What is actuarial science? It uses analytical and statistical process to assess risk in various industries. It’s no easy job, but if you’re interested in math and statistics, becoming an actuarial science major may be a perfect fit. CMU’s actuarial science program offers you comprehensive training in thinking, reasoning and problem-solving — all of which strengthen your skills for a career in business, industry, government and more. Through professional development, resources, developing contacts through student organizations and free tutoring at the Math Center, you will get the support and opportunities to be successful.
Points of Pride
- Your classes will prepare you for the first three actuarial exams (P, FM, Life Contingencies), which are administered by the Society of Actuaries and the Casualty Actuarial Society. Students are encouraged to pass at least two exams by the time they graduate from CMU.
- Actuary science is considered a high-salary profession with great job security and vast opportunities.
Put your actuarial science degree to work
Most actuaries work full time in an office setting, but actuaries who work as consultants may frequently travel to meet with clients. Actuaries often develop, price and evaluate a variety of insurance products and calculate the costs of new risks.
U.S. Bureau of Labor Statistics sample data
Below is a list of potential careers, median salary over the course of the career and projected job growth.
|Job||Median Pay||Job Growth through 2026|
|Actuary||$101,560 per year||22% (5,300 more jobs)|
|Financial analyst||$84,300 per year||11% (32,200 more jobs)|
|Financial manager||$125,080 per year||19% (108,600 more jobs)|
The course listings below are a representation of what this academic program requires. For a full review of this program in detail please see our official online academic bulletin AND consult with an academic advisor. This listing does not include the General Education courses required for all majors and may not include some program specific information, such as admissions, retention, and termination standards.
(Click on the course name or number for a complete course description.)
Actuarial Science Major
Why Study Actuarial Science?
Actuaries are business professionals who use their mathematical, statistical, and business management skills to assess risk and uncertainty. About 70% of actuaries work for insurance companies; about 25% for consulting firms, and about 5% for government agencies. The actuarial employment rate is projected to grow 22% from 2018 to 2026, and it is one of the fastest growing professions. According to the U.S. News & World Report's "2018 Best Jobs Ranking," actuary ranked second in best business jobs and third in best jobs for STEM.
Actuarial Science at CMU
The major offers courses to prepare students for the actuarial Exam P, Exam FM, Exam IFM, and Exam LTAM administered by the Society of Actuaries (SOA) or the Casualty Actuarial Society (CAS). All of the courses required to fulfill the SOA/CAS Validation by Education Experience (VEE) are offered at CMU, and those courses are required for the Actuarial Science major. Students should try to pass at least two exams by the time they graduate from CMU. The major also provides coursework to prepare a graduate for a career in the business world in which the insurance industry is the focus. More direct contact with actuaries comes through the student organization Gamma Iota Sigma.
This major consists of 65 hours of course work in mathematics, statistics, accounting, economics, finance, and computer science. The major is designed to give the student the type of background necessary to pursue a career in actuarial science and, in particular, to prepare the student to pass four actuarial exams. There is no required minor. Advisors are from the Department of Statistics, Actuarial and Data Sciences.
Total: 65 semester hours
Required Courses I
Concepts of Financial Accounting
Students gain an understanding of the accounting system used to develop financial statements. The emphasis is on interpreting financial data used in business decision making. This course is approved for offering in a distance learning format. Recommended: completion of MTH 105.
Probability Foundations of Actuarial Science
Fundamental probability tools for quantitatively assessing risk, with emphasis on application of these tools to problems encountered in actuarial science. Prerequisite: STA 584.
Mathematical Theory of Interest
Fundamental concepts of the mathematical theory of interest and applications in calculating present and accumulated values for various streams of cash flows. Prerequisite: MTH 133 or graduate standing.
Mathematics of Financial Models
Introduction to the theoretical basis of certain actuarial models and the application of those models to financial risks. Prerequisites: ACT 540; STA 584; or graduate standing.
Principles of Macroeconomics
Provides understanding of basic principles of economics, methods of National Income accounting, inflation, unemployment, role of government, money and banking, monetary policy, and international economics. Credit may not be earned in more than one of ECO 201 and 204. ECO 201 may not be applied toward the University Program requirements if a student is earning the Bachelor of Science in Business Administration degree. This course may be offered in an online or hybrid format. (University Program Group III-B: Studies in Social Structures)
Principles of Microeconomics
Introduction to scarcity, choice, and opportunity cost; supply and demand; welfare economics; household and firm behavior; competition and monopoly; resource markets. Credit may not be earned in more than one of ECO 202 and ECO 203. This course may be offered in an online format. (University Program Group III-B: Studies in Social Structures)
Basic principles and techniques of the acquisition, management, and distribution of financial resources. Credit may not be earned in both FIN 302 and FIN 332. This course may be offered in an online format. Prerequisites: ACC 201 or 250; 56 semester hours completed. Recommended: ACC 202 or 255.
Limits, continuity, interpretations of the derivative, differentiation of elementary functions, applications of derivatives, antiderivatives, Riemann sums, definite integrals, fundamental theorem of calculus. This course may be offered in an online or hybrid format. Recommended: MTH 107, 109; or MTH 130. (University Program Group II-B: Quantitative and Mathematical Sciences)
Techniques of integration, applications of definite integrals, improper integrals, elementary differential equations, infinite series, Taylor series, and polar coordinates. Prerequisite: MTH 132 or placement.
Linear Algebra and Matrix Theory
Systems of linear equations, matrices, determinants, vectors, vector spaces, eigenvalues, linear transformations, applications and numerical methods. Prerequisite: MTH 132.
Vectors and surfaces in R3, vector-valued functions, functions of several variables, partial differentiation and some applications, multiple integrals, vector calculus. Prerequisites: MTH 133. Pre/Co-Requisites: MTH 223 or 232.
Statistical Programming for Data Management and Analysis
Introduction to statistical programming for managing and analyzing data, including programming logic, data manipulation, missing data handling, basic techniques for analyzing data and creating reports. Prerequisites: STA 282 or 382 or 392; or graduate standing.
Applied Statistical Methods I
Applications of statistical analysis methods including the usage of computer software packages. Topics include simple and multiple regression, diagnostics, forecasting, and analysis of variance. This course may be offered in an online or hybrid format. Prerequisites: STA 282 or 382 or 392; or graduate standing.
Mathematical Statistics I
Probability defined on finite and infinite samples spaces, conditional probability and independence, random variables, expectations, moment-generating functions, probability models, limit theorems. Prerequisite: MTH 233.
Mathematical Statistics II
Introductory topics from mathematical theory of statistics: population distributions, sampling distributions, point and interval estimation, tests of hypotheses. Prerequisite: STA 584.
Time Series Forecasting
Introduction to basic time series forecasting techniques. Topics include forecasting, basic stochastic models, time series regression, stationary and nonstationary models. Prerequisite: STA 580.
Required Courses II
Introduction to spreadsheets and report generation. Features common to most spreadsheets. Evaluation of software packages. This course is approved for offering in a distance learning format. Recommended: Familiarity with personal computer use.
Principles of Computer Programming
Algorithm development and problem solving methods. Design and development of computer programs in a structured programming language. Pre/Co-requisite: One of MTH 130, 132, 133, 217. (University Program Group II-B: Quantitative and Mathematical Sciences)
Select three of the following in consultation with the advisor:
Actuarial Mathematics for Life Contingencies I
Introduction to survival distributions and life tables, life annuities and life insurance, benefit premiums and benefit reserves. Prerequisites: ACT 539, 540.
Actuarial Mathematics for Life Contingencies II
Estimating survival curves, introduction to multiple state models including multiple life models and multiple decrement models, pension mathematics, and cash flow analysis for insurance products. Prerequisites: ACT 541; STA 585.
Applied Business Communication
Expands understanding of the communication process as students apply business communication principles related to oral, written, and employment communication in a real-world setting. Prerequisite: 56 semester hours completed. Recommended: ENG 201.
This course introduces students to risk management and insurance decisions in personal financial planning, including health, disability, property, liability, and long-term care risks and insurance. This course may be offered in an online format. Prerequisite: ACC 201 or 250.
Introduction to Mathematical Proof
Study of several basic concepts in mathematics including logic, set theory, relations and functions, cardinality, number systems, sequences. Pre/Co-requisites: MTH 175, 351; or one of: MTH 223, 232.
Applied Statistical Methods II
Linear models with autocorrelated errors, non-linear regression, logistic regression, multiway ANOVA, simultaneous comparison procedures, ANOVA diagnostics, analysis of covariance, unbalanced data and missing data analysis. Prerequisites: MTH 223; STA 580; or graduate standing.
Data Mining Techniques I
Data mining techniques for analyzing large and high dimensional data. Topics include data mining strategy, exploratory analysis, predictive modeling techniques, model assessment and comparison. Prerequisite: STA 580 or graduate standing.
Six Sigma: Foundations and Techniques for Green Belts
Six Sigma problem solving strategy for continuous improvement. Topics include DMAIC and PDSA strategies and applications, tools and statistical techniques used in the strategies. Prerequisites: STA 282 or 382 or 392; or graduate standing.
Introduction to Bayesian Statistics
Introduction to Bayesian analysis and applications. Topics include principles of Bayesian statistics, Bayesian linear models and generalized linear models. Prerequisites: STA 580; STA 581 or 584; or graduate standing.