Program Change Involving STAT 201 and MeEn 273
Program Change in effect Fall 2023
Which option should you pursue?
We recommend that you pursue Option A if:
- You have already taken STAT 201 or MeEn 273
- You have not yet taken STAT 201 or MeEn 273, but you are ready to take MeEn 273 in Winter or Spring 2023
If you pursue Option A, be sure to take MeEn 273 in Winter or Spring 2023—it will not be offered after that.
We recommend that you pursue Option B if:
- You have not yet taken STAT 201 or MeEn 273, and you are not ready to take MeEn 273 in Winter or Spring 2023.
If you pursue Option B, note that MeEn 275 will be offered for the first time in Fall 2023 (and then every fall, winter, spring after that).
Frequently Asked Questions
FAQs - General Questions
Toggle ItemWhat brought about this change?
We love getting feedback from our students through a variety of channels (student ratings and comments, standardized engineering tests, exit interviews, surveys taken years after graduation, etc); we review and discuss this feedback regularly, and then decide how to address it and make improvements to our program. In particular, we’ve learned that our students would benefit from more experience with computer programming, and from better integration of statistics into our program. For these reasons, we’ve decided to increase the amount of computer programming instruction by requiring CS 110 or CS 111, and we’ve decided to integrate statistics and numerical methods into a new course, MeEn 275 (Computational Methods in Engineering).
FAQs - Questions about Option A
Toggle ItemWhen is the last time that MeEn 273 will be offered?
The last times this course will be taught will be in Winter 2023 and Spring 2023.
Toggle ItemWill STAT 201 be retired?
No. Students in many engineering and science majors will continue to take STAT 201.
FAQs - Questions about Option B
Toggle ItemShould I take CS 110 or CS 111?
Toggle ItemIs it really okay if I only take CS 110? Will I not be behind compared to students who have taken CS 111?
In subsequent MeEn courses (such as MeEn 275) that require CS 110 or CS 111 as a prerequisite, we will assume that you understand what was taught in CS 110. We will build on that understanding, teaching you what you need to be successful in mechanical engineering courses and applications in the future.
Toggle ItemWhy might I want to take CS 111?
If you have programming experience before taking CS 110 or CS 111, you can skip CS 110 and take CS 111. This will allow you to learn more about Computer Science than you would have in CS 110, potentially opening up additional opportunities in the future. For example, some of our students decide to get a CS minor, and CS 111 is the first course required for the CS minor.
Toggle ItemWhat languages are taught in both CS 110 and CS 111?
Python is the primary language taught in both classes.
Toggle ItemWhat languages are needed for MeEn 275?
Much of MeEn 275 relies on Python, and we expect students to have learned Python in CS 110 or CS 111 before entering MeEn 275. In addition, in MeEn 275 we introduce students to Matlab.
Toggle ItemWhere can I find more details about Me EN 275?
We expect that the following information will be listed in the undergraduate catalog:
- Course title: Computational methods in engineering
- Course description: Numerical methods and statistics for engineers, implemented using software and computer programming
- Credit load: 3 credits (3 lecture hours and 2 lab hours per week)
- Taught: Fall, Winter, Spring (starting in Fall 2023)
- Math 113
- CS 110 or CS 111
- Math 302 or Math 314 or concurrent
- Learning outcomes:
- Fundamentals of Numerical Methods:
- 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.
- Numerical Methods –Approximating Integrals and Derivatives:
- Students will apply numerical methods fundamentals to appropriately compute approximations of integrals and derivatives.
- Numerical Methods –Solving Equations:
- Students will apply numerical methods fundamentals to solve non-linear equations and systems of linear equations.
- Numerical Methods –Approximating Solutions of Ordinary Differential Equations:
- Students will apply numerical methods fundamentals to appropriately compute approximate solutions to ordinary differential equations.
- Fundamentals of Statistics:
- Students will apply fundamental concepts of statistics (including randomness and uncertainty) and a knowledge of methodological advantages and limitations to solve engineering problems.
- Statistics –Descriptions of Data:
- Students will apply statistical fundamentals to appropriately describe data distributions using measures of central tendency, spread, and data visualization techniques.
- Statistics –Estimating Data Patterns:
- Students will apply statistical fundamentals and generalized linear regression to obtain and assess least-squares approximations to data sets.
- Statistics –Estimating Statistical Significance:
- Students will apply statistical fundamentals to calculate confidence intervals, perform basic hypothesis testing (t-test, paired t-test, etc.), and correctly interpret p-values
- Programming Languages:
- 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.
- Real-World Problem Solving –Explore:
- Students will learn the BYU ME methodology for exploring the solution space of engineering problems.
- Real-World Problem Solving –Communicate:
- Students will be introduced to the importance of clear, concise, and convincing communication and apply these principles by writing effective technical memos.
- Fundamentals of Numerical Methods:
For additional questions, please contact our undergraduate advisor, Miriam Busch, or current peer advisor, Ryan Hanson.
Miriam has open office hours 9-4pm on M-F (360R EB) and can also be reached via email (email@example.com) and phone (801-422-2624).
The peer advisor can be reached via email (firstname.lastname@example.org) and phone (801-422-8091).