Applied Statistics & Data Science Major


Applied statistics uses a variety of computational techniques and methods, in order to visualize and explore data, seek and establish the structure and trends in data, investigate relationships between observed phenomena and facilitate data interpretation. Data science expands on statistics to encompass the entire life cycle of data, from its specification, gathering, and cleaning through its management and analysis, to its use in making decisions and setting policy. The Data Science and Applied Statistics program at USMA provides Cadets the opportunity to effectively explore structured and unstructured data, defining answerable questions, performing statistical analysis and communicating results both written and orally.  The program introduces the underlying mathematics of Data Science and Applied Statistics while simultaneously offering an exposure to computation and optimization issues inherent in large and disparate data sets.

Student Outcomes

The student outcomes of the Applied Statistics & Data Science major include:

  1. Demonstrate competence in computational and statistical thinking
    • Understand the basic statistical concepts of data analysis, data collection, modeling and inference
    • Formulate problems, plan data collection campaigns and analyze the data to provide insights
    • Demonstrate proficiency in foundational software skills and the associated algorithmic, computational problem-solving strategies
  2. Demonstrate competence in mathematical foundations
    • Understand the underlying structure of common models used in statistical and machine learning as well as the issues of optimization and convergence of algorithms
  3. SLO 1: Apply statistical model building and assessment techniques
    • Be adapt at data visualization using visualization techniques to communicate with others and identify weaknesses in proposed models
    • Employ statistical inference and draw conclusions using formal modeling.  Understand how data issues impact analysis and interpretation of statistical finding
  4. Employ algorithmic problem-solving skills
    • Define clear requirements to a problem, use efficient strategies to arrive at an algorithmic solution using a suitable high-level computer language
    • Leverage existing packages and tools to solve computational problems
  5. Prepare and manage data through the entire problem-solving process
    • Work with a variety of sources and formats of data
    • Prepare the data for use with a variety of statistical methods and models
    • Ensure the integrity of the data throughout the entire analytical process
  6. Transfer knowledge
    • Communicate results both written and orally
    • Demonstrate understanding of ethical issues in reproducibility

Program of Study

The Applied Statistics and Data Science Major offers abundant opportunities for study in a broad range of mathematical subjects. Courses such as linear algebra, applied statistics, mathematical statistics, theory and applications of data science, generalized linear models, and mathematical computation provide a sound mathematical foundation in the data science and statistics fields. In addition, follow-on courses such as cyber foundations, database systems, computer aided systems engineering, and advanced individual study provide both depth in understanding the applications of data science theory, as well as opportunity for study and research in a selected subject. Whenever possible, the use of technology is emphasized to extend the knowledge required for the consideration of realistic and challenging problems of today's world.

To complete the Applied Statistics and Data Science major, a cadet is must complete at total of 41 courses, comprised of the following:

  • 22 core courses
  • 3 courses from any one of the seven 3-course engineering sequences.
  • 16 additional courses (10 required and 6 elective)

Honors Program

The Applied Statistics and Data Science major offers an honors program.  To receive a Applied Statistics and Data Science Major with Honors a cadet is must:

  • In place of MA491, complete the two-course sequence MA498 Senior Thesis I and MA499 Senior Thesis II or the two-course sequence of XE401 Integrative System Design I and XE402 Integrative System Design II.
  • Graduate with an APSC > 3.0 in core academic program courses
  • Graduate with an APSC > 3.5 in Applied Statistics and Data Science major courses

Required Courses (6 of 6)

Course No. Course Title
MA371 Linear Algebra
MA376 Applied Statistics
MA476 Mathematical Statistics
MA477 Theory & Application of Data Science
MA478 Generalized Linear Models
MA486 Mathematical Computation
 
Discipline Electives (2 of 16)
Course No. Course Title
CS473 Computer Graphics
CS486 Artificial Intelligence
IT383 User Interface Development
MA372 Introduction to Discrete Math
MA383 Foundations of Math
MA386 Into to Numerical Analysis
MA387 Mathematical Analysis
MA388 Sabermetrics
MA391 Mathematical Modeling
MA394 Fundamentals of Network Science
MA461 Graph Theory and Networks
MA462 Combinatorics
MA488 Special Topics in Mathematics
MA489 Adv Individual Study in Math
XE402 Integrative System Design II
XE492 Disruptive Innovations
 
Research Course (1 of 2)
Course No. Course Title
MA491 Research Seminar Applied Mathematics
XE401 Integrative System Design I
 
IT Course (1 of 2)
Course No. Course Title
CY305 Cyber Foundations
CY355 Cyber Foundations - Computing
 
Complementary Support Course-Computer Science (1 of 2)
Course No. Course Title
IT393 Database Systems
SE370 Computer Aided Systems Engineering
 
Integrative Experience (1 of 1)
Course No. Course Title
MA490 Applied Problem from Math, Science, & Engineering