Successfully tested in the authors' courses at Boston University and Harvard University, this text combines theory and practice in presenting traditional and new epidemiologic concepts. Broad in scope, the text opens with five chapters covering the basic epidemiologic concepts and data sources. A major emphasis is placed on study design, with separate chapters devoted to each of the three main analytic designs: experimental, cohort, and case-control studies. Full chapters on bias, confounding, and random error, including the role of statistics in epidemiology, ensure that students are well-equipped with the necessary information to interpret the results of epidemiologic studies. An entire chapter is also devoted to the concept of effect measure modification, an often-neglected topic in introductory textbooks. Up-to-date examples from the epidemiologic literature on diseases of public health importance are provided throughout the book. The second edition has been thoroughly revised with up-to-date examples and data from epidemiologic literature and features over 100 new study questions.

Essentials of Epidemiology in Public Health, Second Edition
Essentials of Epidemiology in Public Health, Second Edition
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Linear algebra is relatively easy for students during the early stages of the course, when the material is presented in a familiar, concrete setting. But when abstract concepts are introduced, students often hit a brick wall. Instructors seem to agree that certain concepts (such as linear independence, spanning, subspace, vector space, and linear transformations), are not easily understood, and require time to assimilate. Since they are fundamental to the study of linear algebra, students' understanding of these concepts is vital to their mastery of the subject. Lay introduces these concepts early in a familiar, concrete Rn setting, develops them gradually, and returns to them again and again throughout the text so that when discussed in the abstract, these concepts are more accessible.

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