Statistics (BS): Data Science Concentration
The Bachelor of Science in Statistics curriculum provides foundational training for careers in statistics and data science, and also prepares students for graduate study in statistics or related fields such as analytics. The Data Science Concentration adds to that strong foundation with courses designed to prepare graduates for careers in the rapidly evolving Data Science sector. While our curriculum is centered on statistics, mathematics, and computer programming, it is also designed to have a flexible interdisciplinary flavor. Each statistics major works with their advisor to formulate an individualized plan for the use of "Advised Electives” that typically leads to a minor or second major in fields including business and finance, agriculture and life sciences, computer science, industrial engineering, or the social sciences.
Plan Requirements
| Code | Title | Hours |
|---|---|---|
| Orientation a | 0 | |
| COS 100 | Science of Change (verify requirement) a | 0 |
| Communication & Advanced Writing | ||
| ENG 101 | Academic Writing and Research b | 4 |
| Select one of the following Communications courses: | 3 | |
| Public Speaking | ||
| Interpersonal Communication | ||
| Argumentation and Advocacy | ||
| Select one of the following Advanced Writing courses: | 3 | |
| Communication for Engineering and Technology | ||
| Communication for Business and Management | ||
| Communication for Science and Research | ||
| Mathematics b, c | ||
| MA 141 | Calculus I | 4 |
| MA 241 | Calculus II | 4 |
| MA 242 | Calculus III | 4 |
| MA 305 | Introduction to Linear Algebra and Matrices | 3 |
| or MA 405 | Advanced Linear Algebra | |
| Data Science and Statistical Computing b, c | ||
| ST 115 | Introduction to a Data Science Toolkit with R and GitHub | 3 |
| ST 215 | Data Management and Statistical Programming in SAS | 3 |
| ST 216 | Modern Statistical Computing with Python | 3 |
| PHI 227 | Data Ethics | 3 |
| DSA 202 | Introduction to Data Visualization | 1 |
| DSA 405 | Data Wrangling and Web Scraping | 1 |
| Introduction to Data Science: Select one of the following | 3 | |
| Mathematical Foundations of Data Science I | ||
| Introduction to Data Science | ||
| Introduction to Data Science | ||
| Statistical Data Science Electives. Select two of the following courses: | 6 | |
| Intermediate SAS Programming with Applications | ||
| Statistical Learning and Data Analytics | ||
| Advanced Computing for Statistical Reasoning | ||
| General Data Science Electives. Select 2 credits of DSA courses at any level from the approved list. | 2 | |
| Advanced Data Science Electives. Select 2 credits of DSA courses at the 400 level. | 2 | |
| Statistics b, c | ||
| ST 120 | Fundamentals of Statistical Inference | 4 |
| ST 121 | Introduction to Probability and Mathematical Statistics | 3 |
| ST 220 | Intermediate Statistical Methods | 3 |
| ST 240 | Principles of Data Collection | 3 |
| ST 323 | Linear Models | 4 |
| ST 421 | Introduction to Mathematical Statistics I | 3 |
| ST 422 | Introduction to Mathematical Statistics II | 3 |
| Select one of the following 3-credit courses in Survey Sampling or Experimental Design. | 3 | |
| Introduction to Experimental Design | ||
| Introduction to Survey Sampling | ||
| Advanced Statistics Electives b, c, e | 3 | |
| GEP Natural Sciences | 11 | |
Selected courses must include (i) at least two laboratory classes and (ii) at least three 3- or 4-credit courses. | ||
| GEP Courses | ||
| GEP Humanities | 3 | |
| GEP Social Sciences | 6 | |
| GEP Health and Exercise Studies | 2 | |
| GEP Elective | 3 | |
| GEP Interdisciplinary Perspectives | 5 | |
| GEP Global Knowledge (verify requirement) | ||
| GEP Foundations of American Democracy (verify requirement) | ||
| World Language Proficiency (verify requirement) | ||
| Free Electives d | ||
| Free Electives (12 Hr S/U Lmt) | 9 | |
| Total Hours | 120 | |
- a
The orientation requirement is typically satisfied by a first-year course taught in the student's original NCSU major. For students entering as Freshmen Statistics majors that course is COS 100, and those 2 credits will appear in the GEP Interdisciplinary Perspectives slot of their degree audit. Students transferring from another college or university will have this requirement waived.
- b
A grade of C- or higher is required.
- c
A grade of D- or better can be used in one course to meet degree requirements of the Mathematics, Data Science & Statistical Computing, or Statistics sections of the degree audit. However, grades of C- or better are required for ST 115, ST 120, ST 121, MA 141, MA 241, and MA 305
- d
Students should consult their academic advisors to determine which courses fill this requirement.
- e
No more than 6 total credits from ST 497, ST 498, ST 499 may be used as Advanced Statistics Electives. If a student takes ST 497, ST 498, or ST 499 for less than 3 credits, that course may not be used for Advanced Statistics Elective credit. (e.g., a student may not take ST 499 for 1 credit three times and apply those 3 credits to Advanced Statistics Electives.) In addition, please note that ST 497 can only be taken one time.
Advanced Statistics Electives
| Code | Title | Hours |
|---|---|---|
| ST 404 | Epidemiology and Statistics in Global Public Health | 3 |
| ST 405 | Applied Nonparametric Statistics | 3 |
| ST 412 | Long-Term Actuarial Models | 3 |
| ST 413 | Short-Term Actuarial Models | 3 |
| ST 420 | 3 | |
| ST 431 | Introduction to Experimental Design | 3 |
| ST 432 | Introduction to Survey Sampling | 3 |
| ST 433 | Applied Spatial Statistics | 3 |
| ST 434 | Applied Time Series | 3 |
| ST 435 | Statistical Methods for Quality and Productivity Improvement | 3 |
| ST 437 | Applied Multivariate and Longitudinal Data Analysis | 3 |
| ST 440 | Applied Bayesian Analysis | 3 |
| ST 442 | Introduction to Data Science | 3 |
| ST 445 | Introduction to Statistical Computing and Data Management | 3 |
| ST 446 | Intermediate SAS Programming with Applications | 3 |
| ST 451 | Sports Analytics | 3 |
| ST 452 | Statistical Learning and Data Analytics | 3 |
| ST 453 | Advanced Computing for Statistical Reasoning | 3 |
| ST 491 | Statistics in Practice | 3 |
| ST 495 | Special Topics in Statistics | 1-6 |
| ST 497 | Professional Experience in Statistics | 1-3 |
| ST 498 | Independent Study In Statistics | 1-6 |
| ST 499 | Research Experience in Statistics | 1-3 |
General Data Science Electives
| Code | Title | Hours |
|---|---|---|
| DSA 205 | Data Communication | 1 |
| DSA 220 | Introduction to AI Ethics | 1 |
| DSA 225 | Data Science for Social Good | 1 |
| DSA 235 | Introduction to Data Science for Cybersecurity | 1 |
| DSA 240 | Measuring Success | 1 |
| DSA 295 | Introductory Special Topics in Data Science | 1-3 |
| DSA 406 | Exploratory Data Analysis for Big Data | 1 |
| DSA 410 | Data Internship Preparation for Social Impact | 1 |
| DSA 412 | Exploring Machine Learning | 1 |
| DSA 495 | Special Topics in Data Science | 1-3 |
| DSA 595 | Graduate Special Topics in Data Science | 1-3 |
Advanced Data Science Electives
| Code | Title | Hours |
|---|---|---|
| DSA 406 | Exploratory Data Analysis for Big Data | 1 |
| DSA 410 | Data Internship Preparation for Social Impact | 1 |
| DSA 412 | Exploring Machine Learning | 1 |
| DSA 435 | Predictive Analytics for Improving Services | 1 |
| DSA 440 | Introduction to APACHE Spark Using Big Datasets | 1 |
| DSA 495 | Special Topics in Data Science | 1-3 |
| DSA 595 | Graduate Special Topics in Data Science | 1-3 |
| First Year | ||
|---|---|---|
| Fall Semester | Hours | |
| COS 100 or E 115 | Science of Change a or Introduction to Computing Environments | 2 |
| MA 141 | Calculus I (CP) b, c | 4 |
| ST 115 | Introduction to a Data Science Toolkit with R and GitHub b, c | 3 |
| ST 120 | Fundamentals of Statistical Inference b, c | 4 |
| GEP Health and Exercise Studies | 1 | |
| Hours | 14 | |
| Spring Semester | ||
| ENG 101 | Academic Writing and Research b | 4 |
| MA 241 | Calculus II (CP) b, c | 4 |
| ST 121 | Introduction to Probability and Mathematical Statistics b, c | 3 |
| PHI 227 | Data Ethics | 3 |
| GEP Health and Exercise Studies | 1 | |
| Hours | 15 | |
| Second Year | ||
| Fall Semester | ||
| MA 242 | Calculus III (CP) b, c | 4 |
| MA 305 | Introduction to Linear Algebra and Matrices b, c | 3 |
| ST 215 | Data Management and Statistical Programming in SAS b, c | 3 |
| DSA 202 | Introduction to Data Visualization b, c | 1 |
| DSA 405 | Data Wrangling and Web Scraping b, c | 1 |
| General Data Science Elective b, c | 1 | |
| GEP Requirement | 3 | |
| Hours | 16 | |
| Spring Semester | ||
| ST 220 | Intermediate Statistical Methods b, c | 3 |
| ST 240 | Principles of Data Collection b, c | 3 |
| ST 216 | Modern Statistical Computing with Python b, c | 3 |
| GEP Natural Sciences | 4 | |
| Communications Elective: COM 110, 112, or 211 | 3 | |
| Hours | 16 | |
| Third Year | ||
| Fall Semester | ||
| ST 323 | Linear Models b, c | 4 |
| ST 421 | Introduction to Mathematical Statistics I (CP) b, c | 3 |
| Introduction to Data Science: ST 442, CSC 442, or MA 326 b, c | 3 | |
| GEP Requirement | 3 | |
| Hours | 13 | |
| Spring Semester | ||
| ST 422 | Introduction to Mathematical Statistics II (CP) b, c | 3 |
| GEP Requirement | 3 | |
| GEP Natural Sciences | 3 | |
| Statistical Data Science Elective b, c | 3 | |
| General Data Science Elective b, c | 1 | |
| Advanced Data Science Electives b, c | 2 | |
| Hours | 15 | |
| Fourth Year | ||
| Fall Semester | ||
| Statistical Data Science Elective b, c | 3 | |
| Technical Writing Elective: ENG 331, 332, or 333 | 3 | |
| Free Elective d | 3 | |
| GEP Requirement | 3 | |
| GEP Natural Sciences | 4 | |
| Hours | 16 | |
| Spring Semester | ||
| Survey Sampling/Experimental Design Elective: ST 431 or ST 432 b, c | 3 | |
| Advanced Statistics Elective b, c, e | 3 | |
| GEP Requirement | 3 | |
| Free Elective d | 3 | |
| Free Elective d | 3 | |
| Hours | 15 | |
| Total Hours | 120 | |
- a
The orientation requirement is typically satisfied by a first-year course taught in the student's original NCSU major. For students entering as Freshmen Statistics majors that course is COS 100, and those 2 credits will appear in the GEP Interdisciplinary Perspectives slot of their degree audit. Students transferring from another college or university will have this requirement waived.
- b
A grade of C- or higher is required.
- c
A grade of D- or better can be used in one course to meet degree requirements of the Mathematics, Computer Programming & Statistical Computing, or Statistics sections of the degree audit. However, grades of C- or better are required for ST 115, ST 120, ST 121, MA 141, MA 241, and MA 305.
- d
Students should consult their academic advisors to determine which courses fill this requirement.
- e
No more than 6 total credits from ST 497, ST 498, ST 499 may be used as Advanced Statistics Electives. If a student takes ST 497, ST 498, or ST 499 for less than 3 credits, that course may not be used for Advanced Statistics Elective credit. (e.g., a student may not take ST 499 for 1 credit three times and apply those 3 credits to Advanced Statistics Electives.) In addition, please note that ST 497 can only be taken one time.
Career Opportunities
The importance of sound statistical thinking in the design and analysis of quantitative studies is reflected in the abundance of job opportunities for statisticians. Because one can improve the efficiency and use of increasingly complex and expensive experimental and survey data, statisticians are in demand wherever quantitative studies are conducted. Statisticians are highly valued members of teams working in such diverse fields as biomedical science, global public health, weather prediction, environmental monitoring, political polling, crop and livestock management, and financial forecasting. Statistics is at the core of Data Science and Analytics, and our department provides an outstanding environment to prepare for careers in these areas. In addition to finding exciting careers in industry and government, our graduates are also very successful moving on to graduate programs in statistics and related fields at top universities around the globe.
Career Titles
- Actuary
- Aeronautical & Aerospace Engineer
- Aerospace Engineering Technician
- Air Traffic Controller
- Astronomer
- Atmospheric and Space Scientist
- Bank and Branch Managers
- Biopsychologist
- Budget Analyst
- Buyer
- Compensation Administrator
- Computer and Information Scientists
- Computer Programmer
- Database Administrator
- Financial Aid Counselor
- Financial Analyst
- Government Budget Analyst
- High School Teacher
- Market Research Analysts and Marketing Specialists
- Math Professor
- Mathematical Technician
- Mathematician
- Meteorologist
- Middle School Teacher
- Operations Research Analyst
- Physicist
- Psychometrist
- Purchasing Manager
- Securities and Commodities Sales Agent
- Social Science Research Assistants
- Statistical Assistants
- Statistician
- Technical Publications Writer
Learn More About Careers
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