Prospective SAS learner: If you knew a high school student went from knowing nothing about SAS software to using it weeks later to prepare a conference presentation, would that encourage you to make the leap?
Let Richa Sehgal, a senior at Northview High School near Atlanta, inspire you. She sandwiched learning SAS among a full load of classes and extracurricular activities.
Granted, she's playing to her strengths. She has loved math for as long as she can remember, an aptitude for computers and a research-statistician uncle to give her pointers. (Read about her recent Analytics Experience presentation in Chris Hemedinger's post, Using machine learning to improve tumor biopsies.)
But as she notes in the interview below, she overcame trepidation and found plenty of help along the way, including in the SAS Support Communities. Enjoy her story.
What sparked your interest in math?
I've always found math really interesting. I can't think of a specific instance, but I'd always loved the simplicity of it, and the way in which everything has a solution; there's not much grey area. I've always enjoyed doing math homework problems and loved the feeling of being able to solve something complicated.
How did you develop your interest?
I began to take math classes ahead of my level and ended up taking four math classes at Georgia Tech. I was able to solidify my interest in math when I took multivariable calculus at GT, and despite the difficulty, truly loved learning about it and doing homework problems. This is one of the driving reasons why I want to major in applied math in college.
I began to get really interested in machine learning and AI when I did a science fair project in which I used MATLAB to create a program that, using image recognition, would be able to determine if a skin lesion is benign or malignant, essentially testing it for melanoma. This was really my first endeavor into math, computers, machine learning, and cancer research (or more specifically, cancer detection research).
Then, in the summer before my junior year, I interned at the Canary Center for Cancer Early Detection at Stanford University, which was where I really learned about the biology of cancer. The center is focused entirely on the early detection of cancer, so this is where I learned the importance of effective early detection. It has immense value when it comes to treatment and chance of survival. This is where I learned the most regarding computational biology and how machine learning and modeling can be used to tackle a lot of questions surrounding cancer.
Describe your experience using SAS University Edition.
I learned SAS with University Edition, running it through AWS. Getting started using SAS was pretty challenging at first, as I had almost no knowledge of SAS when I began using it. However, after I got used to it, I was able to learn a lot more quickly.
Being in high school, I didn’t really have the background in statistics (or anything) to completely understand how each program I ran functioned or what each statement did. I had to learn not only how to use SAS, but also what everything I was doing meant, what the outputs did, and what the functions did. Often, the explanations that I found online still used a lot of terminology I didn’t know, so I had to constantly look up new things to understand what I was doing, so that was the most challenging part.
What advice would you give someone just starting to learn SAS?
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