This book develops statistical thinking over rote drill and practice. The Nature of Statistics; Organizing Data; Descriptive Measures; Probability Concepts; Discrete Random Variables; The Normal Distribution; The Sampling Distribution of the Sample Menu; Confidence Intervals for One Population Mean; Hypothesis Tests for One Population Mean; Inferences for Two Population Means; Inferences for Population Standard Deviations; Inferences for Population Proportions; Chi-Square Procedures; Descriptive Methods in Regression and Correlation; Inferential Methods in Regression and Correlation; Analysis of Variance (ANOVA) For all readers interested in Introductory Statistics.

    Integrated central case studies woven throughout each chapter, use real-life stories to give you a tangible and engaging framework around which to learn and understand the science behind environmental issues. Printed on FSC (Forest Stewardship Council) certified paper, the newly revised Fourth Edition engages you through the addition of new EnvisionIt photo essays.

    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.

    The author's writing has been praised for anticipating readers' questions, and appeals to their need to learn visually and by solving problems. Emphasizing that learners should reason their way to solutions rather than memorize facts, Bruice encourages them to think about what they have learned previously and apply that knowledge in a new setting.

    Designed for two-semester, beginning graduate courses in Mathematical Statistics, and for senior undergraduate Mathematics, Statistics, and Actuarial Science majors, this text retains its ongoing features and continues to provide students with background material.

    Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps readers discover the nature of statistics and understand its essential role in scientific research.

    The new edition provides invitations - not requirements - to use technology, as well as new conceptual problems, and new projects that focus on writing and working in teams.

    The sixth edition explores core concepts in considerable depth and presents experimental detail when it helps to explain and reinforce the concepts. The majority of discussions have been modified to reflect the latest changes in the field. The book also builds on its strong illustration program by opening each chapter with “VIP” art that serves as a visual summary for the chapter. Over 60 new micrographs and computer-derived images have been added to enhance the material. Biologists benefit from these changes as they build their skills in making the connection. Doody Review Services Reviewer: Bruce A. Fenderson, PhD(Thomas Jefferson University) Description: The author expertly organizes, explains, and illustrates the chemical and cellular basis of life on Earth in this comprehensive and exciting introduction to cell and molecular biology. The 18 fascinating chapters cover topics ranging from control of gene expression to mechanisms of immune response. There is even a chapter on laboratory techniques. The focus of the book is on biological chemistry, with an emphasis on core concepts and experimental approaches. Purpose: The purpose is to provide a textbook for an introductory course in cell and molecular biology. The author hopes that students will visualize a world filled with "giant molecules and minuscule structures" that constitute the chemistry of life. He encourages students to consider the evidence that is presented to support a biological model, think of alternate explanations, and plan experiments that may lead to new hypotheses. One of the author's goals is to help students develop their independent, critical-thinking skills. Audience: This is an excellent companion textbook for undergraduate and graduate-level courses in cell and molecular biology. It is written for students across a wide range of life science disciplines

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    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.

    The realistic content of its examples and exercises, the clarity and brevity of its presentation, and the soundness of its pedagogical approach have received the highest remarks from both students and instructors. Now this bestseller is available in a new 6th edition.

    It bridges the gap between the mechanics of econometrics and modern applications of econometrics by employing a systematic approach motivated by the major problems facing applied researchers today. Throughout the text, the emphasis on examples gives a concrete reality to economic relationships and allows treatment of interesting policy questions in a realistic and accessible framework.

    The book covers four major topics in field experimentation:

    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.

    Covering various the materials needed by students in engineering, science, and mathematics, this calculus text makes effective use of computing technology, graphics, and applications. It presents at least two technology projects in each chapter.