Statistical Modeling and Inference for Social Science

PURPOSE

This text is written for a first course on statistics and quantitative methods for Ph.D. students in social science and allied fields. Anyone undertaking to write such a book must sooner or later confront the question of whether the world really needs another introductory statistics textbook. In my surveys of the market for my own classes on this subject in two social science Ph.D. programs, I clearly decided that it does.

Students in social science Ph.D. programs outside of economics have widely divergent levels of previous exposure to statistical methods, as well as comfort with mathematical expression of concepts. The typical Ph.D. program does not have the luxury of multiple “tracks” to suit different backgrounds, so one course must accommodate all of them. That course must be accessible to students with divergent levels of preparation but must also prepare them technically for future quantitative methods coursework ahead of them.

More important, I have found that students of whatever background will plunge relatively enthusiastically into methods training once they understand why it is essential for the purely substantive elements of their research. Simply put, many students, particularly those without much prior exposure to statistics, do not understand what it is or how it can help them as social scientists. Without this understanding they lack the buy-in necessary to make the technical rigors of the course seem worthwhile.