Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code and data sets for examples within the text can be found on an accompanying website.
Integrating foundational concepts with beginner-friendly R programming, this student-friendly text introduces the reader to statistics with R through an exploration of the world's "tricky problems" faced by the book's characters. Inspired by the programming group "R Ladies," the book's "R Team" works together to master the skills of statistical analysis and data visualization to untangle real-world messy data using R. The storylines draw students in to solving interesting real problems, leading them step-by-step through full-color illustrations of R statistics and interactive exercises.
Deviant Behavior covers the social forces that shape deviance, the motivations and consequences of deviant behaviors, and how our definition of deviance changes over time. Authors John A. Humphrey and Frank Schmalleger discuss a wide range of deviant behaviors-from criminal acts to extreme forms of everyday behavior-and provide students the necessary foundation to understand the impact of globalization on traditional and emerging forms of deviance.
Entrepreneurial Marketing: A Blueprint for Customer Engagement offers a cutting-edge perspective on how to create a customer-centric, multi-channel marketing program.
Negotiation: Moving from Conflict to Agreement helps students see how negotiation is all around them. Using both every day and business examples, the authors emphasize not just what to do during a negotiation-but also why. With an emphasis on the psychology of negotiation levers such as reciprocity, uncertainty, power, and alternatives, the text helps students understand when to use certain tactics to get more.
Carol A. Chapelle shows readers how to design validation research for tests of human capacities and performance. Any test that is used to make decisions about people or programs should have undergone extensive research to demonstrate that the scores are actually appropriate for their intended purpose. Argument-Based Validation in Testing and Assessment is intended to help close the gap between theory and practice, by introducing, explaining, and demonstrating how test developers can formulate the overall design for their validation research from an argument-based perspective.
Introduction to Cyber Politics and Policy is a comprehensive introductory textbook for cyber politics and security courses that bridges the gaps between the intricacies of technology and the theories of political science.
A History of Modern Psychology: The Quest for a Science of the Mind presents a history of psychology up to the turn of the 21st century. Author David C. Ludden, Jr. uses a topical approach to discuss key thinkers and breakthroughs within the context of various schools of thought, allowing students to see how philosophers, researchers, and academics influenced one another to create the rich and diverse landscape of modern psychology.
Access, Prepare, Visualize, Explore Data, and Write Papers
After a first chapter on installing the software and project setup, in the second chapter the authors shows how to write an essay using R Markdown, rewarding readers with an immediate tangible result, and taking the fear out of working with a new software. Student-friendly language and examples (e.g. binge-watched shows on Netflix, top 5 songs on Spotify), cumulative learning and repetition across chapters, and practice exercises make this a must-have guide for a variety of courses where data is used and reports need to be written (including, but not limited to intro statistics and research methods). Code and datasets used to carry out the examples in the book are available on an accompanying website.
