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. It is not uncommon for applicants to already hold advanced degrees (MS, MBA, PhD, etc.)
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 for applicants include at least one, but ideally two semesters of college-level statistical methods, including substantive coursework covering regression analysis. We recognize prerequisite courses completed for credit and a grade from accredited institutions.
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 might consider completing ST 513 and ST 514 through NC State’s Non-Degree Studies (NDS) program, or comparable courses through a university local to you.
If you are an undergraduate student currently enrolled at NC State, we strongly recommend that you complete one of the following course pairs:
- ST 305 – Statistical Methods and ST 430 – Regression Analysis
- ST 371 – Probability and Distribution Theory and ST 372 – Statistical Inference and Regression
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.
Statistical topics/methods your prerequisite course(s) should cover:
- Analysis of Variance (ANOVA)
- Confidence Intervals
- Data Collection / Sampling
- Eigenvalues / Eigenvectors
- Gauss-Jordan Elimination
- Hypothesis Testing
- Least Squares Estimation / Normal Equation
- Matrix Manipulation
- Multiple Linear Regression
- Normal & Binomial Distributions
- Residual Diagnostics
- Sampling Distributions / Central Limit Theorem
- Simple Linear Regression
- Solving Systems of Linear Equations
- Variable Reduction through Eigenvalues
- Variable Selection
An additional requirement of MSA admission is the ability to code in one or more languages, particularly as it relates to data science and analytics. Your ability could have been gained in formal coursework or through substantive experience coding. There are numerous online resources for enhancing coding skill, many of them free or at low cost.
Please send questions about prerequisites to MSA Admissions.