Numerical analysis vs functional analysis vs statistics for engineerin

In summary: However, for someone intending to study engineering or applied physics, the project would be more important.
  • #1
Hercuflea
596
49
Hey all, back with another question.

I have the opportunity in the fall to choose 1 (maybe 2 if I'm lucky) of the following classes: Numerical analysis (undergrad numerical linear algebra, using matlab), Functional Analysis (as a directed study course with a prof), and the other is doing a research project in statistics. The stats prof hasn't decided on the project, but I may convince her to let me work on Monte Carlo methods. If I want to go to graduate school in nuclear engineering, what order of importance would you place these classes? (I am working on the engineering pre reqs on the side as well).
 
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  • #2
In my opinion, the top choice hands down is the research project. In order to get into grad school you will need good recommendations - the most useful ones would be from people that you did a research project with! That is likely more important than what elective courses you took as an undergrad - you can make up coursework in grad school as needed. I am not a nuclear engineer so will refrain from any recommendations beyond this. I wish you the best.

jason
 
  • #3
Jason,

Thanks for the response. It is something I am carefully considering. It is only tentative as of now, but it does seem like it could be a promising project. I am just unsure about it because it may or may not be related to my ultimate research interest in graduate school, nuclear fusion.
 
  • #4
Hercuflea said:
Hey all, back with another question.

I have the opportunity in the fall to choose 1 (maybe 2 if I'm lucky) of the following classes: Numerical analysis (undergrad numerical linear algebra, using matlab), Functional Analysis (as a directed study course with a prof), and the other is doing a research project in statistics. The stats prof hasn't decided on the project, but I may convince her to let me work on Monte Carlo methods. If I want to go to graduate school in nuclear engineering, what order of importance would you place these classes? (I am working on the engineering pre reqs on the side as well).
If one is considering engineering, particularly nuclear engineering, and if one is interested in R&D/analysis/simulation, then go with numerical analysis and learn C++ and/or Fortran. I recommend engineering students get as much physics and mathematics as possible.
 
  • #5
Monte Carlo methods are used all over the place. Sounds like a good project. Absolutely make sure you learn C++ and Fortran before you graduate. You'd be amazed how many Fortran codes are still running out there and you may be asked to maintain one.
 
  • #6
Thanks astronuc and carlgrace for the input. So best case scenario, I do the project and numerical analysis, and dump functional analysis? Maybe later on I will take it.
 
  • #7
Hercuflea said:
Thanks astronuc and carlgrace for the input. So best case scenario, I do the project and numerical analysis, and dump functional analysis? Maybe later on I will take it.
For engineering or applied physics, I'd recommend the project and numerical analysis (with learning to program C++ and Fortran).

Rather than dump functional analysis, defer it. Functional analysis seems more appropriate if one is doing theoretical physics or mathematics.

Meanwhile, see this text - https://www.physicsforums.com/showthread.php?t=665468 - and others in the mathematics textbook discussion forum.

In control theory, an aspect of engineering, functional analysis would be useful.
 

Related to Numerical analysis vs functional analysis vs statistics for engineerin

1. What is the main difference between numerical analysis, functional analysis, and statistics for engineering?

Numerical analysis is a branch of mathematics that focuses on developing algorithms and methods for solving mathematical problems using numerical approximations. Functional analysis is a branch of mathematics that studies vector spaces and their linear transformations. Statistics for engineering is a field that applies statistical methods to analyze and interpret data in engineering applications.

2. Which one is more applicable in real-world engineering problems?

All three fields have applications in real-world engineering problems. Numerical analysis is useful for solving complex mathematical equations and models. Functional analysis is essential for understanding and analyzing systems and processes in engineering. Statistics is crucial for making data-driven decisions and predictions in engineering projects.

3. Can numerical analysis, functional analysis, and statistics be used together in engineering projects?

Yes, these three fields can be used together in engineering projects. For example, numerical methods can be used to solve differential equations in functional analysis, and statistical methods can be applied to analyze the results. In engineering, it is common to use a combination of different mathematical techniques to solve complex problems.

4. What are some common applications of numerical analysis in engineering?

Numerical analysis has numerous applications in engineering, including finite element analysis, optimization, and computational fluid dynamics. These methods are used to model and simulate real-world systems and processes, such as structures, machines, and fluids.

5. How can statistics be applied in engineering projects?

Statistics is used in engineering to analyze and interpret data, make predictions, and evaluate the performance of systems and processes. It is used in quality control, risk analysis, and design optimization. Additionally, statistics is crucial for making data-driven decisions in engineering projects.

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