Statistics, BS
Degree: Bachelor of Science (BS)
Major: Statistics
Program Overview
All undergraduate degrees in the Department of Mathematics, Applied Mathematics and Statistics are based on a four-course sequence in calculus and differential equations. The mathematics and applied mathematics degrees each require further mathematics courses in analysis and algebra. The statistics degrees each require a further statistics core. There are additional requirements particular to each degree program, including technical electives in the major. Each degree program requires a minimum of 120 credit hours.
Students in statistics begin with a foundation in mathematics, followed by statistical theory and intensive modern data analysis. This prepares students to enter a growing profession with opportunities in academic, governmental, actuarial, and industrial spheres. The program offers a concentration in actuarial science, designed to develop both technical mastery and a broad appreciation of the discipline.
The BS degree in statistics requires the same coursework in mathematics and statistics as the BA degree. It also requires an additional 12 credit hours in the sciences.
Learning Outcomes
- Students will be able to know the fundamental concepts of probability theory, random variables, probability distributions, moments, and the transformation of random variables.
- Students will be able to correctly identify appropriate probability models for a given random phenomenon and demonstrates the capability of finding distributions of functions of random variables and properties thereof.
- Students will be able to know the fundamental concepts of the central limit theorem, law of large numbers, theory of estimation, and hypothesis testing.
- Students will be able to demonstrate the capability of setting up the mathematical proof for finding large sample properties of estimators and/or is able to construct appropriate statistical inferential procedures using such estimators.
- Students will be able to know the fundamental concepts of linear regression models and is trained with appropriate statistical software for exploratory data analysis, data visualization, building regression models, carrying out statistical inferences, and validations of model assumptions.
- Students will be able to formulate an appropriate linear regression model for a given problem, is able to fit such a model and use it for statistical inference, and/or identify its limitations.
- Students will be able to express a given research problem in quantitative and statistical terms, finds the appropriate set of statistical methods and/or models to solve the problem, and is able to implement them using appropriate statistical software that leads to the solution of the problem.
- Students will be able to effectively communicate the statistical analysis to a non-expert in statistics and is able to put the work in the proper context in the form of a technical report.
Undergraduate Policies
For undergraduate policies and procedures, please review the Undergraduate Academics section of the General Bulletin.
Combined Bachelor's/Master's Programs
Undergraduate students may participate in accelerated programs toward graduate or professional degrees. For more information and details of the policies and procedures related to accelerated studies, please visit the Undergraduate Academics section of the General Bulletin.
Program Requirements
Students seeking to complete this major and degree program must meet the general requirements for bachelor's degrees and the Unified General Education Requirements. Students completing this program as a secondary major while completing another undergraduate degree program do not need to satisfy the school-specific requirements associated with this major.
The BS degree in statistics requires a minimum of 62 hours of approved coursework, including 27 hours in statistics and the remainder in related disciplines. In addition to the requirements for the BA, the BS degree includes a laboratory science requirement.
| Code | Title | Credit Hours |
|---|---|---|
| Required Courses: | ||
| MATH 121 | Calculus for Science and Engineering I | 4 |
| or MATH 123 | Calculus I | |
| MATH 122 | Calculus for Science and Engineering II | 4 |
| or MATH 124 | Calculus II | |
| MATH 223 | Calculus for Science and Engineering III | 3 |
| or MATH 227 | Calculus III | |
| MATH 224 | Elementary Differential Equations | 3 |
| or MATH 228 | Differential Equations | |
| MATH 307 | Linear Algebra | 3 |
| ENGR 131 | Elementary Computer Programming | 3 |
| or MATH 330 | Introduction to Scientific Computing | |
| or CSDS 132 | Programming in Java | |
| STAT 301 | Introduction to Probability for Statistics | 3 |
| STAT 302 | Introduction to Statistical Inference | 3 |
| STAT 325 | Data Analysis and Linear Regression Models | 3 |
| STAT 326 | Multivariate Analysis and Data Mining | 3 |
| STAT 327 | Statistical Computing | 3 |
| STAT 346 | Mathematical Statistics | 3 |
| Statistical Methodology Courses a,b | 12 | |
| Laboratory Science Requirement | ||
| Choose at least one of the following sequences: | 6-8 | |
| General Physics I - Mechanics and General Physics II - Electricity and Magnetism | ||
| Principles of Chemistry I and Principles of Chemistry II and Principles of Chemistry Laboratory | ||
| Introduction to the Sun and Its Planets and Introduction to the Stars, Galaxies, and the Universe | ||
| Stars and Planets and Galaxies and Cosmology | ||
| Physical Geology and Introduction to Oceanography | ||
| Physical Geology and Earth History: Time, Tectonics, Climate, and Life | ||
| Additional courses in ASTR, BIOL, CHEM, EEPS, or PHYS | 4-6 | |
| Total Credit Hours | 62 | |
- a
Courses in statistical methodology chosen from STAT courses numbered 300 and higher, or courses in statistical methodology or probability approved by major advisor and taught in biostatistics, computer science, data science, economics, mathematics, operations research, etc.
- b
At least 6 hours must be in STAT.
Examples of non-STAT courses that can count as statistical methodology courses are as follows:
| Code | Title | Credit Hours |
|---|---|---|
| MATH 319 | Applied Probability and Stochastic Processes for Biology | 3 |
| MATH 321 | Fundamentals of Analysis I | 3 |
| MATH 322 | Fundamentals of Analysis II | 3 |
| MATH 327 | Convexity and Optimization | 3 |
| MATH 330 | Introduction to Scientific Computing | 3 |
| MATH 345 | Introduction to Linear Partial Differential Equations | 3 |
| MATH 356 | Math in Machine Learning | 3 |
| MATH 358 | Mathematical Modeling | 3 |
| MATH 376 | Mathematical Analysis of Biological Models | 3 |
| MATH 378 | Computational Neuroscience | 3 |
| MATH 380 | Introduction to Probability | 3 |
| MATH 382 | High Dimensional Probability | 3 |
| MATH 394 | Introduction to Information Theory | 3 |
| ECON 326 | Econometrics | 4 |
| ECON 327 | Advanced Econometrics | 3 |
| PQHS 435 | Survival Data Analysis | 3 |
| PQHS 453 | Categorical Data Analysis | 3 |
| PQHS 459 | Longitudinal Data Analysis | 3 |
| CSDS 323 | Numerical Algorithms for Machine Learning | 3 |
| CSDS 335 | Data Mining for Big Data | 3 |
| CSDS 340 | Introduction to Machine Learning | 3 |
Concentration Requirements
Actuarial Science Concentration
The concentration in Actuarial Science requires 12 credit hours as follows:
| Code | Title | Credit Hours |
|---|---|---|
| STAT 317 | Actuarial Science I | 3 |
| STAT 318 | Actuarial Science II | 3 |
| Two statistical methodology courses c,d | 6 | |
| Total Credit Hours | 12 | |
- c
Courses in statistical methodology specifically relevant to actuarial science, chosen from STAT courses numbered 300 and higher, or courses in statistical methodology or probability approved by major advisor and taught in biostatistics, computer science, data science, economics, mathematics, operations research, etc. These credits also may count towards the 12 credits of statistical methodology required for the major.
- d
Students are especially encouraged to discuss with their major advisor courses in operations research and numerical analysis which are fundamental to actuarial theory and computation.