ME EN 275
Computational Methods in Engineering
Mechanical Engineering
Ira A. Fulton College of Engineering
Course Description
Numerical methods and statistics for engineers, implemented using software and computer programming
When Taught
Fall, Winter, Spring
Grade Rule
Grade Rule 8: A, B, C, D, E, I (Standard grade rule)
Fixed
3
Fixed
3
Fixed
2
Other Prerequisites
Math 302 or Math 314 or concurrent
Title
Title: Fundamentals of Numerical Methods
Learning Outcome
Students will apply fundamental principles of numerical methods (including round-off error, truncation error, and convergence) and a knowledge of methodological advantages and limitations to solve engineering problems.
Title
Numerical Methods – Approximating Integrals and Derivatives
Learning Outcome
Students will apply numerical methods fundamentals to appropriately compute approximations of integrals and derivatives.
Title
Numerical Methods – Solving Equations
Learning Outcome
Students will apply numerical methods fundamentals to solve non-linear equations and systems of linear equations.
Title
Numerical Methods – Approximating Solutions of Ordinary Differential Equations
Learning Outcome
Students will apply numerical methods fundamentals to appropriately compute approximate solutions to ordinary differential equations.
Title
Fundamentals of Statistics
Learning Outcome
Students will apply fundamental concepts of statistics (including randomness and uncertainty) and a knowledge of methodological advantages and limitations to solve engineering problems.
Title
Statistics – Descriptions of Data
Learning Outcome
Students will apply statistical fundamentals to appropriately describe data distributions using measures of central tendency, spread, and data visualization techniques.
Title
Statistics – Estimating Data Patterns
Learning Outcome
Students will apply statistical fundamentals and generalized linear regression to obtain and assess least-squares approximations to data sets.
Title
Statistics – Estimating Statistical Significance
Learning Outcome
Students will apply statistical fundamentals to calculate confidence intervals, perform basic hypothesis testing (t-test, paired t-test, etc.), and correctly interpret p-values.
Title
Programming Languages
Learning Outcome
Using Excel, MATLAB, and Python, students will perform numerical/statistical analyses using their own code as well as packages/libraries while demonstrating best practices in programming techniques.
Title
Real-World Problem Solving – Explore
Learning Outcome
Students will learn the BYU ME methodology for exploring the solution space of engineering problems.
Title
Real-World Problem Solving – Communicate
Learning Outcome
Students will be introduced to the importance of clear, concise, and convincing communication and apply these principles by writing effective technical memos.
