ECON 1158 Statistical Computing: Programming in Stata

This course provides an introduction to statistical computing in the Stata environment for those who have not taken ECON1151 and its lab component. The course covers data management, statistics, and graphics components of the Stata language with hands-on exercises.

Course overview

Department
Economics
School
MCAS
Credits
1
Level
Undergraduate
Offered
Every Fall, Every Spring

Catalog details

Prerequisites
The course is not available for students who have taken ECON1151.

Catalog text is imported from the reviewed Boston College course snapshot. Confirm eligibility in EagleApps.

Course evaluations

Response-weighted averages from Boston College’s official course evaluations (Avalanche/Blue).

Course rating
3.75 / 5 · Very Good
92 responses
Instructor rating
4.00 / 5 · Very Good
92 responses
Terms evaluated
8
Most recent: Spring 2026

Scales: overall ratings run from 1 (poor) to 5 (excellent); agreement questions from 1 (strongly disagree) to 5 (strongly agree); weekly effort from 1 (up to 1 hour) to 5 (10 or more hours).

Evaluations by term and instructor
TermInstructorCourse overallInstructor overallWell organizedClear learning objectivesIntellectually challengingHelpful assignmentsApplicable beyond courseAttendance necessaryWeekly effortResponses
Spring 2026Anirudh Padinjaray Pisharam3.63.74.44.23.44.34.14.4—12 of 13
Spring 2026Federico Rodari4.64.84.74.64.34.44.34.41–3 hrs/week10 of 13
Spring 2025Vaibhav Ojha2.62.73.33.13.63.43.42.71–3 hrs/week11 of 14
Fall 2024Enrico Cristoforoni3.13.44.44.03.33.93.23.31–3 hrs/week9 of 11
Spring 2024Pietro Visaggio3.13.03.83.82.83.93.42.6—10 of 11
Spring 2023Shane Mcmiken4.14.54.74.74.24.54.14.31–3 hrs/week15 of 15
Fall 2022Arnab Palit4.24.84.74.74.34.84.54.61–3 hrs/week10 of 12
Spring 2022Esther Lee4.34.74.84.83.84.44.64.31–3 hrs/week12 of 23
Fall 2021Kritika Goel4.34.54.54.53.85.04.55.01–3 hrs/week3 of 10

Data freshness

Course and evaluation data last updated 2026-10-09. Source details and limitations are documented in Data Sources and Methodology.

Instructors

Sections

  • Section 01
    Spring 2027 · Instructor not listed · O'Neill Library 255 M 11:00AM-11:50AM · Offered
  • Section 02
    Spring 2027 · Instructor not listed · O'Neill Library 256 F 11:00AM-11:50AM · Offered
  • Section 01
    Fall 2026 · Mingyang Wei · Carney Hall 305 F 11:00AM-11:50AM · Offered
  • Section 02
    Fall 2026 · Luisa Wall · Mcguinn Hall 30 Th 09:00AM-09:50AM · Offered