Instructor Insights pages are part of the OCW Educator initiative, which seeks to enhance the value of OCW for educators.
This page focuses on the course 14.381 Statistical Method in Economics as it was taught by Prof. Anna Mikusheva in Fall 2013.
Statistical Method in Economics is part of the Economics Department’s sequence on Statistics and Econometrics. It provides an introduction to probability and statistics as background for advanced econometrics and introduction to the linear regression model. 14.381 highlights illustrations from economics and the application of these concepts to economic problems.
Note: 14.381 is divided into two sections and is co-taught by Prof. Mikusheva and another instructor. The Fall 2013 version of 14.381 on OCW focuses on the first part of the course. See the 2006 offering of 14.381 to learn about the second part of the course.
Course Goals for Students
The main objective of this course is to develop the basic skills needed to do statistical analysis of data. The course aims to provide students with techniques and receipts for estimation, hypothesis testing and confidence set construction.
- H-Level graduate credit
- Serves as a prerequisite for the econometrics and statistics core requirements for the Economics Ph.D.
Every fall semester
The students' grades were based on the following activities:
Breakdown by Year
All of the students were Ph.D. students.
Breakdown by Major
Almost all of the students are Economics Ph.D. students, though some Ph.D. students from the Sloan School of Management, political science, and engineering enroll.
During an average week in the spring semester, students were expected to spend 14.5 hours on the course, roughly divided as follows:
- Met 2 times per week for 1.5 hours per session; 13 sessions total.
- The midterm exam was taken during one of the sessions.
- Met one time per week for 1.5 hours.
- Discussed topics covered in that week’s lecture and reviewed sample problems.
Out of Class
The students had six problem sets to work on outside of class.