The actuarial mathematics major is specifically designed for students who wish to pursue an actuarial field, pursue graduate work in financial mathematics, or employment in a mathematics or statistics-related field.
Program Highlights
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The inclusion of a minor in Risk Management and Insurance introduces the student to specific uses of Actuarial Mathematics.
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The combination of Applied Mathematics and Statistics expands the student’s knowledge of solution methods for Risk Analysis.
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The inclusion of computational analytical methods introduces the student to computer modeling.
Careers
Check out these ideas from ODU's Center for Career & Leadership Development and the Occupational Information Network (O*NET). A median salary is a midpoint of what people typically earn—half of those surveyed earned above the median salary, and half earned below.
Financial Analysts
Conduct quantitative analyses of information affecting investment programs of public or private institutions.
Risk Management Specialists
Analyze and manage risk management issues by identifying, measuring, and making decisions on operational or enterprise risks for an organization.
Actuaries
Analyze statistical data, such as mortality, accident, sickness, disability, and retirement rates and construct probability tables to forecast risk and liability for payment of future benefits. May ascertain insurance rates required and cash reserves necessary to ensure payment of future benefits.
Requirements
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Math Core courses: 34 credits (GPA of 2.3)
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Actuarial Math specific courses: 18 credits
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Minor in Risk Management and Insurance
Transfer
At ODU, we understand that as a transfer student you have unique needs that require a wide array of campus resources. The Center for Advising Administration and Academic Partnerships aims to create a transfer inclusive culture that supports the successful...
Featured Courses
Use of SAS and R to handle data sets. Topics for SAS include data input, creating permanent data sets, merging data sets, creating new variables, sorting, printing, charting, formatting, IML programming, macro programming, and an overview of proc SQL and other statistical procedures. Topics for R include data structure, control structure, writing functions, and graphics. Prerequisites: grade of C or better in STAT 130M or equivalent and a grade of C or better in MATH 316 or equivalent or permission of instructor.
This course is a data-based tour of advanced statistical techniques using software packages, exploring a catalog of data sets (simulated or otherwise) spanning a variety of fields and applications, including data suitable for regression, ANOVA, time series modeling, longitudinal data analysis, and multivariate techniques. Approaches will include parametric, nonparametric, simulation, and bootstrapping. SAS and R (S-plus) will be used extensively, with some other specialized products. For writing actual (not packaged) code, PROC IML and R will be used. This is a finishing course for applied statisticians, highly recommended for students planning a career in statistical programming and simulation. Prerequisites: A grade of C or better in STAT 405/STAT 505 and two of STAT 435/STAT 535, STAT 437/STAT 537, STAT 447/STAT 547 and STAT 450/STAT 550.
Topics include least squares problems, the QR factorization, the conjugate gradient method, Householder transformation and the QR method for approximating eigenvalues and singular values of a matrix. For applications, the finite difference method and the finite element method for solving partial differential equations, trigonometric interpolation and FFT as well as introductory study of optimization are discussed. Prerequisites: A grade of C or better in MATH 408/MATH 508.
Cost
Estimated rates for the 2024-25 academic year. Rates are subject to change. Anyone that is not a current Virginia resident will be charged non-resident rates. That includes international students.
Ways to Save
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