Before matriculating, applicants must have completed a bachelor’s degree from an accredited college or university and have a proven track record of strong academic performance. We accept applicants from a wide variety of academic majors. However, to be a competitive applicant, you will need to have successfully completed prerequisite courses prior to or concurrent with your application for admission to the MSA program.
Prerequisite Courses
Prerequisite courses for applicants include at least one, but ideally two semesters of college-level statistical methods, including substantive coursework covering regression analysis. To gauge whether courses you’ve taken previously (or are considering taking in the future) would serve as sufficient preparation, please compare their content against the topics/methods listed below.
It is advantageous for MSA applicants to be familiar with the following topics/methods:
- Analysis of Variance (ANOVA)
- Confidence Intervals
- Correlation
- Data Collection / Sampling
- Eigenvalues / Eigenvectors
- Gauss-Jordan Elimination
- Hypothesis Testing
- Least Squares Estimation / Normal Equation
- Matrix Manipulation
- Multicollinearity
- Multiple Linear Regression
- Normal & Binomial Distributions
- Probability
- Residual Diagnostics
- Sampling Distributions / Central Limit Theorem
- Simple Linear Regression
- Solving Systems of Linear Equations
- Variable Reduction through Eigenvalues
- Variable Selection
If you are an undergraduate student currently enrolled at NC State, courses you might consider completing are:
- ST 311 and ST 312 – Introduction to Statistics I and II
- ST 371 and ST 372 – Introduction to Probability and Distribution Theory, and Introduction to Statistical Inference and Regression
- If you have the prerequisites for it, then ST 430 – Introduction to Regression Analysis
If you already hold an undergraduate degree but do not feel that your past coursework provided sufficient preparation (or if you wish to have a refresher), you have a few options:
- We offer a self-paced online, non-credit course called Introduction to Analytics 2, through NC State’s Wolfware Outreach platform. This course is appropriate for those who have previously completed introductory statistics coursework and are looking to advance their knowledge.
- NC State’s Non-Degree Studies (NDS) program offers viable online options (e.g., ST 513-514).
- We recognize comparable courses completed for credit and a grade from other accredited institutions as well.
Coding Experience
An additional requirement of MSA admission is the ability to write code from scratch — what we consider to be an intermediate level of proficiency — in one or more languages, especially those most relevant to data science (e.g., Python, R, SQL). One can acquire coding skills through formal coursework, work experience, and/or independent study.
There are numerous online resources for enhancing coding skill, many of them free or at low cost; for example, you might consider the Python Institute’s PCEP™ – Certified Entry-Level Python Programmer certification.
The most effective way to learn to code is through hands-on practice. Consider completing a personal coding project using a real dataset, such as those available via Kaggle and Google. When you encounter difficulties or errors (and you will!), use resources such as Google and YouTube to find possible solutions.
Should you have questions about prerequisite courses or coding experience, contact MSA Admissions.