Learning Objectives

The purpose of B.S/B.A. major in statistics is to provide students with the statistics, mathematics, and computing science tools necessary for them to be successful as statisticians, data scientists, biostatisticians, and quantitative analysts in business, industry, government, and the many aspects of the health professions, and to prepare students for graduate study in statistics.  Graduates from the program will demonstrate competence in the statistical, mathematical, computational, and nonmathematical skills in the American Statistical Association Curriculum Guidelines for Undergraduate Programs in Statistical Science.


  1. Statistics majors will demonstrate mastery of foundational mathematics in calculus, linear algebra, and foundations of analysis.
  2. Statistics majors will demonstrate proficiency in basic computer programming.
  3. Statistics majors will demonstrate proficiency in two statistical programming languages, and be able use these languages for data exploration, visualization, cleaning, and analysis.
  4. Statistics majors will demonstrate proficiency in the application of multiple statistical methods in the analysis of data.
  5. Statistics majors will demonstrate proficiency in the theoretical underpinnings of probability and statistical inference.
  6. Statistics majors will demonstrate proficiency in the communication of the processes, methods and results of statistical analyses.


Student Evaluations of Courses and Instructors

The standardized USU course evaluation form is conducted in all courses taught by Mathematics and Statistics faculty to allow students to evaluate both the course and the instructor.

College of Science Interviews and Questionnaire

Each year, the Dean of the College of Science interviews a number of majors from each department in the college. In addition, every student applying for graduation in the College of Science is given a questionnaire to complete. These collectively provide information on general student satisfaction with the degree program, courses, faculty and facilities. This information is collected anonymously and then returned to the department in the summer following graduation.

Self-Study and External Review

The Department of Mathematics and Statistics periodically conducts a Regents-mandated self-study and external review. The self-study allows the faculty to reassess the program and its direction as well as its goals and objectives. The recommendations made by the external review team are used to modify and improve the program.

Capstone Experience and Math GRE

Beginning in 2017-18, the Department of Mathematics and Statistics will formally organize a capstone experience for undergraduates, in order to consistently measure the broader impact of the program on our learning objectives. This capstone experience will be fulfilled by one of the following: (1) a senior thesis on a special topic within the mathematical sciences, resulting in a concise report and oral presentation; (2) preparing and taking the GRE Mathematics Subject Test; or (3) the successful completion of an internship for USU credit.

Student success in subsequent graduate programs

A significant proportion of our graduating students in Mathematics and Statistics pursue graduate and professional degrees. Successful admission into such programs and subsequent degree completion can also help to understand how Beginning in 2016-17, these outcomes will be tracked both retrospectively and prospectively, for use in future calibration of our undergraduate programs.

Outcomes Data

Data-Based Decision Making

The Department of Mathematics and Statistics regularly restructures and enhances the undergraduate curriculum in response to student feedback and performance, course enrollments and evaluations, self-study and Regents reviews, professional and market trends, and new faculty expertise and research interests. The Department pays particular attention to recommendations from the profession – as best implemented in the context of USU’s mission and our existing strengths and capabilities – including the recent National Research Council report The Mathematical Sciences in 2025 (2013, National Academies Press).

The feedback and information from across these resources have led to these recent and ongoing programmatic changes:

  • (2015-2017) A new interdisciplinary data science degree program, in collaboration with Management Information Systems, Economics and Finance, and Computer Science, to better prepare students for the growing demands of big data and analytics. (Master's of Data Analytics degree program received final approval from the Board of Regents in July, 2017.)
  • (2014-2017) Additional courses in statistical computing and data science, including R programming, SAS programming, and statistical methods for big data.
    (2016-2017) A significant reworking of courses in applied and computational mathematics, along with mathematical biology, to provide more 1- and 2-credit offerings, and greater flexibility and breadth, and an additional 4000-level course in mathematical computing.
  • (2016-2018) An initiative to hire new faculty with expertise in mathematical computing and numerical methods, to enhance and update our undergraduate curriculum. (A new assistant professor in mathematical computing hired spring 2017. Ongoing search for a professor in Data Science and Analytics.)
  • (2017) Introduction of an additional course in discrete mathematics, to better serve students with interests in mathematical computing and computer science.
  • (2016) Revision of mathematics content course requirements for Elementary and Special Education Majors, to extend the former single content course for elementary teachers (Math 2020 Introduction to Logic and Geometry) into a 2-semester sequence: Math 2010 (Algebraic Thinking & Number Sense for Elementary School Teachers), and a revised Math 2020 (Euclidean Geometry & Statistics for Elementary School Teachers).
  • (2016-2017) Engagement in the Mathematics Teacher Education (MTE) Partnership, due to the success of our field-based mathematics teacher preparation program. The MTE-Partnership was established to “transform secondary mathematics teacher preparation” to ensure an adequate supply of teacher candidates who can promote mathematical excellence in their future students, leading to college and career readiness in accordance with documents such as the Common Core State Standards for Mathematics (CCSSM) and the Mathematics Education of Teachers II (METII). Using a Networked Improvement Community model, USU has collaborated with a research action cluster focused on developing MODULES for improving specialized mathematical knowledge for teaching in Statistics, Modeling, Geometry and Algebra