ENGR 2104 Engineering Foundations Studio IV
This course provides students the mathematical and statistical foundation for analyzing engineering systems. Topics include descriptive statistics, probability theory, regression analysis, probability distributions (Binomial, Poisson, Normal, Exponential), confidence intervals, hypothesis testing, and statistical process control, as well as graphical description of data. Additional topics include mathematical definition of reliability and uncertainty quantification. In the hands-on lab portion of the class, students apply these concepts to engineering decision-making, quality control, and predictive modeling, to connect the theoretical analysis with practical engineering applications.
Course overview
- Department
- Engineering
- School
- MCAS
- Credits
- 4
- Level
- Undergraduate
- Offered
- Annually
Catalog details
Requirements fulfilled
Course evaluations
- Course rating
- 3.55 / 5 · Very Good
- Instructor rating
- 3.94 / 5 · Very Good
- Terms evaluated
- 4
| Term | Instructor | Course overall | Instructor overall | Well organized | Clear learning objectives | Intellectually challenging | Helpful assignments | Applicable beyond course | Attendance necessary | Weekly effort | Responses |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Spring 2026 | Justin Henriques | 3.6 | 3.8 | 3.9 | 4.1 | 4.0 | 4.4 | 4.5 | 4.1 | 4–6 hrs/week | 71 of 88 |
| Spring 2025 | Amin Mohebbi | 3.4 | 4.3 | 4.1 | 4.3 | 3.6 | 4.0 | 4.1 | 3.7 | 1–3 hrs/week | 37 of 38 |
| Spring 2025 | Justin Henriques | 2.8 | 3.1 | 3.1 | 3.5 | 3.8 | 3.6 | 4.0 | 3.5 | 4–6 hrs/week | 52 of 54 |
| Spring 2024 | Amin Mohebbi | 3.7 | 4.2 | 4.3 | 4.3 | 4.0 | 4.4 | 4.4 | 4.2 | 4–6 hrs/week | 67 of 70 |
| Spring 2024 | Jonathan Krones | 4.7 | 4.9 | 5.0 | 5.0 | 5.0 | 4.8 | 4.8 | 4.8 | 10+ hrs/week | 24 of 30 |
| Spring 2023 | Jonathan Krones | 3.6 | 3.9 | 3.9 | 4.0 | 4.4 | 4.0 | 4.1 | 4.4 | 1–3 hrs/week | 37 of 54 |
Data freshness
Instructors
Sections
- Section 01
- Section 02
- Section 03
- Section 04