Applied Statistics and Data Science, Bachelor of Science

CIP Code

27.0601.00

Program Overview

Applied Statistics and Data Science prepares individuals for careers as statisticians, data scientists, data analysts and more. A Bachelor of Science in Applied Statistics and Data Science includes planning for the collection of data, managing data, analyzing, interpreting and drawing conclusions from data, and identifying problems, solutions and opportunities using the analysis. It can lead to a lucrative career due to the growing needs of dealing with Big Data in astronomical, medical and various biological fields.

Specific graduation requirements for this program beyond university bachelor’s degree requirements.

• Major requirements must be completed with a minimum grade of ‘C’ and a minimum GPA of 2.5.

Core Curriculum - 42 hours

The Core Curriculum serves as a broad foundation for the undergraduate degree. All candidates for a bachelor’s degree must achieve core student learning outcomes, including communication, critical thinking, empirical and quantitative skills, teamwork, personal responsibility, and social responsibility, by completing courses within each category or component area of the Core Curriculum as outlined below.

The University has approved specific courses that satisfy Core Curriculum Requirements. Approved courses can be found on the Core Curriculum Page. Students seeking the most efficient way to complete the core curriculum and major or minor requirements are advised to take approved courses that can fulfill both requirements. Although core curriculum courses can also be used to fulfill major or minor requirements, earned credits hours are only applied once.

The courses listed below fulfill core curriculum and major requirements. Students who have completed a core curriculum category with courses other than those listed below will still be required to take the listed course(s) to meet major requirements.

020 Mathematics - 3 hours

Choose from:

CourseCourse Name
MATH 1342Elementary Statistical Methods
MATH 1343Introduction to Biostatistics

030 Life and Physical Sciences - 6 hours

Choose one pair from:

CourseCourse Name
BIOL 1406General Biology I
BIOL 1407General Biology II
Or
ENVR 1401Introduction to Environmental Science I
ENVR 1402Introduction to Environmental Science II

080 Social and Behavioral Sciences - 3 hours

Choose from:

CourseCourse Name
ECON 1301Introduction to Economics
ECON 2302Principles of Microeconomics

090 Integrative and Experiential Learning - 6 hours

Required:

CourseCourse Name
CSCI 1380Introduction to Programming in Python

Required:

CourseCourse Name
CSCI 1380Introduction to Programming in Python

Choose one pair from:

CourseCourse Name
BIOL 1406General Biology I
BIOL 1407General Biology II
Or
ENVR 1401Introduction to Environmental Science I
ENVR 1402Introduction to Environmental Science II

One credit hour from Life and Physical Science course applies for a total of two credits.

Major Requirements - 73 hours

Required Courses - 36 hours

CourseCourse Name
MATH 2413Calculus I
MATH 2414Calculus II
MATH 2318Linear Algebra
CSCI 1470Computer Science I
CSCI 2380Computer Science II
STAT 2336Statistical Computing and Data Management
STAT 3301Applied Statistics
STAT 3335Applied Regression Analysis
STAT 3337Probability and Statistics
STAT 3338Mathematical Statistics
STAT 4390Statistics Project

Prescribed Electives - 30 hours

Advanced Statistics Electives - 12 hours

Choose 12 hours from the following:

CourseCourse Name
STAT 3336Sampling
STAT 3351Multivariate Analysis
STAT 4332Experimental Design and Analysis
STAT 4341Introduction to Stochastic Processes
STAT 4399Special Topics in Statistics

Advanced Math Electives - 9 hours (6 hours must be advanced)

Choose 9 hours from the following:

CourseCourse Name
MATH 2415Calculus III
MATH 3341Differential Equations
MATH 3343Introduction to Mathematical Software
MATH 3345Linear Optimization
MATH 3349Numerical Methods
MATH 3350Introduction to Mathematical Proof
MATH 3361Applied Discrete Mathematics
MATH 3363Modern Algebra I
MATH 4364Modern Algebra II
MATH 3372Real Analysis I
MATH 4373Real Analysis II
MATH 3399Special Topics in Mathematics
MATH 4355Topology

Advanced Computer Science Electives - 9 hours

Choose 9 hours from the following:

CourseCourse Name
CSCI 3310Mathematical Foundations of Computer Science
CSCI 3329Object Oriented Programming in Python
CSCI 3333Algorithms and Data Structures
CSCI 4310Design and Analysis of Algorithms
CSCI 4333Database Design and Implementation
CSCI 4343Data Mining
CSCI 4352Machine Learning

Support Courses - 7 hours

CourseCourse Name
MATH 1314College Algebra
Or
MATH 1414College Algebra
And
MATH 2412Precalculus

Students who test out of MATH 1314, MATH 1414 and/or MATH 2412 may take free electives in lieu of this requirement.

Free Electives

Free electives credit hours required may vary to achieve the institutional minimum of 120 hours for a degree.

Total Credit Hours: 42

Total Credit Hours: 120

View this program’s recommended roadmap to graduation.

 

UTRGV Roadmaps are a suggested sequence of courses designed to assist students in completing their undergraduate degree requirements. This is a term-by-term sample roadmap of courses required to complete the degree. Students must satisfy all requirements in their catalog including, but not limited to course prerequisites, grade point average and course grade benchmarks, progression requirements, and graduation requirements. 

 

Students should meet with their academic advisor every semester to discuss their individualized path toward completion. Degree progress within this roadmap depends upon such factors as course availability, individual student academic preparation and readiness, student time management, work and personal responsibilities, and financial considerations. Students may choose to take courses during summer terms to reduce course loads during long semesters.