About
Table of contents
Class Description
ME 103 introduces students to the principles and practice of measuring physical quantities in mechanical systems, with an emphasis on how real-world data are generated, interpreted, and communicated. The course develops a rigorous understanding of measurement error and uncertainty—both systematic bias and random variation—and trains students to quantify, propagate, and mitigate these effects using probabilistic and statistical tools. Students gain hands-on experience with a wide range of sensors and transducers (mechanical, thermal, optical, magnetic, and electronic) for measuring displacement, velocity, acceleration, strain, temperature, pressure, and flow, alongside modern data-acquisition and analysis software. Core topics include experimental design (including factorial designs), hypothesis testing and non-parametric methods, frequency-domain analysis (Nyquist criterion, aliasing, FFTs, and Bode plots), and dynamic response of measurement systems. Through a creative, open-ended team measurement project, students practice the full experimental workflow—from planning and setup to data analysis and interpretation—while developing strong technical communication skills via formal written reports and oral presentations.
Prerequisites
While ME 109 is listed as a prerequisite for this course, it is not required to succeed in ME 103. The course is designed so that students can be successful regardless of whether they have taken (or are concurrently taking) ME 109, and no prior knowledge from ME 106 will be assumed. Students are expected to be comfortable with core ME 100 concepts, basic laboratory skills such as breadboarding, and elementary statistics. Familiarity with MATLAB or Python is helpful but not strictly required. Some topics may overlap with courses such as E178 or ME 132; however, students without this background will be fully supported and prepared to succeed. Students with questions about their preparation are encouraged to speak with a member of the course staff.
Desired Course Outcomes
The primary objective of ME 103 is to develop students’ ability to design, execute, analyze, and communicate high-quality engineering experiments. The course emphasizes experimental reasoning, measurement uncertainty, sensor physics, and data analysis techniques that are essential for validating mechanical systems and investigating physical phenomena. Through structured laboratories and an open-ended team measurement project, students will gain hands-on experience translating physical questions into measurable quantities, selecting and characterizing sensors, and interpreting imperfect data using statistical and frequency-domain tools. Communication is a central focus of the course; students will practice presenting experimental results clearly and rigorously in both written and oral formats.
Students who successfully complete ME 103 should be able to:
- Design and plan experiments that effectively address engineering questions while accounting for uncertainty, bias, and variability.
- Select, implement, and characterize sensors for measuring mechanical, thermal, and fluid quantities.
- Analyze experimental data using appropriate statistical, regression, and frequency-domain methods.
- Evaluate the limitations of measurement systems, including dynamic response, noise, and sampling effects.
- Communicate experimental methods, results, and conclusions clearly through technical reports, figures, and oral presentations.
Please see the course homepage for a detailed weekly breakdown of topics and laboratory activities.