Schaum's Outline of Advanced Mathematics for Engineers and Scientists


Murray R. Spiegel - 1971
    Fully stocked with solved problemsN950 of themNit shows you how to solve problems that may not have been fully explained in class. Plus you ge"

Schaum's Outline of College Physics


Frederick J. Bueche - 2006
    Provides a review of introductory noncalculus-based physics for those who do not have a strong background in mathematics.

Electronic Devices (Conventional Current Version)


Thomas L. Floyd - 1984
    Floyd is well known for straightforward, understandable explanations of complex concepts, as well as for non-technical, on-target treatment of mathematics. The extensive use of examples, Multisim simulations, and graphical illustrations makes even complex concepts understandable. From discrete components, to linear integrated circuits, to programmable analog devices, this books¿ coverage is well balanced between discrete and integrated circuits. Also includes focus on power amplifiers; BJT and FET amplifiers; advanced integrated circuits–instrumentation and isolation amplifiers; OTAs; log/antilog amplifiers; and converters. Thorough coverage of optical topics–high intensity LEDs and fiber optics. Devices sections on differential amplifiers and the IGBT (insulated gate bipolar transistor) are now included. For electronics technicians.

Fundamentals of Physics, Chapters 1 - 21, Enhanced Problems Version


David Halliday - 2000
    This newest edition expands on the strengths of earlier versions, helping students bridge the gap between concepts and reasoning. Students are shown, rather than told about, how physics works and are given the opportunity to apply concepts to real-world problems. Each chapter and concept has been scrutinized to ensure clarity, currency, and accuracy while checkpoints, problem solving tactics, and sample problems help students make sense of new concepts. As always, Fundamentals of Physics covers every aspect of basic physics, from force and motion to relativity and will prepare today's students to be tomorrow's scientists.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction


Trevor Hastie - 2001
    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

Essentials of Nursing Research: Appraising Evidence for Nursing Practice


Denise F. Polit - 2009
    The Seventh Edition has been updated with stronger coverage of evidence-based practice, including content on how to read, interpret, and critique systematic reviews, which are considered by many to be a cornerstone of evidence-based practice. Also included in the Seventh Edition: a more balanced presentation of medical and social science methods and nomenclature; enhanced coverage of qualitative research; and more!

Elementary Statistics


Mario F. Triola - 1983
    This text is highly regarded because of its engaging and understandable introduction to statistics. The author's commitment to providing student-friendly guidance through the material and giving students opportunities to apply their newly learned skills in a real-world context has made Elementary Statistics the #1 best-seller in the market.

Introduction to Electrodynamics


David J. Griffiths - 1981
    This work offers accesible coverage of the fundamentals of electrodynamics, enhanced with with discussion points, examples and exercises.

Using Multivariate Statistics


Barbara G. Tabachnick - 1983
    It givessyntax and output for accomplishing many analyses through the mostrecent releases of SAS, SPSS, and SYSTAT, some not available insoftware manuals. The book maintains its practical approach, stillfocusing on the benefits and limitations of applications of a techniqueto a data set -- when, why, and how to do it. Overall, it providesadvanced students with a timely and comprehensive introduction totoday's most commonly encountered statistical and multivariatetechniques, while assuming only a limited knowledge of higher-levelmathematics.

Starting Out with Java: From Control Structures Through Objects


Tony Gaddis - 2009
    If you wouldlike to purchase both the physical text and MyProgrammingLab search for ISBN-10: 0132989999/ISBN-13: 9780132989992. That packageincludes ISBN-10: 0132855836/ISBN-13: 9780132855839 and ISBN-10: 0132891557/ISBN-13: 9780132891554. MyProgrammingLab should only be purchased when required by an instructor. In "Starting Out with Java: From Control Structures through Objects", Gaddis covers procedural programming control structures and methods before introducing object-oriented programming. As with all Gaddis texts, clear and easy-to-read code listings, concise and practical real-world examples, and an abundance of exercises appear in every chapter. "

MATLAB: An Introduction with Applications


Amos Gilat - 2003
    The first chapter describes basic features of the program and shows how to use it in simple arithmetic operations with scalars. The next two chapters focus on the topic of arrays (the basis of MATLAB), while the remaining text covers a wide range of other applications. Computer screens, tutorials, samples, and homework questions in math, science, and engineering, provide the student with the practical hands-on experience needed for total proficiency.

Microelectronic Circuits


Adel S. Sedra - 1982
    Sedra and Kenneth C. Smith. All material in the fifth edition of Microelectronic Circuits is thoroughly updated to reflect changes in technology-CMOS technology in particular. These technological changes have shaped the book's organization and topical coverage, making it the most current resource available for teaching tomorrow's engineers how to analyze and design electronic circuits.

Bayesian Data Analysis


Andrew Gelman - 1995
    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

Operations Research: Applications and Algorithms (with CD-ROM and InfoTrac)


Wayne L. Winston - 1987
    It moves beyond a mere study of algorithms without sacrificing the rigor that faculty desire. As in every edition, Winston reinforces the book's successful features and coverage with the most recent developments in the field. The Student Suite CD-ROM, which now accompanies every new copy of the text, contains the latest versions of commercial software for optimization, simulation, and decision analysis.

Discrete Mathematics and Its Applications


Kenneth H. Rosen - 2000
    These themes include mathematical reasoning, combinatorial analysis, discrete structures, algorithmic thinking, and enhanced problem-solving skills through modeling. Its intent is to demonstrate the relevance and practicality of discrete mathematics to all students. The Fifth Edition includes a more thorough and linear presentation of logic, proof types and proof writing, and mathematical reasoning. This enhanced coverage will provide students with a solid understanding of the material as it relates to their immediate field of study and other relevant subjects. The inclusion of applications and examples to key topics has been significantly addressed to add clarity to every subject. True to the Fourth Edition, the text-specific web site supplements the subject matter in meaningful ways, offering additional material for students and instructors. Discrete math is an active subject with new discoveries made every year. The continual growth and updates to the web site reflect the active nature of the topics being discussed. The book is appropriate for a one- or two-term introductory discrete mathematics course to be taken by students in a wide variety of majors, including computer science, mathematics, and engineering. College Algebra is the only explicit prerequisite.