Here’s what you’ll need to apply for the Baylor MSBA online program:

• Completed application, available online now.
• Undergraduate transcript. A bachelor’s degree from an accredited institution in the U.S. or proof of equivalent training at a foreign university is required.
• Current resume indicating professional work experience, including start and end dates (month and year) for each position held.
• Two letters of recommendation from employers or superiors who can attest to your talents, professional skills, work accomplishments and qualifications for the Baylor MSBA online program.

There is no application fee for the MSBA online program.

Prerequisites

Prerequisites for admission include:

• Introduction to Python Programming (an informal online course can meet this requirement, and several options are available)
• Minimum 3 hours of statistics or successful completion of designated statistics modules prior to course registration.

International Students

All foreign national applicants are required to provide a score from the TOEFL, IELTS or PTE Academic test. Minimum scores are required.

The Baylor Online MSBA has an extensive and comprehensive curriculum for a good reason. We want to provide in-depth knowledge and practical experience by working with data from Fortune 500 companies.

This way, you’re not just learning theories; you’re applying skills in real-world contexts, significantly enhancing your mastery and professional value.

See below for courses currently offered on-campus and online.

Show/Hide course descriptions

• STA 5300 Statistical Methods
  Introduction to descriptive and inferential statistics. Topics may be selected from the following: descriptive statistics and graphs, probability, regression, correlation, tests of hypotheses, interval estimation, measurement, reliability, experimental design, analysis of variance, nonparametric methods, and multivariate methods.
• STA 5303 Regression
  Pre-requisite(s): STA 5300. Regression modeling, estimation, and diagnostics with emphasis on applications. Topics include simple linear regression, multiple regression, logistic regression, and Poisson regression. The statistical programming language R is used.
• STA 5362 Time Series Analysis
  Statistical methods for analyzing time series. Topics include autocorrelation function and spectrum, stationary and non-stationary time series, linear filtering, trend elimination, forecasting, general models, and autoregressive integrated moving average models with applications in economics and engineering.
• STA 5373 Computational Methods
  Pre-requisite(s): STA 5300. Introduction to programming in R and data science methods and techniques using R. Focus will be on current R packages and will emphasize data management and visualization along with report writing. Relevant business cases will be considered.
• STA 5384 Multivariate Statistical Methods
  Pre-requisite(s): STA 5300: This course will focus on summarizing multivariate data both graphically and numerically. Topics include principal components analysis, discriminant analysis, cluster analysis, and other machine learning topics as time allows.
• MIS 5322 Advanced Python for Analytics
  Study of advanced topics in the Python programming language. Focus is on data analytics and data science. Main topics include data visualization, array processing, data mining, machine learning, natural language processing, and web application development. Projects cover game development using PyGame and web app development using Django.
• MIS 5342 Business Intelligence
  Business Intelligence (BI) is the discovery of patterns and relationships hidden in large volumes of data. This hands-on course is designed to provide practical analytic skills that may be applied in almost any workplace. The course explores the analytical techniques for making intelligent business decisions in data-rich organizations. A key component of the course is the use of BI software tools with techniques such as correlation analysis, data visualization, linear regression, classification, and clustering to address common problems in marketing, customer relationship management, risk management, finance, and operations.
• MIS 5343 Seminar in Data Visualization
  Covers basic theories of cognition and data visualization, including how data types influence the decision to use a particular representation, when to use various chart types, how to structure data visualizations, and visualization evaluation. Emphasis on ethical use of visualizations.
• MIS 5390 Ethics in Business Analytics
  Ethical decision-making in data analytics and contemporary issues. Topics include ethics theory, American Statistical Association Ethical Guidelines for Statistical Practice, ethics issues in statistical analyses and presentation of data, ethical consideration in the information age, and data ethics in contemporary issues.

Upcoming courses not yet in the Graduate Course Catalog:

• STA 5V85 Practicum
  Capstone in analytics. Students will be combined into teams and will work together on
  solving a real life problem using techniques and tools from other courses in the program.
• MIS 53XX Cloud Computing
• MIS 53XX Database Technologies for Analytics

An MS in Business Analytics leads to various in-demand opportunities. Roles range from Application Architects to Chief Data Officers in sectors such as pharmaceuticals, consumer marketing, healthcare, environmental science, and architecture.

Thanks to the massive demand for their skills in building, managing, and analyzing data infrastructures, Data Architects and Data Engineers earn an average salary above $100,000.

On the higher end, executive roles like Chief Data Officers and Chief Technology Officers see average salaries ranging from around $150,000 to over $200,000. *

Additionally, professionals in roles not specifically tied to data can significantly benefit from business analytics skills for career advancement—for example, Financial Analysts, Chief Marketing Officers, or Mechanical Engineers.

Consider the possibilities as you think about your career goals and where you want to be.

* Salaries may vary based on the role, location, and years of experience.