The book uses the theme of evolution to develop a broad-scale view of animal diversity--students focus not only the organisms themselves, but also the processes that produce evolutionary diversity. The book is unique in its comprehensive survey of zoological diversity and its emphasis on evolutionary, systematic and ecological principles, all in one package.

    In clear, lively, warm prose, this edition continues the title's integration of gender, culture, and ethnicity. By the end, readers will learn how to interpret research and to address and resolve controversies. MyPsychLab is an integral part of the Wade/Tavris/Garry program. Engaging activities and assessments provide a teaching and learning system that helps students think like a psychologist. With MyPsychLab, students can watch videos on psychological research and applications, participate in virtual classic experiments, and develop critical thinking skills through writing. "Invitation to Psychology, "5/e is available in a new DSM-5 Updated edition. To learn more, click here. This title is available in a variety of formats - digital and print. Pearson offers its titles on the devices students love through Pearson's MyLab products, CourseSmart, Amazon, and more.

    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Chapters cover cancer, infection, immune disorders, genetics, and disorders of each body system, highlighting pathophysiologic processes, resulting signs and symptoms, diagnostic test findings, and current treatments. Reader-friendly features include illustrations, checklists, and full-color miniguides illustrating the pathophysiology of specific disorders.This edition has new full-color miniguides on cancer pathophysiology and neuropathology. A new Focus on Genetics feature identifies gene-related discoveries and their implications for treatment or diagnosis. Review questions and answers follow current NCLEX-RN® requirements and alternate-format questions are included.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    The text's major theme "Changes, Choices, and Constraints" explores: Contemporary "changes "in families and their structure Impacts on the "choices "that are available to family members ""Constraints ""that often limit our choices Through this approach, students are better able to understand what the research and statistics mean "for themselves"! Marriages and Families balances theoretical and empirical discussions with practical examples and applications. It highlights important contemporary changes in society and the family. This text is written from a sociological perspective and incorporates material from other disciplines: history, economics, social work, psychology, law, biology, medicine, family studies, women's studies, and anthropology. "More about the themes: " "Changes"Examines how recent profound structural and attitudinal changes affect family forms, interpersonal relationships, and raising children. It reaches beyond the traditional discussions to explore racial-ethnic families, single-parent families and gay families as well as the recent scholarship by and about men, fathers, and grandfathers. Contemporary American marriages and families vary greatly in structure, dynamics, and cultural heritage. Thus, discussions of gender roles, social class, race, ethnicity, age, and sexual orientation are integrated throughout this book. To further strengthen students understanding of the growing diversity among today's families, the author included a series of boxes that focus on families from many cultures. "Choices"On the individual level, family members have many more choices today than ever before. People feel freer to postpone marriage, to cohabit, or to raise children as single parents. As a result, household forms vary greatly, ranging from commuter marriages to those in which several generations live together under the same roof. "Constraints"Although family members choices are more varied today, we also face greater macro- level constraints. Our options are increasingly limited, for example, by government policies. Economic changes often shape family life and not vice versa. Political and legal institutions also have a major impact on most families in tax laws, welfare reform, and even in defining what a family is. Because laws, public policies, and religious groups affect our everyday lives, the author has framed many discussions of individual choices within the larger picture of the institutional constraints that limit our choices.To learn more about the new edition, click here to visit the showcase site.

    Never again will you order the Poisson Distribution in a French restaurant!This updated version features all new material.

    I also hope that it will serve as a useful reference too for the many workers engaged in one type of solid state research activity or another, who may be without formal training in the subject.

    While the mathematics is there, the effort is not all concentrated on proofs. Strang's emphasis is on understanding. He explains concepts, rather than deduces. This book is written in an informal and personal style and teaches real mathematics. The gears change in Chapter 2 as students reach the introduction of vector spaces. Throughout the book, the theory is motivated and reinforced by genuine applications, allowing pure mathematicians to teach applied mathematics.

    The first abnormal psychology book to present a thoroughly integrated multicultural perspective--based on the authors' view that cross-cultural comparisons can greatly enhance the understanding of disorders--the text provides extensive coverage and integration of multicultural models, explanations, and concepts. The book also helps you gain an understanding of abnormal behavior as scientific and clinical endeavors, while providing insight into the tools that mental health professionals use to study and treat disorders.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    Fundamentals of Biostatistics with CD-Rom.

    This work focuses on the maths skills necessary to pass the GMAT, with nearly 300 questions and explanations on subjects such as arithmetic, algebra, geometry and data sufficiency.