Book picks similar to
Essential Calculus by James Stewart
textbooks
mathematics
reference
science
The Worst-Case Scenario Survival Handbook
Joshua Piven - 1999
Volcanoes. Sharks. Quicksand. Terrorists. The pilot of the plane blacks out and it's up to you to land the jet. What do you do? The Worst-Case Scenario Survival Handbook is here to help: jam-packed with how-to, hands-on, step-by-step, illustrated instructions on everything you need to know FAST-from defusing a bomb to delivering a baby in the back of a cab. Providing frightening and funny real information in the best-selling tradition of the Paranoid's Pocket Guide and Hypochondriac's Handbook, this indispensable, indestructible pocket-sized guide is the definitive handbook for those times when life takes a sudden turn for the worse. The essential companion for a perilous age. Because you never know...
Introduction to Real Analysis
Robert G. Bartle - 1982
Therefore, this book provides the fundamental concepts and techniques of real analysis for readers in all of these areas. It helps one develop the ability to think deductively, analyze mathematical situations and extend ideas to a new context. Like the first two editions, this edition maintains the same spirit and user-friendly approach with some streamlined arguments, a few new examples, rearranged topics, and a new chapter on the Generalized Riemann Integral.
Invitation to Psychology
Carole Wade - 1998
In clear, lively, warm prose, this edition continues the title's integration of gender, culture, and ethnicity. By the end, readers will learn how to interpret research and to address and resolve controversies. MyPsychLab is an integral part of the Wade/Tavris/Garry program. Engaging activities and assessments provide a teaching and learning system that helps students think like a psychologist. With MyPsychLab, students can watch videos on psychological research and applications, participate in virtual classic experiments, and develop critical thinking skills through writing. "Invitation to Psychology, "5/e is available in a new DSM-5 Updated edition. To learn more, click here. This title is available in a variety of formats - digital and print. Pearson offers its titles on the devices students love through Pearson's MyLab products, CourseSmart, Amazon, and more.
Introduction to Probability
Joseph K. Blitzstein - 2014
The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo MCMC. Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.
Principles of Neural Science
Eric R. Kandel - 1981
It discusses neuroanatomy, cell and molecular mechanisms and signaling through a cognitive approach to behaviour. It features an expanded treatment of the nervous system, neurological and psychiatric diseases and perception.
Mathematical Methods in the Physical Sciences
Mary L. Boas - 1967
Intuition and computational abilities are stressed. Original material on DE and multiple integrals has been expanded.
Python Data Science Handbook: Tools and Techniques for Developers
Jake Vanderplas - 2016
Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Think Python
Allen B. Downey - 2002
It covers the basics of computer programming, including variables and values, functions, conditionals and control flow, program development and debugging. Later chapters cover basic algorithms and data structures.
The Politics Book: Big Ideas Simply Explained
Kate Johnsen - 2013
From ancient and medieval philosophers such as Confucius and Thomas Aquinas, to revolutionary thought leaders such as Thomas Jefferson and Leon Trotsky, to the voices who have shaped modern politics today -- Mao Zedong, Malcolm X, Che Guevara, and more -- "The Politics Book" clearly and simply explains more than 100 groundbreaking ideas in the history of political thought.With easy-to-follow graphics, succinct quotations, and accessible text, "The Politics Book" is an essential reference for students and anyone wondering how politics works.
Naked Statistics: Stripping the Dread from the Data
Charles Wheelan - 2012
How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.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.
An Introduction to Statistical Learning: With Applications in R
Gareth James - 2013
This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Mathematics: From the Birth of Numbers
Jan Gullberg - 1997
The book is unique among popular books on mathematics in combining an engaging, easy-to-read history of the subject with a comprehensive mathematical survey text. Intended, in the author's words, "for the benefit of those who never studied the subject, those who think they have forgotten what they once learned, or those with a sincere desire for more knowledge," it links mathematics to the humanities, linguistics, the natural sciences, and technology.Contains more than 1000 original technical illustrations, a multitude of reproductions from mathematical classics and other relevant works, and a generous sprinkling of humorous asides, ranging from limericks and tall stories to cartoons and decorative drawings.
Emergency Care
Daniel J. Limmer - 1997
Emergency Care, 10/E has prepared more students to pass state and/or the National Registry Exam than any other text on the market with well-organized, clearly presented content, thorough coverage of patient assessment, an accessible reading level, high quality artwork, and outstanding skill scans of equipment and procedures. Case studies and practical tips from the field tie chapter concepts to real world applications. Each chapter sends students to the Companion Website where there are links to EMS-related sites. A new in-text CD provides extra information to help students master concepts.
Computer Networking: A Top-Down Approach
James F. Kurose - 2000
Building on the successful top-down approach of previous editions, this fourth edition continues with an early emphasis on application-layer paradigms and application programming interfaces, encouraging a hands-on experience with protocols and networking concepts.