Applied Statistics MS


Applied Statistics: Online
Master of science degree
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A degree driven by real-time employer demand
Applied statistics jobs will grow 34% by 2026, four times faster than the overall labor market. Advance your career with RIT’s online MS in Applied Statistics, ranked #8 for Best Online Statistics Master’s Degree Programs.
The applied statistics job market
84k+
Average Annual Salary for Statisticians
34%
Employment Growth for Statisticians
47%
Postings for Jobs Requiring SAS
190%
Demand Growth for Artificial Intelligence
Program Highlights
The online master of science in applied statistics at RIT is ranked #8 for Best Online Statistics Master's Degree Programs by Learn.org. Offered online for more than 30 years, this degree has a proven track record in online education and preparation for statisticians in a broad range of industries and academia.
We offer start dates in the Fall, Spring, and Summer semesters. The online curriculum, faculty, and distinguished degree are identical to the on-campus degree program. You will have access to RIT’s Career Services counselors who can provide advice to help you plan, prepare for, and meet your career goals.
Designed for working professionals studying online part-time from a variety of backgrounds, you will choose electives within one or two areas of concentration tailored to your interests and career goals. You may pick a plan of study between two tracks:
- The professional track consists of core courses in the first year, and select electives in areas of study which relate to your professional goals.
- The thesis/capstone project track also consists of electives relevant to your academic and career goals, and culminates in either a thesis or capstone project.
Curriculum packed with high-demand skills

Software and Programming
Skills in Python and R are in 20% of job postings related to statistics.

Data Science
Demand for skills in artificial intelligence has grown 190% in the last 2 years, and machine learning is in the top 15 skills employers want.

Experimental Design
Crossover, adaptive, and equivalence designs are dominating 38% of this job market.

Modeling Techniques
Statistical analysis skills like linear, multivariate, and logistic regression are in over ⅓ of all postings for jobs in this field.
What you will learn
- How to manage, analyze, and draw inferences from big data—adapting to a diverse audience using business communication skills to effectively convey your insights
- How to use data mining—with tools including machine learning, software like SAS and R—to drive insightful decision-making
- How to apply statistics to the design and analysis of experiment-based industrial studies and clinical trials
Curriculum
Option 1- Professional Track
Option 2- Thesis/Project Track
Electives
Earn a credential as-you-go
Earn the advanced certificate in applied statistics and advance your career, all while working toward your master of science in applied statistics. These four courses may be fully applied toward the master’s degree.
Admission Requirements
- Complete a Graduate Application.
- Hold a baccalaureate degree (or equivalent) from an accredited university or college.
- Have satisfactory background in mathematics (a two-course sequence in calculus) and one course in applied statistics. Bridge course options available.
- Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
- Submit a current resume and personal statement.
- Submit two letters of recommendation from academic or professional sources.
- A minimum cumulative GPA of 3.0 (or equivalent) is recommended but not required.
- International applicants whose native language is not English must submit scores from the TOEFL, IELTS, or PTE.
Certain countries and individuals are subject to comprehensive embargoes under US Export Controls, which prohibit virtually ALL exports, imports and other transactions without a license or other US Government authorization. Individuals applying for online study who are subject to these embargoes will be notified during the application process.