Statistics (BS)
To see more about what you will learn in this program, visit the Learning Outcomes website!
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. Our program's emphasis on statistical computing is unique, and prepares our 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 12 credits of "Advised Electives”, and this plan 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.
For more information, see the website for our major.
Contact
Dr. Spencer Muse
Professor and Director of Undergraduate Programs
Department of Statistics
NC State University Campus Box 8203
5276 SAS Hall
Raleigh, NC 27695-8203
muse@ncsu.edu
Plan Requirements
| Code | Title | Hours | Counts towards |
|---|---|---|---|
| Orientation | |||
| COS 100 | Science of Change (verify requirement) | 0 | |
| Communication & Advanced Writing | |||
| 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 | |||
| ENG 101 | Academic Writing and Research 1 | 4 | |
| Mathematics & Sciences | |||
| MA 141 | Calculus I 1 | 4 | |
| MA 241 | Calculus II 1 | 4 | |
| MA 242 | Calculus III 1 | 4 | |
| MA 225 | Foundations of Advanced Mathematics 1 | 3 | |
| MA 305 | Introductory Linear Algebra and Matrices 1 | 3 | |
| or MA 405 | Introduction to Linear Algebra | ||
Students considering graduate school are strongly encouraged to select MA 405 | |||
| GEP Natural Sciences | 11 | ||
Selected courses mustinclude (i) at least two laboratory classes and (ii) at least three 3- or 4-credit courses. | |||
| Computer Science/Statistical Computing | |||
| ST 114 | Statistical Programming 1 | 3 | |
| ST 307 | Introduction to Statistical Programming- SAS 1 | 1 | |
| ST 308 | Introduction to Statistical Programming - R 1 | 1 | |
| ST 445 | Introduction to Statistical Computing and Data Management 1 | 3 | |
| Select one of the following Computational Statistics courses: 1 | 3 | ||
| Introduction to Data Science | |||
| Applied Bayesian Analysis | |||
| Introduction to Data Science | |||
| Intermediate SAS Programming with Applications | |||
| Applied Bayesian Analysis | |||
| Statistics | |||
| ST 311 | Introduction to Statistics 1 | 3 | |
| ST 312 | Introduction to Statistics II 1 | 3 | |
| ST 421 | Introduction to Mathematical Statistics I 1 | 3 | |
| ST 422 | Introduction to Mathematical Statistics II 1 | 3 | |
| ST 430 | Introduction to Regression Analysis 1 | 3 | |
| ST 431 | Introduction to Experimental Design 1 | 3 | |
| ST 432 | Introduction to Survey Sampling 1 | 3 | |
| ST Electives 400 Level 1 | 6 | ||
| Advised Electives | |||
| Advised Electives 1,2 | 12 | ||
A documented plan for the 12 credits of the Advised Electives will be created in conjunction with the student’s academic advisor. These courses may or may not be statistics courses. Students are encouraged to use Advised Elective credits to pursue a minor or second minor. Note that many courses used as Advised Electives might have prerequisites or other restrictions. | |||
| GEP Courses | |||
| GEP Humanities | 6 | ||
| GEP Social Sciences | 6 | ||
| GEP Health and Exercise Studies | 2 | ||
| GEP US Diversity, Equity, and Inclusion | 3 | ||
| GEP Interdisciplinary Perspectives | 5 | ||
| GEP Global Knowledge (verify requirement) | |||
| Foreign Language Proficiency (verify requirement) | |||
| Free Electives | |||
| Free Electives (12 Hr S/U Lmt) 2 | 9 | ||
| Total Hours | 120 | ||
- 1
A grade of C- or higher is required.
- 2
Students should consult their academic advisors to determine which courses fill this requirement.
- *
No more than 6 total credits from undergraduate research, independent study, credit by examination, or other similar types of courses may be used to meet program requirements (credit from AP exams or transfer credits is not included under this restriction). If you are unsure if a course falls into this category, please confer with your advisor.
ST Electives 400 Level
| Code | Title | Hours | Counts towards |
|---|---|---|---|
| ST 401 | Experiences in Data Analysis | 4 | |
| 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 421 | Introduction to Mathematical Statistics I | 3 | |
| ST 422 | Introduction to Mathematical Statistics II | 3 | |
| ST 430 | Introduction to Regression Analysis | 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 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 |
Semester Sequence
This is a sample.
| First Year | ||
|---|---|---|
| Fall Semester | Hours | |
| COS 100 or E 115 | Science of Change or Introduction to Computing Environments | 2 |
| ST 311 | Introduction to Statistics 1 | 3 |
| MA 141 | Calculus I (CP) 1 | 4 |
| Select one of the following: 1 | 3 | |
| Statistical Programming (CP) | ||
| Introduction to Computing: Python | ||
| Introduction to Computing - Java | ||
| GEP Health and Exercise Studies | 1 | |
| Hours | 13 | |
| Spring Semester | ||
| Select one of the following: | 3 | |
| Public Speaking | ||
| Interpersonal Communication | ||
| Argumentation and Advocacy | ||
| MA 241 | Calculus II (CP) 1 | 4 |
| ENG 101 | Academic Writing and Research | 4 |
| ST 312 | Introduction to Statistics II (CP) 1 | 3 |
| ST 307 | Introduction to Statistical Programming- SAS (CP) 1 | 1 |
| Hours | 15 | |
| Second Year | ||
| Fall Semester | ||
| MA 242 | Calculus III (CP) 1 | 4 |
| MA 225 | Foundations of Advanced Mathematics (CP) 1 | 3 |
| ST 445 | Introduction to Statistical Computing and Data Management 1 | 3 |
| GEP Requirement | 3 | |
| GEP Health and Exercise Studies | 1 | |
| Hours | 14 | |
| Spring Semester | ||
| ST 308 | Introduction to Statistical Programming - R 1 | 1 |
| GEP Requirement | 3 | |
| ST 431 | Introduction to Experimental Design 1 | 3 |
| MA 305 or MA 405 | Introductory Linear Algebra and Matrices (CP) 1 or Introduction to Linear Algebra | 3 |
| Advised Elective 1 | 3 | |
| Free Elective | 3 | |
| Hours | 16 | |
| Third Year | ||
| Fall Semester | ||
| ST 421 | Introduction to Mathematical Statistics I (CP) 1 | 3 |
| ST 430 | Introduction to Regression Analysis (CP) 1 | 3 |
| GEP Requirement | 3 | |
| Advised Elective 1 | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Spring Semester | ||
| ST 422 | Introduction to Mathematical Statistics II (CP) | 3 |
| GEP Requirement | 3 | |
| Computational Statistics Elective 1 | 3 | |
| GEP Natural Sciences | 4 | |
| Statistical Elective 1 | 3 | |
| Hours | 16 | |
| Fourth Year | ||
| Fall Semester | ||
| Select one of the following: | 3 | |
| Communication for Engineering and Technology | ||
| Communication for Business and Management | ||
| Communication for Science and Research | ||
| GEP Requirement | 3 | |
| Advised Elective 1 | 3 | |
| Statistics Elective 1 | 3 | |
| GEP Natural Sciences | 3 | |
| Hours | 15 | |
| Spring Semester | ||
| ST 432 | Introduction to Survey Sampling 1 | 3 |
| GEP Natural Sciences | 4 | |
| Advised Elective 1 | 3 | |
| Free Electives | 3 | |
| GEP Requirement | 3 | |
| Hours | 16 | |
| Total Hours | 120 | |
- 1
At most one D level grade is permitted in Advised Electives, Statistics Electives, or required MAT, ST, or CSC courses. C- or better is required in ST 307 Introduction to Statistical Programming- SAS, ST 311 Introduction to Statistics, ST 312 Introduction to Statistics II and ST 421 Introduction to Mathematical Statistics I.
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.