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Actuarial Science Graduate Programs

Individuals interested in obtaining either a master's degree or a Ph.D. in the field of actuarial science have a number of options to choose from. Keep reading to learn about course and admissions requirements for both program levels.

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The field of actuarial science involves using different mathematical methods and statistical analysis to assess risk in the finance and insurance industries. Individuals who study actuarial science at the graduate level are highly qualified for jobs as actuaries and insurance underwriters, among other possibilities. Graduate programs are available at both the master's and Ph.D. levels. We will learn about both options below.

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General Information About Actuarial Science Graduate Programs

At the master's level, graduate programs in actuarial science can usually be completed on a full- or part-time basis; full-time students could complete the program in as few as three semesters. At the Ph.D. level, program length includes at least two years of coursework followed by the time it takes to research, write, and defend a dissertation and fulfill any required teaching hours. Both master's and Ph.D. students may enroll in similar courses while pursuing their degree, though master's students do not have to write a dissertation. We will look at some common courses for these programs below.

Probability Theory

This course may be required toward the beginning of an actuarial science program, as it outlines fundamental principles in probability and statistics. Some topics likely covered during this course include infinite sequences, central limit theorem, and conditional probabilities.

Statistical Inference

In this course, students examine the basic principles of statistical inference and distribution theory as well as topics like point and interval estimation, the theory of hypothesis testing and the method of maximum likelihood. They may also learn how to apply these various methods when working in different industries.

Loss Distributions

In this course, students learn how to compile data from multiple sources and use various models, such as severity and frequency models, to estimate possible losses. They might also learn how to apply credibility theory.

Survival Methods and Analysis

Students taking a course in survival methods and analysis focus creating and interpreting survival models and distributions. Possible course topics include regression analysis, censored data, estimation of survival distribution, hypothesis testing of survival rates, and truncated lifetime data.

Linear Regression Models

Regression analysis is used frequently in actuarial science, so this course is designed to provide students with a strong background in the basics of regression models as well as other forms of applied statistics. Students study both simple and multiple regression, along with polynomial regression, co-linearity, and confounding. They also explore nonlinear regression.

Actuarial Science Graduate Program Admission Requirements

To apply for admission to either a master's level or Ph.D. program in actuarial science, you will need to possess a bachelor's degree, though Ph.D. programs also accept those who have already obtained a master's degree. Some programs may specify that your bachelor's degree should be in a related field, while others may only require that you have taken a specific number of courses in topics like linear algebra, economics, and calculus.

Both master's programs and Ph.D. programs often have a minimum GPA requirement of 3.0 on a 4.0 scale in order to be considered for admission. Most schools will also require you to submit GRE scores. Depending on the competitiveness of the program, they may post a general GRE score range in which most of their students scored.

Graduate programs in actuarial science provide students with an advanced understanding of the various statistical analysis methods necessary to be successful in their chosen field. Admission to these programs generally requires strong performance in an undergraduate or graduate program that included related coursework.

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