Tackling all the obstacles that are associated with presenting research, this handy guide will help students successfully and productively present relevant and engaging material.

This book explores the fun things researchers can do with logistic regression, explicates and simplifies the confounding complexities of understanding what logistic regression is, and provides evidence-based guidance as to what the best practices in performing logistic regression are.

Building on the authors' experience with their own doctoral students, this easy-to-read guide, helps and encourages students to write and complete their thesis faster.

This book summarizes the most important questions about basic statistics from the simple understanding of summary statistics to more sophisticated inferential statistics

Demonstrating the use of spatial analysis in the social sciences within a regression framework, the second edition of this text employs examples based on real data to illustrate the concepts discussed. The authors also provide relevant code to enable the users to work through the examples in the text.

Takes the panic out of sampling designs and helps students understand what sampling is, how it applies to different types of situations, and how to decide what approach works best for their project so they can maximize the impact of their research.

This book reflects recent attention in both the press and peer-reviewed research on learning through online engagement, whether formally through online classes and MOOCs or informally within game environments and popular culture discussion boards.

Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more examples of transformations; and the inclusion of the measures of tolerance and VIF within the discussion about collinearity.