Partial Differential Equations for Scientists and Engineers


Stanley J. Farlow - 1982
    Indeed, such equations are crucial to mathematical physics. Although simplifications can be made that reduce these equations to ordinary differential equations, nevertheless the complete description of physical systems resides in the general area of partial differential equations.This highly useful text shows the reader how to formulate a partial differential equation from the physical problem (constructing the mathematical model) and how to solve the equation (along with initial and boundary conditions). Written for advanced undergraduate and graduate students, as well as professionals working in the applied sciences, this clearly written book offers realistic, practical coverage of diffusion-type problems, hyperbolic-type problems, elliptic-type problems, and numerical and approximate methods. Each chapter contains a selection of relevant problems (answers are provided) and suggestions for further reading.

An Introduction to Probability Theory and Its Applications, Volume 1


William Feller - 1968
    Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book's comprehensive approach provides a complete view of theory along with enlightening examples along the way.

Deep Learning with Python


François Chollet - 2017
    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

Head First Statistics


Dawn Griffiths - 2008
    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 statistics Tackle 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 life Discover how to measure spread, calculate odds through probability, and understand the normal, binomial, geometric, and Poisson distributions Conduct sampling, use correlation and regression, do hypothesis testing, perform chi square analysis, and moreBefore 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.

How to Measure Anything: Finding the Value of "Intangibles" in Business


Douglas W. Hubbard - 1985
    Douglas Hubbard helps us create a path to know the answer to almost any question in business, in science, or in life . . . Hubbard helps us by showing us that when we seek metrics to solve problems, we are really trying to know something better than we know it now. How to Measure Anything provides just the tools most of us need to measure anything better, to gain that insight, to make progress, and to succeed." -Peter Tippett, PhD, M.D. Chief Technology Officer at CyberTrust and inventor of the first antivirus software "Doug Hubbard has provided an easy-to-read, demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions. We encourage our clients to try his powerful, practical techniques." -Peter Schay EVP and COO of The Advisory Council "As a reader you soon realize that actually everything can be measured while learning how to measure only what matters. This book cuts through conventional cliches and business rhetoric and offers practical steps to using measurements as a tool for better decision making. Hubbard bridges the gaps to make college statistics relevant and valuable for business decisions." -Ray Gilbert EVP Lucent "This book is remarkable in its range of measurement applications and its clarity of style. A must-read for every professional who has ever exclaimed, 'Sure, that concept is important, but can we measure it?'" -Dr. Jack Stenner Cofounder and CEO of MetraMetrics, Inc.

Rigging the Game: How Inequality Is Reproduced in Everyday Life


Michael Schwalbe - 2007
    Guided by the questions How did the situation get this way? and How does it stay this way?, Schwalbe tracks inequality from its roots to its regulation. In the final chapter, "Escaping the Inequality Trap," he also shows how inequality can be overcome. Throughout, Schwalbe's engaging writing style draws students into the material, providing instructors with a solid foundation for discussing this challenging and provocative subject.With its lively combination of incisive analysis and compelling fictional narratives, Rigging the Game is an innovative teaching tool--not only for courses on stratification, but also for social problems courses, introductory sociology courses, and any course that takes a close look at how the inequalities of race, class, and gender are perpetuated.

Stochastic Calculus Models for Finance II: Continuous Time Models (Springer Finance)


Steven E. Shreve - 2004
    The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for shastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.This book is being published in two volumes. This second volume develops shastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time.Masters level students and researchers in mathematical finance and financial engineering will find this book useful.Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

Financial Accounting [with CD-ROM]


Robert Libby - 1995
    This title presents the use of focus companies and the financial statements. The decision-making focus shows the relevance of financial accounting regardless of whether or not the student has chosen to major in accounting.

Macroeconomics: Theories and Policies


Richard T. Froyen - 1983
    Now revised and updated to include expanded coverage of monetary policy, this volume traces the history of macroeconomics and the evolution of macroeconomic thought and the resulting theory and policy.

Running a Restaurant for Dummies


Heather Dismore - 2004
    Running a Restaurant For Dummies covers every aspect of getting started for wannabe restaurateurs. From setting up a business plan and finding financing, to designing a menu and dining room, you'll find all the advice you need to start and run a successful restaurant. Even if you don't know anything about cooking or running a business, you might still have a great idea for a restaurant -- and this handy guide will show you how to make your dream a reality. If you already own a restaurant, but want to see it do better, Running a Restaurant For Dummies offers unbeatable tips and advice of bringing in hungry customers. From start to finish, you'll learn everything you need to know to succeed:Put your ideas on paper with a realistic business plan Attract investors to help get the business off the ground Be totally prepared for your grand opening Make sure your business is legal and above board Hire and train a great staff Develop a delicious menu If you're looking for expert guidance from people in the know, then Running a Restaurant For Dummies is the only book you need. Written by Michael Garvey, co-owner of the famous Oyster Bar at Grand Central, with help from writer Heather Dismore and chef Andy Dismore, this book covers all the bases, from balancing the books to training staff and much more:Designing and theme and a concept Taking over an existing restaurant or buying into a franchise Stocking and operating a bar Working with partners and other investors Choose a perfect location Hiring and training an excellent staff Pricing menu items Designing the interior of the restaurant Purchasing and managing supplies Marketing your restaurant to customers If you're looking for a new career as a restaurateur, or you need new ideas for your struggling restaurant, Running a Restaurant For Dummies offers expert advice in a fun, friendly format. Packed with practical advice and expert wisdom on every aspect of the food service business, this guide is all you need to get cooking.

Elementary Linear Algebra with Applications


Bernard Kolman - 1995
    It offers a fine balance between abstraction/theory and computational skills, and gives readers an excellent opportunity to learn how to handle abstract concepts. Included in this comprehensive and easy-to-follow manual are these topics: linear equations and matrices; solving linear systems; real vector spaces; inner product spaces; linear transformations and matrices; determinants; eigenvalues and eigenvectors; differential equations; and MATLAB for linear algebra. Because this book gives real applications for linear algebraic basic ideas and computational techniques, it is useful as a reference work for mathematicians and those in field of computer science.

Street-Fighting Mathematics: The Art of Educated Guessing and Opportunistic Problem Solving


Sanjoy Mahajan - 2010
    Traditional mathematics teaching is largely about solving exactly stated problems exactly, yet life often hands us partly defined problems needing only moderately accurate solutions. This engaging book is an antidote to the rigor mortis brought on by too much mathematical rigor, teaching us how to guess answers without needing a proof or an exact calculation.In Street-Fighting Mathematics, Sanjoy Mahajan builds, sharpens, and demonstrates tools for educated guessing and down-and-dirty, opportunistic problem solving across diverse fields of knowledge--from mathematics to management. Mahajan describes six tools: dimensional analysis, easy cases, lumping, picture proofs, successive approximation, and reasoning by analogy. Illustrating each tool with numerous examples, he carefully separates the tool--the general principle--from the particular application so that the reader can most easily grasp the tool itself to use on problems of particular interest. Street-Fighting Mathematics grew out of a short course taught by the author at MIT for students ranging from first-year undergraduates to graduate students ready for careers in physics, mathematics, management, electrical engineering, computer science, and biology. They benefited from an approach that avoided rigor and taught them how to use mathematics to solve real problems.Street-Fighting Mathematics will appear in print and online under a Creative Commons Noncommercial Share Alike license.

Kellogg on Marketing


Alice M. Tybout - 2000
    This is a must-have marketing reference.

The Theoretical Minimum: What You Need to Know to Start Doing Physics


Leonard Susskind - 2013
    In this unconventional introduction, physicist Leonard Susskind and hacker-scientist George Hrabovsky offer a first course in physics and associated math for the ardent amateur. Unlike most popular physics books—which give readers a taste of what physicists know but shy away from equations or math—Susskind and Hrabovsky actually teach the skills you need to do physics, beginning with classical mechanics, yourself. Based on Susskind's enormously popular Stanford University-based (and YouTube-featured) continuing-education course, the authors cover the minimum—the theoretical minimum of the title—that readers need to master to study more advanced topics.An alternative to the conventional go-to-college method, The Theoretical Minimum provides a tool kit for amateur scientists to learn physics at their own pace.

New Era Of Management


Richard L. Daft
    In response to the dynamic environment of management, Richard Daft has written a text integrating the newest management thinking with a solid foundation in the essentials of management.