Statistical science

For those seeking an analytical career, the Master of Science in statistical science blends advanced mathematics and applied statistics with modern quantitative and computational techniques. If you understand how data can provide insights into the best way to solve a problem, this program speaks to your interests while expanding your knowledge and equipping you for a broad range of industries and roles. In addition to our on-campus program, a fully online course of study is available.

A bachelor’s degree in statistics isn’t a requirement, but candidates should have a strong foundation in calculus and statistics.

The Department of Mathematics and Statistical Science designed this degree to fulfill the needs of today’s workforce. In addition to analyzing numbers, statistics professionals use computational tools, analytics platforms and specialized software to evaluate large datasets and uncover meaningful insights. Because they often collaborate with non-technical teams during the decision-making process, they must be able to communicate their findings clearly and persuasively.

Not everyone considering this career path starts with the same goal. You may eye a role in business, want to influence crop and animal production, or seek a position in the biological sciences, human behavior, government or health care. You can tailor the degree to meet your career goals. You’ll complete 24 credits of core courses and then complete either:

• A thesis (STAT 500)
• An internship (STAT 598) with an internship report (requirements)
• A consulting option (minimum of 8 credits of STAT 597)

Through this format, you’ll design and analyze experimental data, plan and interpret surveys, explore relationships among social, physical and biological variables; and use numerical data tools and statistical theory to solve real-world problems. In the process, you’ll:

• Learn how to compile complex data, analyze it and use your results to solve common problems and deliver sound solutions.
• Gain hand-on experience through research projects based on the potential challenges you may face in your career.
• Learn to interpret data and perform data management and statistical analyses with current tools like SAS and R.
• Understand how to apply results gleaned from probability and statistical inference theories in a broad range of scenarios.
• Refine your oral and written communication skills for delivering and discussing results with non-analytical business professionals
• Become familiar with the tools and techniques for modeling large and multifaceted data sets to identify patterns and draw insights.
• Prepare to have a voice in the decision-making process through exposure to forecasting, predictive analytics and converting raw data into actionable insights.
• Explore the research, development and analytical applications of quantitative tools.
• Advance your mathematical knowledge to prepare for a career or apply to a doctoral program.