketing Performance, Second Edition, is the definitive guide to today’s most valuable marketing metrics. In this thoroughly updated and significantly expanded book, four leading marketing researchers show exactly how to choose the right metrics for every challenge and expand their treatment of social marketing, web metrics, and brand equity. They also give readers new systems for organizing marketing metrics into models and dashboards that translate numbers into management insight.
The authors show how to use marketing dashboards to view market dynamics from multiple perspectives, maximize accuracy, and “triangulate” to optimal solutions. You’ll discover high-value metrics for virtually every facet of marketing: promotional strategy, advertising, and distribution; customer perceptions; market share; competitors’ power; margins and pricing; products and portfolios; customer profitability; sales forces and channels; and more. For every metric, the authors present real-world pros, cons, and tradeoffs--and help you understand what the numbers really mean.
This edition introduces essential new metrics ranging from Net Promoter to social media and brand equity measurement. Last, but not least, it shows how to build comprehensive models to support planning--and optimize every marketing decision you make:
· Understand the full spectrum of marketing metrics: pros, cons, nuances, and application
· Quantify the profitability of products, customers, channels, and marketing initiatives
· Measure everything from “bounce rates” to the growth of your web communities
· Understand your true return on marketing investment--and enhance it
This award-winning book will show you how to apply the right metrics to all your marketing investments, get accurate answers, and use them to systematically improve ROI.
This insightful and eloquent book will show you how to measure those things in your own business, government agency or other organization that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI.Adds new measurement methods, showing how they can be applied to a variety of areas such as risk management and customer satisfaction Simplifies overall content while still making the more technical applications available to those readers who want to dig deeper Continues to boldly assert that any perception of "immeasurability" is based on certain popular misconceptions about measurement and measurement methods Shows the common reasoning for calling something immeasurable, and sets out to correct those ideas Offers practical methods for measuring a variety of "intangibles" Provides an online database (www.howtomeasureanything.com) of downloadable, practical examples worked out in detailed spreadsheets
Written by recognized expert Douglas Hubbard—creator of Applied Information Economics—How to Measure Anything, Third Edition illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.
Hate 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!
- Create pivot tables from worksheet databases.
- Rearrange pivot tables by dragging, swapping, and nesting fields.
- Customize pivot tables with styles, layouts, totals, and subtotals.
- Combine numbers, dates, times, or text values into custom groups.
- Calculate common statistics or create custom formulas.
- Filter data that you don't want to see.
- Create and customize pivot charts.
- Unlink a pivot table from its source data.
- Control references to pivot table cells.
- Plenty of tips, tricks, and timesavers.
- Fully cross-referenced, linked, and searchable.
1. Pivot Table Basics
2. Nesting Fields
3. Grouping Items
4. Calculations and Custom Formulas
5. Filtering Data
6. Charting Pivot Tables
7. Tricks with Pivot Tables
Updated throughout, this edition contains new chapters assessing the current options landscape, discussing margin collateral issues, and introducing Cohen’s exceptionally valuable OVI indicators.
The Bible of Options Strategies, Second Editionis practical from start to finish: modular, easy to navigate, and thoroughly cross-referenced, so you can find what you need fast, and act before your opportunity disappears. Cohen systematically covers every key area of options strategy: income strategies, volatility strategies, sideways market strategies, leveraged strategies, and synthetic strategies.
Even the most complex techniques are explained with unsurpassed clarity – making them accessible to any trader with even modest options experience. More than an incredible value, this is the definitive reference to contemporary options trading: the one book you need by your side whenever you trade. For all options traders with at least some experience.
So why is it so hard to make sound decisions? In Think Twice, now in paperback, Michael Mauboussin argues that we often fall victim to simplified mental routines that prevent us from coping with the complex realities inherent in important judgment calls. Yet these cognitive errors are preventable.
In this engaging book, Mauboussin shows us how to recognize and avoid common mental missteps. These include misunderstanding cause-and-effect linkages, not considering enough alternative possibilities in making a decision, and relying too much on experts.
Through vivid stories, the author presents memorable rules for avoiding each error and explains how to recognize when you should “think twice”—questioning your reasoning and adopting decision-making strategies that are far more effective, even if they seem counterintuitive. Armed with this awareness, you'll soon begin making sounder judgment calls that benefit (rather than hurt) your organization.
Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?
Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.
You'll learn how to:Identify the metrics you need to measureRun experiments and A/B testsAsk the right questions of your data expertsUnderstand statistical terms and conceptsCreate effective charts and visualizationsAvoid common mistakes
New to This Edition
*Extensively revised to cover important new topics: Pearl's graphing theory and the SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more.
*Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping.
*Expanded coverage of psychometrics.
*Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan).
*Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models.
*Exercises with answers, plus end-of-chapter annotated lists of further reading.
*Real examples of troublesome data, demonstrating how to handle typical problems in analyses.
*Topic boxes on specialized issues, such as causes of nonpositive definite correlations.
*Boxed rules to remember.
*Website promoting a learn-by-doing approach, including syntax and data files for six widely used SEM computer tools.
New to This Edition
*Chapters on using each type of analysis with multicategorical antecedent variables.
*Example analyses using PROCESS v3, with annotated outputs throughout the book.
*More tips and advice, including new or revised discussions of formally testing moderation of a mechanism using the index of moderated mediation; effect size in mediation analysis; comparing conditional effects in models with more than one moderator; using R code for visualizing interactions; distinguishing between testing interaction and probing it; and more.
*Rewritten Appendix A, which provides the only documentation of PROCESS v3, including 13 new preprogrammed models that combine moderation with serial mediation or parallel and serial mediation.
*Appendix B, describing how to create customized models in PROCESS v3 or edit preprogrammed models.
New to the fourth edition are the topics of common and special causes, outliers, and risk management tools. Besides the new topics, many current topics have been expanded to reflect changes in auditing practices since 2004 and ISO 19011 guidance, and they have been rewritten to promote the common elements of all types of system and process audits.
The handbook can be used by new auditors to gain an understanding of auditing. Experienced auditors will find it to be a useful reference. Audit managers and quality managers can use the handbook as a guide for leading their auditing programs. The handbook may also be used by trainers and educators as source material for teaching the fundamentals of auditing.
In the late 1980s, Japanese scientists were trying to figure out the economic damage that would be caused if a catastrophic earthquake destroyed Tokyo. The answer was bleak, but not for Japan. Kaoru Oda, an economist who worked for Tokai Bank, speculated that the United States would end up paying the most. Why? Japan owned trillions of dollars’ worth of foreign liquid assets and investments. These assets, which the world depended on, would be sold, forcing countries into the precarious position of having to return large amounts of money they might not have. After the recent earthquake, Michael Lewis reexamined this hypothesis and came to a surprising conclusion. With his characteristic sense of humor and wit, Lewis, once again, explains the inner workings of a financial catastrophe.
“How a Tokyo Earthquake Could Devastate Wall Street” appears in Michael Lewis’s book The Money Culture.
The movie Moneyball made predictive analytics famous: Now you can apply the same techniques to help your business win. You don’t need multimillion-dollar software: All the tools you need are available in Microsoft Excel, and all the knowledge and skills are right here, in this book!
Microsoft Excel MVP Conrad Carlberg shows you how to use Excel predictive analytics to solve real-world problems in areas ranging from sales and marketing to operations. Carlberg offers unprecedented insight into building powerful, credible, and reliable forecasts, showing how to gain deep insights from Excel that would be difficult to uncover with costly tools such as SAS or SPSS.
You’ll get an extensive collection of downloadable Excel workbooks you can easily adapt to your own unique requirements, plus VBA code—much of it open-source—to streamline several of this book’s most complex techniques.
Step by step, you’ll build on Excel skills you already have, learning advanced techniques that can help you increase revenue, reduce costs, and improve productivity. By mastering predictive analytics, you’ll gain a powerful competitive advantage for your company and yourself.
• Learn both the “how” and “why” of using data to make better tactical decisions
• Choose the right analytics technique for each problem
• Use Excel to capture live real-time data from diverse sources, including third-party websites
• Use logistic regression to predict behaviors such as “will buy” versus “won’t buy”
• Distinguish random data bounces from real, fundamental changes
• Forecast time series with smoothing and regression
• Construct more accurate predictions by using Solver to find maximum likelihood estimates
• Manage huge numbers of variables and enormous datasets with principal components analysis and Varimax factor rotation
• Apply ARIMA (Box-Jenkins) techniques to build better forecasts and understand their meaning
How to Measure Anything in Cybersecurity Risk exposes the shortcomings of current "risk management" practices, and offers a series of improvement techniques that help you fill the holes and ramp up security. In his bestselling book How to Measure Anything, author Douglas W. Hubbard opened the business world's eyes to the critical need for better measurement. This book expands upon that premise and draws from The Failure of Risk Management to sound the alarm in the cybersecurity realm. Some of the field's premier risk management approaches actually create more risk than they mitigate, and questionable methods have been duplicated across industries and embedded in the products accepted as gospel. This book sheds light on these blatant risks, and provides alternate techniques that can help improve your current situation. You'll also learn which approaches are too risky to save, and are actually more damaging than a total lack of any security.
Dangerous risk management methods abound; there is no industry more critically in need of solutions than cybersecurity. This book provides solutions where they exist, and advises when to change tracks entirely.Discover the shortcomings of cybersecurity's "best practices"Learn which risk management approaches actually create riskImprove your current practices with practical alterationsLearn which methods are beyond saving, and worse than doing nothing
Insightful and enlightening, this book will inspire a closer examination of your company's own risk management practices in the context of cybersecurity. The end goal is airtight data protection, so finding cracks in the vault is a positive thing—as long as you get there before the bad guys do. How to Measure Anything in Cybersecurity Risk is your guide to more robust protection through better quantitative processes, approaches, and techniques.
—Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden
"This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade."
—Daniel Barbara, George Mason University, Fairfax, Virginia, USA
"The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing ‘just in time’ the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts."
—Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark
"I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength...Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months."
—David Clifton, University of Oxford, UK
"The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book."
—Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK
"This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning...The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective."
—Guangzhi Qu, Oakland University, Rochester, Michigan, USA
The sixth edition is no exception. It provides an accessible, comprehensive introduction to the theory and practice of time series analysis. The treatment covers a wide range of topics, including ARIMA probability models, forecasting methods, spectral analysis, linear systems, state-space models, and the Kalman filter. It also addresses nonlinear, multivariate, and long-memory models. The author has carefully updated each chapter, added new discussions, incorporated new datasets, and made those datasets available for download from www.crcpress.com. A free online appendix on time series analysis using R can be accessed at http://people.bath.ac.uk/mascc/TSA.usingR.doc.
Highlights of the Sixth Edition:A new section on handling real data New discussion on prediction intervals A completely revised and restructured chapter on more advanced topics, with new material on the aggregation of time series, analyzing time series in finance, and discrete-valued time series A new chapter of examples and practical advice Thorough updates and revisions throughout the text that reflect recent developments and dramatic changes in computing practices over the last few years
The analysis of time series can be a difficult topic, but as this book has demonstrated for two-and-a-half decades, it does not have to be daunting. The accessibility, polished presentation, and broad coverage of The Analysis of Time Series make it simply the best introduction to the subject available.
This pocket guide is designed to be a quick, on-the-job reference for anyone interested in making their workplace more effective and efficient. It will provide a solid initial overview of what “quality” is and how it could impact you and your organization. Use it to compare how you and your organization are doing things, and to see whether what’s described in the guide might be useful.
The tools of quality described herein are universal. People across the world need to find better, more effective ways to improve the creation and performance of products and services. Since organizational and process improvement is increasingly integrated into all areas of an organization, everyone must understand the basic principles of process control and process improvement. This succinct and concentrated guide can help.
Unlike any other pocket guide on the market, included throughout are direct links to numerous free online resources that not only go deeper but also to show these concepts and tools in action: case studies, articles, webcasts, templates, tutorials, examples from the ASQ Service Division’s Service Quality Body of Knowledge (SQBOK), and much more. This pocket guide serves as a gateway into the wealth of peerless content that ASQ offers.
Nationally recognized Excel expert Conrad Carlberg shows you how to use Excel 2016 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples and downloadable workbooks, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features. Along the way, he clarifies confusing statistical terminology and helps you avoid common mistakes.
You’ll learn how to use correlation and regression, analyze variance and covariance, and test statistical hypotheses using the normal, binomial, t, and F distributions. To help you make accurate inferences based on samples from a population, Carlberg offers insightful coverage of crucial topics ranging from experimental design to the statistical power of F tests. Updated for Excel 2016, this guide covers both modern consistency functions and legacy compatibility functions.
Becoming an expert with Excel statistics has never been easier! In this book, you’ll find crystal-clear instructions, insider insights, and complete step-by-step guidance.
As the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of increasingly complex problems.
Learn from the Creators of the RapidMiner Software
Written by leaders in the data mining community, including the developers of the RapidMiner software, RapidMiner: Data Mining Use Cases and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. It presents the most powerful and flexible open source software solutions: RapidMiner and RapidAnalytics. The software and their extensions can be freely downloaded at www.RapidMiner.com.
Understand Each Stage of the Data Mining Process
The book and software tools cover all relevant steps of the data mining process, from data loading, transformation, integration, aggregation, and visualization to automated feature selection, automated parameter and process optimization, and integration with other tools, such as R packages or your IT infrastructure via web services. The book and software also extensively discuss the analysis of unstructured data, including text and image mining.
Easily Implement Analytics Approaches Using RapidMiner and RapidAnalytics
Each chapter describes an application, how to approach it with data mining methods, and how to implement it with RapidMiner and RapidAnalytics. These application-oriented chapters give you not only the necessary analytics to solve problems and tasks, but also reproducible, step-by-step descriptions of using RapidMiner and RapidAnalytics. The case studies serve as blueprints for your own data mining applications, enabling you to effectively solve similar problems.
Crunch Big Data to optimize marketing and more!
Overwhelmed by all the Big Data now available to you? Not sure what questions to ask or how to ask them? Using Microsoft Excel and proven decision analytics techniques, you can distill all that data into manageable sets—and use them to optimize a wide variety of business and investment decisions. In Decision Analytics: Microsoft Excel, best selling statistics expert and consultant Conrad Carlberg will show you how—hands-on and step-by-step.
Carlberg guides you through using decision analytics to segment customers (or anything else) into sensible and actionable groups and clusters. Next, you’ll learn practical ways to optimize a wide spectrum of decisions in business and beyond—from pricing to cross-selling, hiring to investments—even facial recognition software uses the techniques discussed in this book!
Through realistic examples, Carlberg helps you understand the techniques and assumptions that underlie decision analytics and use simple Excel charts to intuitively grasp the results. With this foundation in place, you can perform your own analyses in Excel and work with results produced by advanced stats packages such as SAS and SPSS.
This book comes with an extensive collection of downloadable Excel workbooks you can easily adapt to your own unique requirements, plus VBA code to streamline several of its most complex techniques.Classify data according to existing categories or naturally occurring clusters of predictor variables Cut massive numbers of variables and records down to size, so you can get the answers you really need Utilize cluster analysis to find patterns of similarity for market research and many other applications Learn how multiple discriminant analysis helps you classify cases Use MANOVA to decide whether groups differ on multivariate centroids Use principal components to explore data, find patterns, and identify latent factors
Register your book for access to all sample workbooks, updates, and corrections as they become available at quepublishing.com/title/9780789751683.
Learn everything you need to know to start using business analytics and integrating it throughout your organization.
Business Analytics Principles, Concepts, and Applications with SASbrings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives.
They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making.
Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning.
Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself.
Business Analytics Principles, Concepts, and Applications with SASwill be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.
New to This Edition
*Updated throughout to incorporate important developments in latent variable modeling.
*Chapter on Bayesian CFA and multilevel measurement models.
*Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables.
*Utilizes the latest versions of major latent variable software packages.
Highlighting both underlying concepts and practicalcomputational skills, Data Mining and Business Analytics withR begins with coverage of standard linear regression and theimportance of parsimony in statistical modeling. The book includesimportant topics such as penalty-based variable selection (LASSO);logistic regression; regression and classification trees;clustering; principal components and partial least squares; and theanalysis of text and network data. In addition, the bookpresents:
• A thorough discussion and extensive demonstration of thetheory behind the most useful data mining tools
• Illustrations of how to use the outlined concepts inreal-world situations
• Readily available additional data sets and related Rcode allowing readers to apply their own analyses to the discussedmaterials
• Numerous exercises to help readers with computing skillsand deepen their understanding of the material
Data Mining and Business Analytics with R is an excellentgraduate-level textbook for courses on data mining and businessanalytics. The book is also a valuable reference for practitionerswho collect and analyze data in the fields of finance, operationsmanagement, marketing, and the information sciences.
Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now.
Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories.
Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing.
You’ll master data science by answering fascinating questions, such as:
• Are religious individuals more or less likely to have extramarital affairs?
• Do attractive professors get better teaching evaluations?
• Does the higher price of cigarettes deter smoking?
• What determines housing prices more: lot size or the number of bedrooms?
• How do teenagers and older people differ in the way they use social media?
• Who is more likely to use online dating services?
• Why do some purchase iPhones and others Blackberry devices?
• Does the presence of children influence a family’s spending on alcohol?
For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how
others have approached similar challenges; selecting your data and methods; generating your statistics;
organizing your report; and telling your story. Throughout, the focus is squarely on what matters most:
transforming data into insights that are clear, accurate, and can be acted upon.
*Includes worked-through, substantive examples, using large-scale educational and social science databases, such as PISA (Program for International Student Assessment) and the LSAY (Longitudinal Study of American Youth).
*Utilizes open-source R software programs available on CRAN (such as MCMCpack and rjags); readers do not have to master the R language and can easily adapt the example programs to fit individual needs.
*Shows readers how to carefully warrant priors on the basis of empirical data.
*Companion website features data and code for the book's examples, plus other resources.
The aim of this book is to show how R can be used as the software tool in the development of Six Sigma projects. The book includes a gentle introduction to Six Sigma and a variety of examples showing how to use R within real situations. It has been conceived as a self contained piece. Therefore, it is addressed not only to Six Sigma practitioners, but also to professionals trying to initiate themselves in this management methodology. The book may be used as a text book as well.
Each chapter features background information, boldfaced key terms defined in the glossary, detailed interpretations of R output, descriptions of how to write the analysis of results for publication, a summary, R based practice exercises (with solutions included in the back of the book), and references and related readings. Margin notes help readers better understand LVMs and write their own R syntax. Examples using data from published work across a variety of disciplines demonstrate how to use R syntax for analyzing and interpreting results. R functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R functions, packages, and datasets. The book and accompanying website at http://blogs.baylor.edu/rlatentvariable/ provides all of the data for the book’s examples and exercises as well as R syntax so readers can replicate the analyses. The book reviews how to enter the data into R, specify the LVMs, and obtain and interpret the estimated parameter values.
The book opens with the fundamentals of using R including how to download the program, use functions, and enter and manipulate data. Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period. Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. The final chapter examines hierarchical LVMs, demonstrating both higher-order and bi-factor approaches. The book concludes with three Appendices: a review of common measures of model fit including their formulae and interpretation; syntax for other R latent variable models packages; and solutions for each chapter’s exercises.
Intended as a supplementary text for graduate and/or advanced undergraduate courses on latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, business, economics, and social and health sciences, this book also appeals to researchers in these fields. Prerequisites include familiarity with basic statistical concepts, but knowledge of R is not assumed.
Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Selected by the Market Technicians Association as the official companion to its prestigious Chartered Market Technician (CMT) program, Technical Analysis, Third Edition systematically explains the theory of technical analysis, presenting academic evidence both for and against it. Using hundreds of fully updated illustrations and examples, the authors explain the analysis of both markets and individual issues, and present complete investment systems and portfolio management plans. They present authoritative, up-to-date coverage of tested sentiment, momentum indicators, seasonal effects, flow of funds, testing systems, risk mitigation strategies, and many other topics.
Offering 30% new coverage, Technical Analysis, Third Edition thoroughly addresses recent advances in pattern recognition, market analysis, systems management, and confidence testing; Kagi, Renko, Kase, Ichimoku, Clouds, and DeMark indicators; innovations in exit stops, portfolio selection, and testing; implications of behavioral bias, and the recent performance of old formulas and methods. For traders, researchers, and serious investors alike, this is the definitive guide to profiting from technical analysis.
Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons.
Business Statistics For Dummies tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, with lots of examples that shows you how these concepts apply to the world of global business and economics.Shows you how to use statistical data to get an informed and unbiased picture of the marketServes as an excellent supplement to classroom learningHelps you score your highest in your Business Statistics course
If you're studying business at the university level or you're a professional looking for a desk reference on this complicated topic, Business Statistics For Dummies has you covered.
Operational Risk: Modeling Analytics is organized around theprinciple that the analysis of operational risk consists, in part,of the collection of data and the building of mathematical modelsto describe risk. This book is designed to provide risk analystswith a framework of the mathematical models and methods used in themeasurement and modeling of operational risk in both the bankingand insurance sectors.
Beginning with a foundation for operational risk modeling and afocus on the modeling process, the book flows logically todiscussion of probabilistic tools for operational risk modeling andstatistical methods for calibrating models of operational risk.Exercises are included in chapters involving numerical computationsfor students' practice and reinforcement of concepts.
Written by Harry Panjer, one of the foremost authorities in theworld on risk modeling and its effects in business management, thisis the first comprehensive book dedicated to the quantitativeassessment of operational risk using the tools of probability,statistics, and actuarial science.
In addition to providing great detail of the many probabilistic andstatistical methods used in operational risk, this bookfeatures:
* Ample exercises to further elucidate the concepts in thetext
* Definitive coverage of distribution functions and relatedconcepts
* Models for the size of losses
* Models for frequency of loss
* Aggregate loss modeling
* Extreme value modeling
* Dependency modeling using copulas
* Statistical methods in model selection and calibration
Assuming no previous expertise in either operational riskterminology or in mathematical statistics, the text is designed forbeginning graduate-level courses on risk and operational managementor enterprise risk management. This book is also useful as areference for practitioners in both enterprise risk management andrisk and operational management.