Which math field is growing the fastest now?

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In summary, The conversation discusses the potential for new discoveries in the field of statistics due to chaos theory. While there is always ongoing research in all fields, some areas such as point-set topology may be considered stagnant. However, there are still areas to be explored, such as the use of nets and filters in topology and their connection to Riemann-Stieltjes integration.
  • #1
kramer733
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So my math teacher (who has a honours in math) said that his friend who's doing her phd on math told him (yes that's a lot of he says she says) that the field that's going to have the most discoveries is in statistics because of "chaos theory". Is this true? So does this mean that calculus, algebra have stagnated? Is there nothing else to discover?
 
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  • #2
There is research going on in all fields. See Calculus of Variations and Geometric Measure Theory, Homotopy Theory, etc. Perhaps Chaos Theory is special, but research is done where the person is interested and has a good background in; there are always things to discover.
 
  • #3
Actually, there are fields that are stagnant' tapped out, and are now at best
auxiliary. Point-set topology is one of them. Talk to anyone today about Lindeloff
spaces, metrizability, etc., and they will look at you as saying: what.?, or , why
would anyone care.?
 
  • #4
Bacle said:
Actually, there are fields that are stagnant' tapped out, and are now at best
auxiliary. Point-set topology is one of them. Talk to anyone today about Lindeloff
spaces, metrizability, etc., and they will look at you as saying: what.?, or , why
would anyone care.?

I think nets & filters could be added to that list, but I think nets should make a comeback. Prob 2H in Kelley's topology text could be part of a course on Riemann-Stieltjes integration. I think they've always been done in topology because nets & filters are equivalent but I don't seen why nets couldn't be done right after the Riemann integral, as if to say "see how much easier it is with nets?"
 
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  • #5
My impression is that point-set topology becomes more of set theory now days
 

1. What is the fastest-growing math field currently?

The fastest-growing math field currently is data science, also known as data analytics or big data. This field involves using mathematical and statistical methods to analyze and interpret large sets of data in order to make meaningful predictions and decisions. With the rise of technology and the increasing amount of data being generated, the demand for data scientists is rapidly growing.

2. What are the job prospects for mathematicians in the current job market?

The job prospects for mathematicians are quite promising, with a projected job growth of 33% from 2020 to 2030, according to the Bureau of Labor Statistics. This is much faster than the average for all occupations. Additionally, mathematicians are needed in a wide range of industries, including technology, finance, healthcare, and government.

3. Is artificial intelligence (AI) a growing field in mathematics?

Yes, AI is a rapidly growing field in mathematics. AI involves using mathematical algorithms and models to create intelligent machines that can learn, reason, and make decisions on their own. With the increasing use of AI in various industries, the demand for mathematicians with expertise in this area is on the rise.

4. Are there any specific skills or qualifications needed for a career in the fastest-growing math field?

To succeed in the fastest-growing math field, individuals should have a strong foundation in mathematics, statistics, and computer science. They should also have critical thinking skills, problem-solving abilities, and the ability to work with large amounts of data. Some roles may require specific programming skills, such as Python or R, and knowledge of machine learning or data visualization.

5. How can I prepare for a career in the fastest-growing math field?

To prepare for a career in the fastest-growing math field, it is important to have a solid understanding of mathematical concepts and theories. Taking courses in computer science, statistics, and data analysis can also be helpful. Additionally, gaining hands-on experience through internships or research projects can make you stand out to potential employers. Staying updated on the latest developments and advancements in the field is also crucial for success in this fast-paced industry.

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