Dual Master of Science in Statistical Science and Data Science

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Dual M.S. in Statistical Science and Data Science

This STEM-focused dual degree program blends advanced analytics, statistical theory, and computational tools to equip you for leadership in today’s data-driven world

What you'll learn

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Graduates gain advanced knowledge of statistical theory and computational methods. They learn to apply rigorous statistical reasoning to complex data and use modern technologies to build data-intensive applications. They also develop skills to turn quantitative findings into actionable strategies across business, health, science, and policy, preparing them for leadership roles or Ph.D.-level study in data-driven fields.

Two degrees, one path

This dual-degree program merges statistical science with data science, equipping you with the skills to analyze complex datasets with computational skills. You'll gain expertise in computational biology, machine learning, and data analysis, preparing you to address challenges in areas like genomics and biotechnology. The curriculum blends theoretical knowledge with practical applications, fostering critical thinking and problem-solving abilities essential for real-world impact.

Program details for Dual M.S. in Statistical Science and Data Science

At a glance

Format
On-campus
Start dates
Fall

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Graduate handbooks

Admission requirements

Applicants must apply and be admitted to both the Data Science and Statistical Science programs. The combined program requires 52 credit hours, offering a more efficient path compared to the 61 credit hours needed if pursued separately.

The Luddy graduate admission committees will consider students who have a three- or four-year bachelor's degree. Applicants should have a minimum of a 3.0 (B) or higher GPA.

Curriculum

Students complete 52 credit hours across both statistical and data science coursework, including topics like probability, machine learning, and data visualization. The program includes applied projects or research and allows 9 shared credits while meeting the core requirements of each degree.

Typical degree map

Year	Fall	Spring
First	STAT S610 Introduction to Statistical Computing STAT S631 Applied Linear Models DS DMS Requirement	STAT 611 Statistical Computing STAT S632 Applied Linear Models II DS DME Requirement
Second	STAT S621 Fundamentals of Statistical Methods and Theory I STAT S690 Statistical Consulting DS DVS Requirement	STAT S622 Fundamentals of Statistical Methods and Theory II STAT S692 Internship in Statistical Consulting DS Domain I
Third	DS Domain II DS Elective DS Elective	STAT or DS Elective STAT or DS Elective

Degree map for students with weak data science background

This path is for students who may need to bolster their knowledge in data science.

Year	Fall	Spring
First	STAT S610 Introduction to Statistical Computing State S631 Applied Linear Models DSCI-D 590 Introduction to Python Programming	STAT S611 Statistical Computing STAT S632 Applied Linear Models II DSCI-D 590 Introduction to NLP for DS
Second	STAT S621 Fundamentals of Statistical Methods and Theory I STAT S690 Statistical Consulting DS DVS Requirement	STAT S622 Fundamentals of Statistical Methods and Theory II STAT S692 Internship in Statistical Consulting DS Domain I
Third	DS Domanin II DS Elective DS Elective	STAT or DS Elective STAT or DS Elective

Adding data science later

This path is for students who are already in the statistical science program and later decide to add on the M.S. in data science.

Year	Fall	Spring
First	STAT S610 Introduction to Statistical Computing STAT S631 Applied Fundamentals of Statistical Methods and Theory I	STAT S611 Statistical Computing STAT S632 Applied Linear Models II STAT S622 Fundamentals of Statistical Methods and Theory II
Seond	STAT S690 Statistical Consulting DS DMS Requirement DS Domain I	STAT S692 Internship in Statistical Consulting DS DME Requirement DS Domain II
Third	DS DVS Requirement DS Elective STAT or DS Elective	DS Elective STAT or DS Elective

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Paying for a Luddy education

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The Luddy student experience

Real Research. Real Experience.

Discover Luddy Research

At Luddy and across IU, students and faculty tackle bold research in areas like bioinformatics, computational biology, security, and privacy.

Through the Undergraduate Research Opportunities in Computing program, computer science majors can gain hands-on experience, work closely with faculty or Ph.D. mentors, and build skills that open doors in tech and research careers.

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Scholarships and Financial Aid

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Attending the Luddy School of Informatics, Computing, and Engineering is more affordable than you think. With direct-admit scholarships and federal financial aid, you can reduce the cost of earning your Dual Degree in Data Science at IU.

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Advising and Student Resources

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Whether you’re a Data Science major or still exploring your options, Luddy School advisors are here to help you navigate degree requirements, seize academic opportunities, and tailor your journey to fit your goals.