# Professor Luc Chouinard Reviews

2

Class Ratings

4Good Class
4Easy
5Very Interesting
5Very Useful

Professor Rating

Prof: Luc Chouinard / Fall 2021

Dec 20, 2021

A course on structural mechanics, focusing on cases of static equilibrium.

Course Content

Vectors Mechanics: 2-D, 3-D, forces, moments, couples, and wrenches, Varignon's Theorem, components, vector algebra (summation, dot product, cross product, RHR), resultants. Static Equilibrium: types of constraints, static determinacy. Structures: trusses, members, internal forces, methods of analysis, machines. Centroids: Theorem of Pappus, methods of analysis, distributed forces. Beams: axial, shear, and bending moment diagrams. Cables: Flexible, parabolic, and catenary cables. Hydrostatics: fluid pressure on a surface, buoyancy. Methods of analysis. Friction: linear and cable friction. Moments of Inertia: Methods of analysis, Parallel Axis Theorem, products of inertia, rotation of axes, Mohr's Circle.

Mostly just read off of his slides which are copied from the textbook. Curves the final grade though.

Do practice questions and attend tutorials.

Exam HeavyAssignment Heavy
1

Class Ratings

4Good Class
3Avg. Difficulty
5Very Interesting
4Useful

Professor Rating

3OK Prof

Prof: Luc Chouinard / Winter 2023

May 23, 2023

A practical course on probability and statistics with emphasis on problem solving. When I took this class the prof used a Wiley Plus pilot project, so I didn't need to pay anything for the Wiley Plus textbook and companion software. The professor wanted to keep up attendance rates so he had in-person quizzes at the end of every lecture. These quizzes were only marked for completion.

Course Content

Probability: sample space, Venn Diagram, Event Relation Laws, DeMorgan's Laws, counting techniques, permutations and combinations, sampling with or without replacement, Axioms of Probability, Addition Rules, conditional probability, Multiplication Rule, Total Probability Rule, independent events, Bayes' Theorem Discrete Random Variables and Probability Distributions: probability mass function, cumulative distribution function, mean, variance, discrete uniform distribution, binomial distribution, geometric distribution, Poisson distribution, negative binomial distribution, hypergeometric distribution Continuous Random Variables and Probability Distributions: probability density function, continuous uniform distribution, normal distribution, standard normal distribution, standardizing, nor...read more  