Faculty and students praise the book's proven ability to generate class discussion, increase faculty-student engagement, and enhance student learning. Through clear writing, a balanced theoretical approach, and engaging examples, Miller stresses the importance of social inequality, cultural change, and applied aspects of anthropology throughout the book. Each chapter highlights an example of applied anthropology and connects with students by providing practical tips about how they can use anthropology in their everyday lives and careers. The last two chapters address how migration is changing world cultures and the importance of local cultural values and needs in shaping international development policies.

    And they do so, the author tells us, because of the seemingly inescapable pain in their own lives.In Hurt People Hurt People, Dr. Sandra Wilson brings her years as a professional counselor to bear on a difficult topic that affects many of us.Let her warmth and insight lead you toward a heart of compassion and a ministry of healing for those who hurt others.

    The author team includes the most preeminent and respected researchers in abnormal psychology today. Now, the exciting revision of this classic introduces new topics and fresh insights, as well as a streamlined writing style and a sharper focus on research in psychopathology. The esteemed author team of Butcher, Mineka, and Hooley offers students the most thoroughly researched and up-to-date explanation of psychopathology, creating a learning experience that invokes thought, increases awareness, and takes students to levels of understanding that other books do not offer.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results