This page compiles graduate level Statistics courses offered by different universities. My aim is to reach to the graduate students who like to get information on the courses in a same place. Hope that it will help. Harvard graduate level Statistics course tree is below to get the idea of the course sequences.
Regression analysis allows us to model, examine, and explore relationships, and can help explain the factors behind observed patterns. It's is also used for prediction.
Design of experiments (DOE) is a systematic method to determine the relationship between factors affecting a process and the output of that process. In other words, it is used to find cause-and-effect relationships.
Classical linear models are the most commonly used set of statistical techniques in practice. The classes are (1) linear regression models, and (2) analysis of variance (ANOVA) models, and (3) analysis of covariance models (ANCOVA) models.
Professor in the Department of Statistics in University of South Carolina.
Asso. Professor in the Department of Political Science, Pennsylvania State University.
Asso. Professor in the Department of Political Science, Pennsylvania State University.
Graduate student in the cognitive science dept. at the University of California, Merced.
Collection of questions for PhD qualifying exams and solutions. A stack exchange list is also ood to look at.
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