Bachelor of Science with a Major in Mathematics, Applied Statistics and Data Analytics
This track is designed to offer students a solid background in applied statistics and data analytics. It will prepare students for employment in a wide array of fields that employ data analysis, statistical modeling, data-driven decision-making, and other types of quantitative analysis.
The Bachelor of Science in Mathematics program is designed to provide students with a strong foundation in mathematical theory, problem-solving skills, and mathematical applications. This undergraduate degree program offers a comprehensive curriculum that covers a wide range of mathematical topics, equipping students with the knowledge and skills necessary for careers in many government and private-sector fields, including statistics, data analysis, actuarial science, data science, and risk analysis. It also prepares students for graduate studies in mathematics and math education.
This track is designed to offer students a solid background in applied statistics and data analytics. It will prepare students for employment in a wide array of fields that employ data analysis, statistical modeling, data-driven decision-making, and other types of quantitative analysis.
Program Location
Carrollton Campus
Method of Delivery
Face to Face
Accreditation
The University of West Georgia is accredited by The Southern Association of Colleges and Schools Commission on Colleges (SACSCOC).
Credit and transfer
Total semester hours required:
This program may be earned entirely face-to-face. However, depending on the courses chosen, a student may choose to take some partially or fully online courses.
Save money
UWG is often ranked as one of the most affordable accredited universities of its kind, regardless of the method of delivery chosen.
Details
- Total tuition costs and fees may vary, depending on the instructional method of the courses in which the student chooses to enroll.
- The more courses a student takes in a single term, the more they will typically save in fees and total cost.
- Face-to-face or partially online courses are charged at the general tuition rate and all mandatory campus fees, based on the student's residency (non-residents are charged at a higher rate).
- Fully or entirely online course tuition rates and fees my vary depending on the program. Students enrolled in exclusively online courses do not pay non-Resident rates.
- Together this means that GA residents pay about the same if they take all face-to-face or partially online courses as they do if they take only fully online courses exclusively; while non-residents save money by taking fully online courses.
- One word of caution: If a student takes a combination of face-to-face and online courses in a single term, he/she will pay both all mandatory campus fees and the higher eTuition rate.
- For cost information, as well as payment deadlines, see the Student Accounts and Billing Services website
There are a variety of financial assistance options for students, including scholarships and work study programs. Visit the Office of Financial Aid's website for more information.
Coursework
Track Requirements: 36 Hours
MATH 1401, MATH 3203, MATH 3873, MATH 4213, MATH 4803, MATH 4813, MATH 4843, MATH 4873
Additional Stats Course
Choose one of MATH 4823, MATH 4883, MATH 4885, or MATH 4986
Directed Electives: 9 Hours*
9 hours of 2XXX or higher courses selected from one of the lists below.
Note: At least 12 credit hours from the combined general electives and directed electives must be at the 3000 level or above.
- ACCT, ECON, FINC, MGMT, MKTG
- SPMG
- BIOL, CHEM, PHYS, GEOL
- CS, COMP
- PHIL, PSYC, SOCI
General Electives: 21 Hours*
Note: At least 12 credit hours from the combined general electives and directed electives must be at the 3000 level or above.
Track Required
This is a non-calculus based introduction to statistics. Course content includes descriptive statistics, probability theory, confidence intervals, hypothesis testing, and other selected statistical topics.Prerequisites: Math 1101 Mathematical Modeling, 1111 College Algebra, or 1113 Precalculus or approved equivalent.
A calculus based statistics course with a strong emphasis on probability theory. Exercises are both theoretical and applied, including both discrete and continuous probability distributions such as the binomial and normal. The course provides the underlying theory and mathematically derived techniques of statistics. Hypothesis testing for various parameters and regression are also discussed in this course.
This course helps develop programming skills necessary for statistical analysis and data science. Students will learn the basic syntax and functions of the programming language, data organization and visualization, programming, as well as how to use existing packages of the language. Case studies in applied statistics, data science, or machine learning will be discussed.
A continuation of MATH 4203, this course introduces certain discrete and continuous distributions such as the Poisson, Gamma, T and F. The course also provides an introduction to multivariate distributions. Estimation techniques such as the method of moments and maximum likelihood are discussed along with properties such as unbiasedness, efficiency, sufficiency and consistency of estimators.
This course involves a thorough examination of the analysis of variance statistical method including hypotheses tests, interval estimation, and multiple comparison techniques of both single-factor and two-factor models. Extensive use of a statistical computer package, Minitab, will be a necessary part of the course.
This course involves a thorough examination of both simple linear regression models and multivariate models. The course requires extensive use of statistical software for confidence intervals, statistical tests, statistical plots, and model diagnostics.
This course will consider applied principles and approaches for conducting a sample survey, designing a survey, and analyzing a survey.
This course introduces computation-intensive statistical approaches and modern machine learning methods. Topics include:1. R-computing and programming (intermediate to advanced)2. Rmarkdown3. Data scraping and text mining4. Random number simulations5. Bootstrapping6. Optimization7. Regression8. Analysis of Variance9. Classification, Clustering10. Network data analysis
Additional Stats Courses
Choose one of MATH 4823, 4883, 4885, OR 4986
This course provides an introduction to design and analysis of planned experiments. Topics will include one and two-way designs; completely randomized designs, randomized block designs, Latin-square and factorial designs. Use of technology will be an integral part of this course.
This course will involve the study of several nonparametric tests including the Runs test, Wilcoxon signed rank and rank sum test, Kruskal, Wallis and Friedman F test. These tests will include applications in the biological sciences, engineering, and business areas. A statistical software package will be used to facilitate these tests.
This course will be taught from a variety of statistical topics such as statistical quality control, applied time series, game theory, etc. Prerequisite: Dependent upon course title.
A hands-on supervised field experience in mathematics or statistics. Students will create and present a comprehensive portfolio documenting the field experience. This course may be repeated for a total of 6 hours. Grading is S/U.
William M Faucette, Ph.D.
Associate Professor of Mathematics
Scott Gordon, Ph.D.
Professor of Mathematics
Nguyen Hoang, Ph.D.
Associate Professor of Mathematics
David Leach, Ph.D.
Professor of Mathematics & Program Coordinator
Kyunghee Moon, Ph.D.
Professor of Mathematics
Veena Paliwal, Ph.D.
Associate Professor of Mathematics
Dave Robinson, Ph.D.
Senior Lecturer in Mathematics
Kwang Shin, Ph.D.
Associate Professor of Mathematics
Fengrong Wei, Ph.D.
Professor of Mathematics
Rui Xu, Ph.D.
Professor of Mathematics
Mohammad Yazdani, Ph.D.
Professor of MathematicsNo Admissions Data Provided.
Specific dates for Admissions (Undergraduate only), Financial Aid, Fee Payments, Registration, Start/End of term, Final Exams, etc. are available in THE SCOOP.
Learning Objectives:
- Students will demonstrate ability to perform a sustained investigation into a specific mathematical problem or topic, and effectively communicate their findings orally and in writing.
- Students will demonstrate a thorough understanding of the calculus, including its computational aspects, applications, and theoretical foundations.
- Students will demonstrate the ability to read, write, and understand mathematical proofs involving foundational aspects of mathematics.
- Students will demonstrate the ability to utilize statistical methods to analyze real-world problems and draw inferences about a studied population using collected sample data.