How useful is numerical analysis? (compared to other topics)

In summary, numerical analysis is a branch of mathematics that uses algorithms to solve problems with continuous variables. It is different from other topics in science because it relies on numerical methods instead of analytical methods. It is a useful skill for scientists in all fields, allowing for efficient and accurate solutions. It can be applied to real-world problems in various fields. However, it may not always be as accurate as analytical methods and requires a lot of computational power. To improve skills in numerical analysis, one can study principles and algorithms, practice with software, and stay updated on new developments.
  • #1
Simfish
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I know that Matlab is essentially a giant numerical analysis package, so numerical analysis is helpful for anything that involves Matlab or FORTRAN or non-symbolic programming languages (or processes that use approximations of differential equations and stuff). So pretty much anything with giant data analysis requires some numerical analysis (atmospheric science, physical oceanography, physical science, astrophysics, etc).

I've always had the feeling that theoretical physicists and mathematicians disdained numerical analysis. Maybe it isn't useful for them. But for the rest of us, is it possibly more useful than perhaps any other field of math/physics?
 
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  • #2
Numerical analysis is incredibly useful in many fields, not just for Matlab or FORTRAN programming. It can be used in virtually any field that involves data analysis such as atmospheric science, physical oceanography, physical science, and astrophysics. Numerical analysis techniques are used to solve problems using approximations of differential equations, which can provide more accurate results than traditional mathematical techniques. As a result, numerical analysis is often considered to be more useful than other types of mathematics or physics.
 

1. How is numerical analysis different from other topics in science?

Numerical analysis is a branch of mathematics that focuses on developing and implementing algorithms for solving problems involving continuous variables. It differs from other topics in science because it is specifically geared towards solving problems using numerical methods rather than analytical methods.

2. Is numerical analysis a useful skill for scientists in all fields?

Yes, numerical analysis is a useful skill for scientists in all fields because it allows for the efficient and accurate solution of complex problems that would be difficult or impossible to solve analytically. It is especially important in fields such as physics, engineering, and economics.

3. Can numerical analysis be applied to real-world problems?

Yes, numerical analysis is commonly used to solve real-world problems in various fields. For example, it is used in weather forecasting, designing aircraft, analyzing financial markets, and many other applications where precise and efficient solutions are needed.

4. What are the limitations of numerical analysis compared to other methods?

Numerical analysis is not always as accurate as analytical methods, as it involves rounding and approximation. It also requires a lot of computational power and may take longer to obtain a solution compared to analytical methods. Additionally, some problems may not be easily solvable using numerical methods.

5. How can one learn and improve their skills in numerical analysis?

One can learn and improve their skills in numerical analysis by studying mathematical principles and algorithms, practicing with numerical analysis software, and working on various numerical analysis problems. It is also helpful to stay updated on new developments and techniques in the field.

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