Intermediate Statistics: A Conceptual Course

Intermediate Statistics: A Conceptual Course is a student-friendly text for advanced undergraduate and graduate courses. It begins with an introductory chapter that reviews descriptive and inferential statistics in plain language, avoiding extensive emphasis on complex formulas. The remainder of the text covers 13 different statistical topics ranging from descriptive statistics to advanced multiple regression analysis and path analysis. Each chapter contains a description of the logic of each set of statistical tests or procedures and then introduces students to a series of data sets using SPSS, with screen captures and detailed step-by-step instructions. Students acquire an appreciation of the logic of descriptive and inferential statistics, and an understanding of which techniques are best suited to which kinds of data or research questions.

Table of Contents:
Chapter 1: A Review of Basic Statistical Concepts Chapter 2: Descriptive Statistics Chapter 3: Linear and Curvilinear Correlation Chapter 4: Non-Parametric Statistics (Tests Involving Nominal Variables) Chapter 5: Reliability (and a Little Bit of Factor Analysis) Chapter 6: Single-sample and two-sample t-tests Chapter 7: One-way and Factorial Analysis of Variance (ANOVA) Chapter 8: Within-Subjects and Mixed Model Analyses Chapter 9: Multiple Regression Chapter 10: Examining Interactions in Multiple Regression Chapter 11: ANCOVA, Covariate Adjusted Means, and Predicted Scores Chapter 12: Suppressor Variables Chapter 13: Mediation and Path Analysis Chapter 14: Data Cleaning Chapter 15: Data Merging and Data Management Chapter 16: Avoiding Bias: Characterizing without Capitalizing

About the Author :
Brett Pelham grew up as the second of six children near the small town of Rossville, Georgia. Brett received his B.S. from Berry College in 1983 and received his Ph.D. from the University of Texas at Austin in 1989. He began thinking about this book while teaching statistics at UCLA but got serious about doing so while teaching statistics at UB (in Buffalo, NY). After leaving UB, Brett worked for a year as a visiting professor in marketing at Georgetown University. He was then lucky enough to work for about two years as a senior research analyst at Gallup. This was followed by two not-so-lucky years as a Program Director at the National Science Foundation. At the time of this writing (in January 2012) Brett was extremely excited to have just taken a position promoting graduate and postgraduate education in the Education Directorate at the American Psychological Association. With apologies to Lenny Bruce, you can see that Brett has had some difficulties holding down a regular job recently. The bulk of his research focuses on automatic social judgment and self-evaluation. Over the past two decades, he has taught courses in social psychology, research methods, statistics, social cognition, and the self-concept. In his spare time, he enjoys juggling, sculpting, listening to alternative rock music, cooking, and traveling. His two favorite activities while completing this textbook (in late 2011) were spending time with his 3-year-old daughter Brooklyn and his 8-year-old son Lincoln. Along with his wife LJ Pelham, Brett is co-inventor of the recently released card game PRIME. Along with his son Lincoln, he is co-inventor of the soon-to-be-released card game Cliff-Hanger. Along with his daughter Brooklyn, he is co-inventor of the never-to-be-released card game It’s a Hat. You Like It? His most recent writing project is a novel tentatively entitled Elvis 2.0, which focuses on scientific and religious problems associated with the apparent resurrection of Elvis Presley.

Review :
“The text is highly readable, and the author has done a good job making difficult topics like path analysis easy for students to comprehend. As much as possible, the author uses simple language and explains things in ways that students would be able to grasp. His incorporation of numerous examples helps to facilitate this goal as well.” “The key strengths of this text are is applied perspective, focusing on conceptual understanding of data analyses rather than arcane statistical proofs. It finds just the right balance of technical, conceptual and practical perspectives. In addition, the heavy reliance on real-world examples and supplemental information in appendices will render it an invaluable resource for young graduate students as they progress in their research training.” “This is a breath of fresh air compared to most statistics texts—rigorous but highly readable. The author does an impressive job of making statistical concepts feel intuitive. In addition, the integration of datasets and SPSS problems to solve make this book unique.”