Program Overview

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Statistics and Analytics Major, B.S.

The major in statistics and analytics is an excellent program for students interested in statistical data science, operations research, and actuarial science, as well as in fields such as business, economics, public policy and health, psychology, and biomedicine, where the decision and statistical sciences play an increasingly important role.

Student Learning Outcomes

Upon completion of the statistics and analytics program, students should be able to:

• Demonstrate foundational knowledge of probability, statistics, optimization, and stochastic modeling
• Exhibit proficiency in one or more of the scientific programming languages commonly used in statistics and analytics
• Apply the analytical and computational skills needed to formulate and solve data science problems
• Interpret and translate numerical results into actionable ideas and communicate them orally and in writing
• Find employment in professions relying on data and analytics, or continue education in related graduate programs

Requirements

In addition to the program requirements, students must:

• earn a minimum final cumulative GPA of 2.000
• complete a minimum of 45 academic credit hours earned from UNC–Chapel Hill courses
• take at least half of their major core requirements (courses and credit hours) at UNC–Chapel Hill
• earn a minimum cumulative GPA of 2.000 in the major core requirements. Some programs may require higher standards for major or specific courses.

Course List

The following courses are required for the Statistics and Analytics Major, B.S.:

• Core Requirements:
  • MATH/STOR 235: Mathematics for Data Science (4 hours)
  • or MATH 233: Calculus of Functions of Several Variables
  • STOR 315: Discrete Mathematics for Data Science (3-4 hours)
  • or MATH 381: Discrete Mathematics
  • or COMP 283: Discrete Structures
  • STOR 320: Methods and Models of Data Science (4 hours)
  • or STOR 520: Statistical Computing for Data Science
  • STOR 415: Introduction to Optimization 1, H (3 hours)
  • STOR 435: Introduction to Probability H (3 hours)
  • or STOR 535: Probability for Data Science
  • STOR 445: Stochastic Modeling (3 hours)
  • STOR 455: Methods of Data Analysis H (3 hours)
  • One STOR course at the 500 level (3 hours)
• Additional Requirements:
  • COMP 116: Introduction to Scientific Programming (COMP 110 may be substituted) (3 hours)
  • MATH 231: Calculus of Functions of One Variable I H, F (4 hours)
  • MATH 232: Calculus of Functions of One Variable II H, F (4 hours)
  • MATH 347: Linear Algebra for Applications F (3 hours)
  • STOR 155: Introduction to Data Models and Inference H, F (3-4 hours)
  • or STOR 120: Foundations of Statistics and Data Science
  • Three additional courses from either Group A or Group B (see lists below) (9 hours)
• Total Hours: 52-53

Group A

The following courses are part of Group A:

• STOR 305: Introduction to Decision Analytics 1 (3 hours)
• STOR 323: Ethics of Machine Learning in Society (3 hours)
• STOR 471: Long-Term Actuarial Models (3 hours)
• STOR 472: Short Term Actuarial Models (3 hours)
• STOR 475: Healthcare Risk Analytics (3 hours)
• STOR 512: Optimization for Machine Learning and Neural Networks (3 hours)
• STOR 536: Advanced Methods in Probability (3 hours)
• STOR 538: Sports Analytics (3 hours)
• STOR 543: Dynamic Decision Analytics (3 hours)
• STOR 545: Stochastic Models and their Applications (3 hours)
• STOR 555: Mathematical Statistics (3 hours)
• STOR 556: Time Series Data Analysis (3 hours)
• STOR 557: Advanced Methods of Data Analysis (3 hours)
• STOR 565: Machine Learning (3 hours)
• STOR 566: Introduction to Deep Learning (3 hours)
• STOR 572: Simulation for Analytics (3 hours)

Group B

The following courses are part of Group B:

• BIOS 664: Sample Survey Methodology (4 hours)
• BUSI 403: Operations Management (3 hours)
• BUSI 408: Corporate Finance (3 hours)
• BUSI 410: Business Analytics (3 hours)
• BUSI 532: Service and Platforms Operations Management H (3 hours)
• BUSI 533: Supply Chain Management H (3 hours)
• COMP 401: Foundation of Programming (Student can take COMP 301 or COMP 401) H (3-4 hours)
• or COMP 301: Foundations of Programming
• COMP 410: Data Structures (Student can take COMP 210 or COMP 410) (3 hours)
• or COMP 210: Data Structures and Analysis
• COMP 421: Files and Databases (3 hours)
• ECON 410: Intermediate Microeconomics H (4 hours)
• ECON 420: Intermediate Macroeconomics H (3 hours)
• ECON 511: Advanced Game Theory in Economics H (3 hours)
• INLS 523: Introduction to Database Concepts and Applications (3 hours)
• MATH 383: First Course in Differential Equations H (3 hours)
• MATH 521: Advanced Calculus I H (3 hours)
• MATH 522: Advanced Calculus II H (3 hours)
• MATH 523: Functions of a Complex Variable with Applications (3 hours)
• MATH 524: Elementary Differential Equations (3 hours)
• MATH 548: Combinatorial Mathematics (3 hours)
• MATH 566: Introduction to Numerical Analysis (3 hours)

Sample Plan of Study

Sample plans can be used as a guide to identify the courses required to complete the major and other requirements needed for degree completion within the expected eight semesters. The actual degree plan may differ depending on the course of study selected (second major, minor, etc.). Students should meet with their academic advisor to create a degree plan that is specific and unique to their interests.

First Year

• IDST 101: College Thriving (1 hour)
• ENGL 105: English Composition and Rhetoric (3 hours)
• First-Year Seminar or First-Year Launch F (3 hours)
• IDST 111L: Data Literacy Lab (1 hour)
• Global Language through level 3 (varies)
• COMP 116: Introduction to Scientific Programming (COMP 110 may be substituted) (3 hours)
• MATH 231: Calculus of Functions of One Variable I H, F (4 hours)
• MATH 232: Calculus of Functions of One Variable II H, F (4 hours)

Second Year

• MATH/STOR 235: Mathematics for Data Science (Second Year) (4 hours)
• or MATH 233: Calculus of Functions of Several Variables
• STOR 155: Introduction to Data Models and Inference 1, H, F (3-4 hours)
• or STOR 120: Foundations of Statistics and Data Science
• STOR 315: Discrete Mathematics for Data Science (3-4 hours)
• or MATH 381: Discrete Mathematics
• or COMP 283: Discrete Structures
• STOR 320: Methods and Models of Data Science (4 hours)

Third Year

• MATH 347: Linear Algebra for Applications F (3 hours)
• STOR 415: Introduction to Optimization H (3 hours)
• STOR 435: Introduction to Probability H (3 hours)
• or STOR 535: Probability for Data Science
• STOR 455: Methods of Data Analysis H (3 hours)

Fourth Year

• STOR 445: Stochastic Modeling (3 hours)
• One STOR 500-level course (3 hours)
• Three additional courses from Group A or Group B (9 hours)
• Total Hours: 60-62

Dual Bachelor’s – Master’s Degree Program

The Department of Statistics and Operations Research offers a dual bachelor’s – master’s degree program. Interested students should consult the graduate program director.

Special Opportunities in Statistics and Analytics

Honors in Statistics and Analytics

Candidates for honors or highest honors must secure approval from the program director. They must take STOR 691H and STOR 692H, and maintain an overall grade point average of 3.3 and a grade point average in statistics and analytics courses of at least 3.3 at the end of the semester preceding the semester in which they graduate.

Departmental Involvement

The Department of Statistics and Operations Research sponsors Carolina’s Actuarial Student Organization (CASO), for students interested in careers in the actuarial sciences. CASO organizes study groups for the actuarial exams, sponsors talks by professional actuaries, keeps members aware of employment opportunities, and maintains contact with alumni and corporations in the field. The department is also a co-sponsor of Carolina Analytics and Data Science (CADS) student organization, which aims to foster communication among the students who are interested in careers in data science and analytics and contribute to their intellectual growth by hosting speakers from industry as well as academia.

Experiential Education

When arranged in advance with a supervising faculty member, STOR 493 can be used to earn credit for appropriate work experience in the summer or during the academic year. STOR 493 satisfies the experiential education and high-impact experience Gen Ed requirement. Students interested in STOR 493 should secure approval from the program director before starting their work. STOR 496 can also be used to satisfy the experiential education requirement.

Undergraduate Awards

Two undergraduate awards for graduating seniors are given each year by the statistics and analytics program. One is the Statistics and Analytics Award, given to the outstanding graduating senior, and the second is the W. Robert Mann Award, given for excellence in actuarial science. Plaques bearing the names of winners are located in the undergraduate study room in Hanes Hall.

Undergraduate Research

Undergraduate research under the direction of faculty members from the Department of Statistics and Operations Research is offered through the independent study and research course, STOR 496, and the senior honors thesis courses, STOR 691H and STOR 692H.

Department Programs

Major

• Data Science Major, B.A.
• Statistics and Analytics Major, B.S.

Minor

• Data Science Minor
• Statistics and Analytics Minor

Graduate Programs

• M.S. in Statistics, Analytics, and Data Science (STANDS)
• Ph.D. in Statistics and Operations Research

Courses

• Statistics and Operations Research (STOR)

Department of Statistics and Operations Research

• Chair: Jan Hannig
• Director of Undergraduate Studies: Nicolas Fraiman
• Director of Graduate Studies: Richard Smith
• Director of M.S. Program: Mariana Olvera-Cravioto
• Administrative Support Associate: __

Undergraduate

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    • Statistics and Analytics Major, B.S.
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Courses

• AEROSPACE STUDIES (AERO)
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