Information Analyst making an attempt to check arithmetic and statistics to be able to make the transition
I’m a knowledge analyst with a CPA’s license and three YOE.
I’m making an attempt to check arithmetic by myself and I’ve two choices:
1) be taught a masters of monetary arithmetic, after having a bachelor’s in enterprise administration and accounting.
2) Research alone from both youtube or every other web site.
Which might you suggest and when you suggest choice 2, what’s one of the best useful resource for learning arithmetic by yourself?
If you happen to suggest choice 1 however I nonetheless wish to put together myself for the masters, what topics ought to I be taught by myself beforehand to be able to put together myself for the masters?
Comments ( 4 )
The challenge with mathematical self-study is that you need often need feedback to improve your problem solving skills. If all you’re looking to do is memorize approaches and procedures to solve pre-canned problem sets, then you can learn the material via self-study. The challenge there is that you won’t retain that knowledge unless you’re constantly using it. On the other hand, if you fully engage with the material with a good instructor who trains you have to think about the solutions, then you’ll retain the ability to learn how to learn and can pick up what syntax, etc. that you forget via various reference tools.
Now what I just laid out assumes a competent instructor, which is not necessarily a given. And if you have an incompetent instructor than you’re learning the material via self-study anyway. But conditional on having a good instructor, your knowledge and understanding will be superior than if you just learned it on your own.
Can someone pay for your degree? Then that’s the way to go.
If you have to self-pay, it’s 100% not worth it if you’re already a DA with 3 YOE. I really only think formal math/stats education is really helpful for folks with zero experience in a data-related field. If you’ve already got some data experience you’ll have an advantage when it comes time to job-seeking in DS, provided you can demonstrate you have developed sufficient mathematical competence on your own (and this is coming from someone who does have a quantitative MS – my degree was only helpful in that it helped me get interviews. My instructors were shit and I taught myself on my own).
TLDR – I recommend self-study provided that you are disciplined and have a starting level of mathematical competency. There are a ton of different thoughts out there on which resources are best, but in terms of programming I’d want a solid foundation in Probability Theory, Applied Statistics, Linear/Matrix Algebra, and basic Calculus (really only enough to be able to follow how it’s applied in optimization algorithms/problems)
You’ll also want to learn at least 1 programming language. I’d recommend Python and SQL (emphasis on SQL if you had to choose one), even though it kills me as someone who loves R lol.
MIT Open Courseware has some fantastic free materials imo
To begin with, apologies for not knowing what a CPA license requires. If any of these questions are irrelevant because of that, I apologize. What tools are you currently using for analytics? For option 1, what tools would you be exposed to in the program and what kind of portfolio would you have afterwards? For option 2, do you think you can guide yourself to a satisfactory familiarity with the available tools to produce a relatively competitive portfolio of work? Are you coming from effectively 0 stats background? In that case, I’d recommend some degree of coursework, specifically stats fundamentals and advanced topics and linear algebra including relatively in-depth understanding of matrix multiplication and a light dusting of differential calculus.