Mark S. Handcock
Topics vary. Prerequisite: permission of instructor. Offered: AWSp.
In this course we will start from scratch and introduce practical nonparametric, distribution-oriented and graphical analytic methodological tools to aid social science research.
We will follow the topics of traditional methods courses: univariate and multivariate summaries; simple and multivariate regression. These will be supplemented by quantile regression, methods for categorical data and an overall emphasis on distributional comparisons.
These methods aim to bridge the gap between exploratory tools and parametric restrictions. The goal is to present the concepts, theory and practical aspects of the methods in a coherent fashion, with a minimum of statistical prerequisites.
Student learning goals
General method of instruction
There will be a two lectures per week. The lecture on Thursday will sometimes be a laboratory session.
It is recommended that the student have taken the core methods sequence in their program.
Class assignments and grading
There will be weekly homeworks and exercises relating to computing and programming. Students will be graded on a scale of 1 to 10 for each homework.
Grades will be on a digit scale. They will be based on the assigments and the final protect.