The interviewers use the same questions year-after-year and here they are---with solutions! These questions come from all types of interviews (corporate finance, sales and trading, quant research, etc), but they are especially likely in quantitative capital markets job interviews. The questions come from all levels of interviews (undergrad, MBA, PhD), but they are especially likely if you have, or almost have, an MS or MBA. The latest edition includes over 120 non-quantitative actual interview questions, and a new section on interview technique---based partly on Dr. Crack's experiences interviewing candidates for the world's largest institutional asset manager. Dr. Crack has a PhD from MIT. He has won many teaching awards and has publications in the top academic, practitioner, and teaching journals in finance. He has degrees in Mathematics/Statistics, Finance, and Financial Economics and a diploma in Accounting/Finance. Dr. Crack taught at the university level for 20 years including four years as a front line teaching assistant for MBA students at MIT. He recently headed a quantitative active equity research team at the world's largest institutional money manager.

    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.

    To reach this unique audience, Whitlock and Schluter motivate learning with interesting biological and medical examples; they emphasize intuitive understanding; and they focus on real data. The book covers basic topics in introductory statistics, including graphs, confidence intervals, hypothesis testing, comparison of means, regression, and designing experiments. It also introduces the principles behind such modern topics as likelihood, linear models, meta-analysis and computer-intensive methods. Instructors and students consistently praise the book's clear and engaging writing, strong visualization techniques, and its variety of fascinating and relevant biological examples.

    Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you're ready to get started.Use R's default graphics for quick exploration of dataCreate a variety of bar graphs, line graphs, and scatter plotsSummarize data distributions with histograms, density curves, box plots, and other examplesProvide annotations to help viewers interpret dataControl the overall appearance of graphicsRender data groups alongside each other for easy comparisonUse colors in plotsCreate network graphs, heat maps, and 3D scatter plotsStructure data for graphing

    Written by two of the best-known names in categorical logic, Conceptual Mathematics is the first book to apply categories to the most elementary mathematics. It thus serves two purposes: first, to provide a key to mathematics for the general reader or beginning student; and second, to furnish an easy introduction to categories for computer scientists, logicians, physicists, and linguists who want to gain some familiarity with the categorical method without initially committing themselves to extended study.

    Scientists have marveled at the beauty and elegance of his analysis, while ordinary programmers have successfully applied his "cookbook" solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books. "I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up.""--"Charles Long Primarily written as a reference, some people have nevertheless found it possible and interesting to read each volume from beginning to end. A programmer in China even compared the experience to reading a poem. "If you think you're a really good programmer... read Knuth's] "Art of Computer Programming.".. You should definitely send me a resume if you can read the whole thing.""--"Bill Gates Whatever your background, if you need to do any serious computer programming, you will find your own good reason to make each volume in this series a readily accessible part of your scholarly or professional library. "It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers.""--"Jonathan LaventholIn describing the new fourth volume, one reviewer listed the qualities that distinguish all of Knuth's work. In sum: ] "detailed coverage of the basics, illustrated with well-chosen examples; occasional forays into more esoteric topics and problems at the frontiers of research; impeccable writing peppered with occasional bits of humor; extensive collections of exercises, all with solutions or helpful hints; a careful attention to history; implementations of many of the algorithms in his classic step-by-step form."--Frank RuskeyThese four books comprise what easily could be the most important set of information on any serious programmer's bookshelf.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    This connectedness is found in many incarnations: in the rapid growth of the Internet, in the ease with which global communication takes place, and in the ability of news and information as well as epidemics and financial crises to spread with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which our decisions can have subtle consequences for others. This introductory undergraduate textbook takes an interdisciplinary look at economics, sociology, computing and information science, and applied mathematics to understand networks and behavior. It describes the emerging field of study that is growing at the interface of these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

     Offers extensively updated coverage, new problem sets, and chapter-ending material to enhance the book’s relevance to today’s engineers and scientists. Includes new problem sets demonstrating updated applications to engineering as well as biological, physical, and computer science. Emphasizes key ideas as well as the risks and hazards associated with practical application of the material. Includes new material on topics including: difference between discrete and continuous measurements; binary data; quartiles; importance of experimental design; “dummy” variables; rules for expectations and variances of linear functions; Poisson distribution; Weibull and lognormal distributions; central limit theorem, and data plotting. Introduces Bayesian statistics, including its applications to many fields. For those interested in learning more about probability and statistics.

    This concept is at the root of the computational worldview, which basically says that very complex systems — the world we live in — have their beginnings in simple mathematical equations. We've lately come to understand that such an algorithm is only the start of a never-ending story — the real action occurs in the unfolding consequences of the rules. The chip-in-a-box computers so popular in our time have acted as a kind of microscope, letting us see into the secret machinery of the world. In Lifebox, Rucker uses whimsical drawings, fables, and humor to demonstrate that everything is a computation — that thoughts, computations, and physical processes are all the same. Rucker discusses the linguistic and computational advances that make this kind of "digital philosophy" possible, and explains how, like every great new principle, the computational world view contains the seeds of a next step.

    You can use these ideas and methods as-is, or better yet, tweak them and create your own enticing educational meals. The message the authors share is that, with imagination and preparation, every teacher can be a Classroom Chef.

    Get ready to amaze your friends—and yourself—with incredible calculations you never thought you could master, as renowned “mathemagician” Arthur Benjamin shares his techniques for lightning-quick calculations and amazing number tricks. This book will teach you to do math in your head faster than you ever thought possible, dramatically improve your memory for numbers, and—maybe for the first time—make mathematics fun.Yes, even you can learn to do seemingly complex equations in your head; all you need to learn are a few tricks. You’ll be able to quickly multiply and divide triple digits, compute with fractions, and determine squares, cubes, and roots without blinking an eye. No matter what your age or current math ability, Secrets of Mental Math will allow you to perform fantastic feats of the mind effortlessly. This is the math they never taught you in school.Also available as an eBook

    There are classical logic puzzles, lateral thinking puzzles, “who am I?” riddles, mathematical brain teasers, word ladders, ditloids, and a large selection of illustrated pen and paper, coins, cups, and toothpicks puzzles (please view the preview of this book for a full listing). This is the first time a collection of such breadth has been compiled and formatted especially for Kindle devices. The puzzles have been carefully organized into 25 chapters, and each question is hyperlinked to its solution, to provide utmost ease of navigation. Alongside the world’s most famous riddles, are some lesser known gems, and some brand new puzzles, in print here for the first time. Our aim was to create a definitive compendium of riddles and puzzles to bring enjoyment to people of all ages. We hope you will enjoy unraveling them as much as we enjoyed creating and editing them. Here are a handful of sample riddles: Outside the Box Riddles: You need to divide a round birthday cake into eight pieces, so each of your guests will have something to eat. How can you do this by making only three straight cuts with a knife, and without moving any of the pieces? The king’s two bodyguards developed an ingenious method for assuring the king’s safety. With the king standing between them, they would face in opposite directions; one looking to the west and the other to the east, but at the same time, and without the use of any reflective surfaces, they would both be able to observe the king clearly. How was this possible? Pure Logic Riddles: There are two glasses. One contains water, and the other contains an equal quantity of wine. A teaspoon of water is removed and mixed into the glass of wine. A teaspoon of the wine-water mixture is then removed and mixed into the glass of water. Which of the mixtures is now purer? The sorcerer’s tower was enchanted in such a way that it was able to build itself. Bricks, slates, tiles, and panes of glass, all flew to it of their own accord and danced into position. The tower doubled in size every day until after 100 days it reached a height that provided fine views over the entire realm. How many days did the tower take to reach half its full height? Lateral Thinking Puzzles: Five men are going to church. It starts to rain, and four of the men begin to run. When they arrive at the church, the four men who ran are soaking wet, whereas the fifth man, who didn’t run, is completely dry. How is this possible? Think Twice Riddles: If you are running a race, and you overtake the person in second place, what place do you move into? Word Riddles: SOS is read the same forwards, backwards, and even upside-down. What four-letter word also shares these properties? Number Puzzlers: How many letters are there in the answer to this question? You have an opportunity to buy a hen. In fact, you have been offered a choice between two quite remarkable animals. One of the hens produces six dozen dozen eggs per month, and the other produces a half dozen dozen. Admittedly, both seem impressive. Does it matter which hen you choose? Traditional Poetic Riddles: Five creatures cross a field of snow; But leave a single track behind Whose loops and bows are soon, I know, Unravelled by the mind. Coins, Cups, and Toothpicks Illustrated Riddles: A coin is dropped into an empty bottle and a cork is then inserted in the neck of the bottle. How is it possible to remove the coin without taking out the cork, or breaking the bottle?

    “The result is a veritable pi

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.