1. Introduction; 2. Examining univariate distributions; 3. Measures of location, spread, and skewness; 4. Re-expressing variables; 5. Exploring relationships between two variables; 6. Simple linear regression; 7. Probability fundamentals; 8. Theoretical probability models; 9. The role of sampling in inferential statistics; 10. Inferences involving the mean of a single population when is known; 11. Inferences involving the mean when is not known: one- and two-sample designs; 12. Research design: introduction and overview; 13. One-way analysis of variance; 14. Two-way analysis of variance; 15. Correlation and simple regression as inferential techniques; 16. An introduction to multiple regression; 17. Nonparametric methods.
Sharon Lawner Weinberg is Professor of Applied Statistics and Psychology and former Vice Provost for Faculty Affairs at New York University. She has authored numerous articles, books, and reports on statistical methods, statistical education, and evaluation, as well as in applied disciplines, such as psychology, education, and health. She is the recipient of several major grants, including a recent grant from the Sloan Foundation to support her current work with colleagues from New York University to evaluate the New York City Gifted and Talented programs. Sarah Knapp Abramowitz is Professor of Mathematics and Computer Science at Drew University, where she is also Department Chair and Coordinator of Statistics Instruction. She is the coauthor, with Sharon Lawner Weinberg, of Statistics Using IBM SPSS: An Integrative Approach, 3rd edition (Cambridge, forthcoming 2016) and an Associate Editor of the Journal of Statistics Education.