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Fundamentals of Statistical Modeling

Course Number:



Rebecca Lessem,


Undergraduate Economics


B.A. in Economics, Minor in Economics, Required

Course Description

The purpose of this course is to provide in a single semester an introduction to the formal tools of statistical inference that will enable students to take more advanced methods classes, such as the advanced data analysis sequence. By building on what should be a relatively broad experience with statistics and calculus from earlierĀ  courses, this course will emphasize three topics:
  1. Probability models and distribution theory, particularly, distributional properties of functions of random variables;
  2. The practice of statistical inference based on least squares and maximum ikelihood estimation; and
  3. Applications of statistical modeling and inference through several case studies. Since students are coming to this course with (i) a fairly broad statistical background in the sense of having a good solid foundation for data analysis, statistical practice, and a context for the use of statistics, and (ii) facility with the use of statistical software.

This course will provide the student with the necessary mathematical, statistical, and computing tools for the critical and thoughtful use of statistical models. Students who complete this course will be prepared to pursue more advanced studies in statistics either as a complement to another major or in a job setting.

Students who have taken 36-225 or 36-226 may not receive credit for this course.


Lecture: 160min/wk


J. Devore and K. Berk,"Modern Mathematical Statistics with Applications", Duxberry Press, 2007.