This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises.

This book discusses some of the most critical ethical issues in mental health care today, including the moral dimensions of addiction, patient autonomy and compulsory treatment, privacy and confidentiality, and the definition of mental illness itself. Although debates over these issues are ongoing, there are few comprehensive resources for addressing such dilemmas in the practice of psychology, psychiatry, social work, and other behavioral and mental health care professions.

This unique introduction to econometrics provides undergraduate students with a command of regression analysis in one semester, enabling them to grasp the empirical literature and undertake serious quantitative projects of their own. It does not assume any previous exposure to probability and statistics but does discuss the concepts in these areas that are essential for econometrics. The bulk of the textbook is devoted to regression analysis, from simple to advanced topics.

The “golden era” of American environmental lawmaking in the 1960s and 1970s saw twenty-two pieces of major environmental legislation (including the Clean Air Act, the Clean Water Act, and the Endangered Species Act) passed by bipartisan majorities in Congress and signed into law by presidents of both parties. But since then partisanship, the dramatic movement of Republicans to the right, and political brinksmanship have led to legislative gridlock on environmental issues.