H R 1314 H R 1927 H R 4256 H R 4284 H R 4319 And H R 4866

H.R. 1314, H.R. 1927, H.R. 4256, H.R. 4284, H.R. 4319, and H.R. 4866 : legislative hearing before the Committee on Natural Resources, U.S. House of Representatives, One Hundred Thirteenth Congress, second session, Tuesday, September 9, 2014.

Next Generation INDIE Book Awards Grand Prize Winner, Best Non-Fiction Book in 2017; and Winner in the Science/Nature/Environment category Finalist for Foreword INDIES Book of the Year Awards in Ecology and Environment In this book, Lowell E. Baier, one of America’s preeminent experts on environmental litigation, chronicles the century-long story of Americas’ resources management, focusing on litigations, citizen suit provisions, and attorneys’ fees. He provides the first book-length comprehensive examination of the little-known Equal Access to Justice Act (EAJA) and its role in environmental litigation. Originally intended to support veterans, the disabled and small business, EAJA, Baier argues, now paralyzes America’s public land management agencies. Baier introduces readers to the history of EAJA, examines the many beneficiaries of the law, describes in depth 20 of the most prominent litigious environmental groups in America, and recommends carefully tailored amendments to the EAJA to correct environmental abuses of the law while protecting legitimate interests. Inside the Equal Access to Justice Act will be a valuable resource for the environmental legal community, environmentalists, practitioners at all levels of government, and all readers interested in environmental policy and the rise of the administrative state.

If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer and you'll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but there aren't many resources available to help beginners. Based on undergraduate classes taught by author Allen B. Downey, this book's computational approach helps you get a solid start. Use your programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing Get started with simple examples, using coins, dice, and a bowl of cookies Learn computational methods for solving real-world problems