Mark Taper, Subhash Lele and an esteemed group of contributors explore the relationships among hypotheses, models, data and interference on which scientific progress rests in an attempt to develop a new quantitative framework for evidence.

An exploration of the statistical foundations of scientific inference, The Nature of Scientific Evidence asks what constitutes scientific evidence and whether scientific evidence can be quantified statistically. Mark Taper, Subhash Lele, and an esteemed group of contributors explore the relationships among hypotheses, models, data, and inference on which scientific progress rests in an attempt to develop a new quantitative framework for evidence. Informed by interdisciplinary discussions among scientists, philosophers, and statisticians, they propose a new "evidential" approach, which may be more in keeping with the scientific method. The Nature of Scientific Evidence persuasively argues that all scientists should care more about the fine points of statistical philosophy because therein lies the connection between theory and data. Though the book uses ecology as an exemplary science, the interdisciplinary evaluation of the use of statistics in empirical research will be of interest to any reader engaged in the quantification and evaluation of data.

One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.

Marijuana is the world's most popular illicit drug, with hundreds of millions of regular users worldwide. One in three Americans has smoked pot at least once. The Drug Enforcement Agency estimates that Americans smoke five million pounds of marijuana each year. And yet marijuana remains largely misunderstood by both its advocates and its detractors. To some, marijuana is an insidious "stepping-stone" drug, enticing the inexperienced and paving the way to the inevitable abuse of harder drugs. To others, medical marijuana is an organic means of easing the discomfort or stimulating the appetite of the gravely ill. Others still view marijuana, like alcohol, as a largely harmless indulgence, dangerous only when used immoderately. All sides of the debate have appropriated the scientific evidence on marijuana to satisfy their claims. What then are we to make of these conflicting portrayals of a drug with historical origins dating back to 8,000 B.C.? Understanding Marijuana examines the biological, psychological, and societal impact of this controversial substance. What are the effects, for mind and body, of long-term use? Are smokers of marijuana more likely than non-users to abuse cocaine and heroine? What effect has the increasing potency of marijuana in recent years had on users and on use? Does our current legal policy toward marijuana make sense? Earleywine separates science from opinion to show how marijuana defies easy dichotomies. Tracing the medical and political debates surrounding marijuana in a balanced, objective fashion, this book will be the definitive primer on our most controversial and widely used illicit substance.

As both individuals and societies, we are making decisions today that will have profound consequences for future generations. From preserving Earth's plants and animals to altering our use of fossil fuels, none of these decisions can be made wisely without a thorough understanding of life's history on our planet through biological evolution. Companion to the best selling title Teaching About Evolution and the Nature of Science, Evolution in Hawaii examines evolution and the nature of science by looking at a specific part of the world. Tracing the evolutionary pathways in Hawaii, we are able to draw powerful conclusions about evolution's occurrence, mechanisms, and courses. This practical book has been specifically designed to give teachers and their students an opportunity to gain a deeper understanding of evolution using exercises with real genetic data to explore and investigate speciation and the probable order in which speciation occurred based on the ages of the Hawaiian Islands. By focusing on one set of islands, this book illuminates the general principles of evolutionary biology and demonstrate how ongoing research will continue to expand our knowledge of the natural world.

Physicists think they have discovered the top quark. Biologists believe in evolution. But what precisely constitutes evidence for such claims, and why? Scientists often disagree with one another over whether or to what extent some evidence counts in favor of a theory because they are operating with different concepts of scientific evidence. These concepts need to be critically explored. Peter Achinstein has gathered some prominent philosophers and historians of science for critical and lively discussions of both general questions about the meaning of evidence and specific ones about evidence for particular scientific theories. Contributors: Peter Achinstein, The Johns Hopkins University; Steven Gimbel, Gettysburg College; Gary Hatfield, University of Pennsylvania; Frederick M. Kronz, University of Texas–Austin; Helen Longino, University of Minnesota; Deborah G. Mayo, Virginia Tech; Amy L. McLaughlin, Florida Atlantic University; John Norton, University of Pittsburgh; Lawrence M. Principe, The Johns Hopkins University; Richard Richards, University of Alabama; Alex Rosenberg, Duke University; Sherrilyn Roush, Rice University; Laura J. Snyder, St. Johns University; Kent Staley, St. Louis University.