This nonfiction science reader will help fifth grade students gain science content knowledge while building their reading comprehension and literacy skills. This purposefully leveled text features hands-on, challenging science experiments and full-color images. Students will learn all about chemistry, colloids, solubility, solutions, and much more through this engaging text that supports STEM education and is aligned to the Next Generation Science Standards. Important text features like a glossary and index will improve students close reading skills.
While the creation of Dolly the sheep, the world's most famous clone, triggered an enormous amount of discussion about human cloning, in Dolly Mixtures the anthropologist Sarah Franklin looks beyond that much-rehearsed controversy to some of the other reasons why the iconic animal's birth and death were significant. Building on the work of historians and anthropologists, Franklin reveals Dolly as the embodiment of agricultural, scientific, social, and commercial histories which are, in turn, bound up with national and imperial aspirations. Dolly was the offspring of a long tradition of animal domestication, as well as the more recent histories of capital accumulation through selective breeding, and enhanced national competitiveness through the control of biocapital. Franklin traces Dolly's connections to Britain's centuries-old sheep and wool markets (which were vital to the nation's industrial revolution) and to Britain's export of animals to its colonies—particularly Australia—to expand markets and produce wealth. Moving forward in time, she explains the celebrity sheep's links to the embryonic cell lines and global bioscientific innovation of the late twentieth century and early twenty-first. Franklin combines wide-ranging sources—from historical accounts of sheep-breeding, to scientific representations of cloning by nuclear transfer, to popular media reports of Dolly's creation and birth—as she draws on gender and kinship theory as well as postcolonial and science studies. She argues that there is an urgent need for more nuanced responses to the complex intersections between the social and the biological, intersections which are literally reshaping reproduction and genealogy. In Dolly Mixtures, Franklin uses the renowned sheep as an opportunity to begin developing a critical language to identify and evaluate the reproductive possibilities that post-Dolly biology now faces, and to look back at some of the important historical formations that enabled and prefigured Dollys creation.
This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject. The applications are drawn from scientific discipline, including biostatistics, computer science, ecology and finance. This area of statistics is important to a range of disciplines, and its methodology attracts interest from researchers in the fields in which it can be applied.
In this book, both basic and advanced concepts are discussed for considering mixtures from initial exposure characterization through evaluation of risk associated with combined exposures. This book will provide an introduction to key issues and multiple options for evaluating both the toxicity of mixtures as well as the risk associated with exposure to mixtures. Additionally, promising tools adapted from other disciplines will be discussed in the context of mixtures toxicology and risk assessment. Finally, the discussion will move beyond chemical mixtures to address incorporating non-chemical stressors into toxicity studies and cumulative risk assessments. Although exposure to multiple chemical and non-chemical stressors is the rule, not the exception, consideration of mixtures in toxicology and risk assessment continues to be a significant challenge. This book will be an essential resource for researchers and professionals in the fields of toxicology, epidemiology, exposure science, risk assessment, and statistics.
Almost everything around us is a combination of different things. These are mixtures and solutions. Seawater, for example, is a solution of salt and water. The engaging text and vivid illustrations in this book will help readers understand how mixtures and solutions form, and how they apply to everyday life.
An up-to-date, comprehensive account of major issues in finitemixture modeling This volume provides an up-to-date account of the theory andapplications of modeling via finite mixture distributions. With anemphasis on the applications of mixture models in both mainstreamanalysis and other areas such as unsupervised pattern recognition,speech recognition, and medical imaging, the book describes theformulations of the finite mixture approach, details itsmethodology, discusses aspects of its implementation, andillustrates its application in many common statisticalcontexts. Major issues discussed in this book include identifiabilityproblems, actual fitting of finite mixtures through use of the EMalgorithm, properties of the maximum likelihood estimators soobtained, assessment of the number of components to be used in themixture, and the applicability of asymptotic theory in providing abasis for the solutions to some of these problems. The author alsoconsiders how the EM algorithm can be scaled to handle the fittingof mixture models to very large databases, as in data miningapplications. This comprehensive, practical guide: * Provides more than 800 references-40% published since 1995 * Includes an appendix listing available mixture software * Links statistical literature with machine learning and patternrecognition literature * Contains more than 100 helpful graphs, charts, and tables Finite Mixture Models is an important resource for both applied andtheoretical statisticians as well as for researchers in the manyareas in which finite mixture models can be used to analyze data.
Readers will learn about how mixtures and solutions are made and measured; what makes dissolving easier; how we can separate mixtures and solutions; what air is made from; and more.
Mixtures And Solutions Exist Everywhere And Students Will Learn How Some Materials Mix Easily While Others Won't Mix At All. Gives Examples Students Can Use To Make A Physical Mixture And Gives Detailed Information On How Different Components Make Up Different Solutions.
The most comprehensive, single-volume guide to conductingexperiments with mixtures "If one is involved, or heavily interested, in experiments onmixtures of ingredients, one must obtain this book. It is, as wasthe first edition, the definitive work." -Short Book Reviews (Publication of the International StatisticalInstitute) "The text contains many examples with worked solutions and with itsextensive coverage of the subject matter will prove invaluable tothose in the industrial and educational sectors whose work involvesthe design and analysis of mixture experiments." -Journal of the Royal Statistical Society "The author has done a great job in presenting the vitalinformation on experiments with mixtures in a lucid and readablestyle. . . . A very informative, interesting, and useful book on animportant statistical topic." -Zentralblatt fur Mathematik und Ihre Grenzgebiete Experiments with Mixtures shows researchers and students how todesign and set up mixture experiments, then analyze the data anddraw inferences from the results. Virtually every technique thathas appeared in the literature of mixtures can be found here, andcomputing formulas for each method are provided with completelyworked examples. Almost all of the numerical examples are takenfrom real experiments. Coverage begins with Scheffe latticedesigns, introducing the use of independent variables, and endswith the most current methods. New material includes: * Multiple response cases * Residuals and least-squares estimates * Categories of components: Mixtures of mixtures * Fixed as well as variable values for the major componentproportions * Leverage and the Hat Matrix * Fitting a slack-variable model * Estimating components of variances in a mixed model using ANOVAtable entries * Clarification of blocking mates and choice of mates * Optimizing several responses simultaneously * Biplots for multiple responses
