Book picks similar to
Mathematical Statistics with Applications by Richard L. Scheaffer
statistics
m-probstat
math
mathematics
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.
Principles of Mathematical Analysis
Walter Rudin - 1964
The text begins with a discussion of the real number system as a complete ordered field. (Dedekind's construction is now treated in an appendix to Chapter I.) The topological background needed for the development of convergence, continuity, differentiation and integration is provided in Chapter 2. There is a new section on the gamma function, and many new and interesting exercises are included. This text is part of the Walter Rudin Student Series in Advanced Mathematics.
The Baseball Economist: The Real Game Exposed
J.C. Bradbury - 2007
Two hot topics team up in The Baseball Economist, and the result is a refreshing, clear- eyed survey of a playing field that has changed radically in recent years. Utilizing the latest economic methods and statistical analysis, writer, economics professor, and popular blogger J. C. Bradbury dissects burning baseball topics with his original Sabernomic perspective, such as: Did steroids have nothing to do with the recent home run records? Incredibly, Bradbury's research, reviewed by Stanford economists, reveals steroids had little statistical significance. Is the big-city versus small-city competition really lopsided? Bradbury shows why the Marlins and Indians are likely to dominate big-city franchises in the coming years. Which players are ridiculously overvalued? Bradbury lists all players by team with their revenue value to the team listed in dollarsincluding a dishonor role of those players with negative values. Is major league baseball a monopoly that can't govern itself? Bradbury sets out what rules the owners really need to play by, and what the players' union should be doing. Does it help to lobby for balls and strikes? How would Babe Ruth perform in today's game? And who killed all the left-handed catchers, anyway? The Baseball Economist knows. Providing far more than a mere collection of numbers, Bradbury shines the light of his economic thinking on baseball, exposing the power of tradeoffs, competition, and incentives. Statistics alone aren't enough anymore. Fans, fantasy buffs, and players, as well as coaches at all levels who want to grasp what is really happening on the field today and in the coming years, will use and enjoy Bradbury's brilliant new understanding of the national pastime.
The Mathematical Theory of Communication
Claude Shannon - 1949
Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored to issue this commemorative reprinting of a classic.
The Monty Hall Problem: The Remarkable Story of Math's Most Contentious Brain Teaser
Jason Rosenhouse - 2009
Imagine that you face three doors, behind one of which is a prize. You choose one but do not open it. The host--call him Monty Hall--opens a different door, alwayschoosing one he knows to be empty. Left with two doors, will you do better by sticking with your first choice, or by switching to the other remaining door? In this light-hearted yet ultimately serious book, Jason Rosenhouse explores the history of this fascinating puzzle. Using a minimum ofmathematics (and none at all for much of the book), he shows how the problem has fascinated philosophers, psychologists, and many others, and examines the many variations that have appeared over the years. As Rosenhouse demonstrates, the Monty Hall Problem illuminates fundamental mathematical issuesand has abiding philosophical implications. Perhaps most important, he writes, the problem opens a window on our cognitive difficulties in reasoning about uncertainty.
Time Series Analysis
James Douglas Hamilton - 1994
This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.-- "Journal of Economics"
Doing Math with Python
Amit Saha - 2015
Python is easy to learn, and it's perfect for exploring topics like statistics, geometry, probability, and calculus. You’ll learn to write programs to find derivatives, solve equations graphically, manipulate algebraic expressions, even examine projectile motion.Rather than crank through tedious calculations by hand, you'll learn how to use Python functions and modules to handle the number crunching while you focus on the principles behind the math. Exercises throughout teach fundamental programming concepts, like using functions, handling user input, and reading and manipulating data. As you learn to think computationally, you'll discover new ways to explore and think about math, and gain valuable programming skills that you can use to continue your study of math and computer science.If you’re interested in math but have yet to dip into programming, you’ll find that Python makes it easy to go deeper into the subject—let Python handle the tedious work while you spend more time on the math.
A Guide To Econometrics
Peter E. Kennedy - 1979
This overview has enabled students to make sense more easily of what instructors are doing when they produce proofs, theorems and formulas.
The Art of R Programming: A Tour of Statistical Software Design
Norman Matloff - 2011
No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.
Bayesian Reasoning and Machine Learning
David Barber - 2012
They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.
Numerical Analysis
Richard L. Burden - 1978
Explaining how, why, and when the techniques can be expected to work, the Seventh Edition places an even greater emphasis on building readers' intuition to help them understand why the techniques presented work in general, and why, in some situations, they fail. Applied problems from diverse areas, such as engineering and physical, computer, and biological sciences, are provided so readers can understand how numerical methods are used in real-life situations. The Seventh Edition has been updated and now addresses the evolving use of technology, incorporating it whenever appropriate.
Real Analysis
H.L. Royden - 1963
Dealing with measure theory and Lebesque integration, this is an introductory graduate text.
Signals and Systems
A. Anand Kumar - 2011
Written with student centred, pedagogically driven approach, the text provides a self-contained introduction to the theory of signals and systems. This book looks at the concepts of systems, and also examines signals and the way that signals interact with physical systems. It covers topics ranging from basic signals and systems to signal analysis, properties of continuous-time Fourier transforms including Fourier transforms of standard signals, signal transmission through linear systems, relation between convolution and correlation of signals, sampling theorems and techniques, and transform analysis of LTI systems. All the solved and unsolved problems in this book are designed to illustrate the topics in a clear way.
Physics for Scientists and Engineers, Volume 1
Raymond A. Serway - 2003
However, rather than resting on that reputation, the new edition of this text marks a significant advance in the already excellent quality of the book. While preserving concise language, state of the art educational pedagogy, and top-notch worked examples, the Eighth Edition features a unified art design as well as streamlined and carefully reorganized problem sets that enhance the thoughtful instruction for which Raymond A. Serway and John W. Jewett, Jr. earned their reputations. Likewise, PHYSICS FOR SCIENTISTS AND ENGINEERS, will continue to accompany Enhanced WebAssign in the most integrated text-technology offering available today. In an environment where new Physics texts have appeared with challenging and novel means to teach students, this book exceeds all modern standards of education from the most solid foundation in the Physics market today.