Applied Statistics and Actuarial Science Bachelor of science degree
Applied Statistics and Actuarial Science
Bachelor of science degree
Breadcrumb
 RIT /
 Rochester Institute of Technology /
 Academics /
 Applied Statistics and Actuarial Science BS
Inquire about undergraduate study Visit Apply
585‑475‑2163, mlrsma@rit.edu
School of Mathematical Sciences
Overview
Using calculus, statistics, algebra, and computer science, statisticians apply their knowledge of statistical methods—the collection, processing, and analysis of data and its interpretation—to a variety of areas, including biology, economics, engineering, medicine, public health, psychology, marketing, and sports.
The applied statistics and actuarial science degree will provide you with a strong foundation in mathematical and statistical methodology, experience in its applications, a solid background in the use of statistical computing packages, and the skills to communicate the results of statistical analysis. The actuary degree gives you an advantage in the fields of business, government, and industry, and also prepares you for advanced study in graduate school. You'll collaborate with specialists in both scientific and nontechnical areas to design and conduct experiments and interpret the results. Diverse application areas for graduates include product design, biostatistics, actuarial science, quality control, and statistical forecasting.
As an accelerated dual degree program that allows students to earn a BS and an MS with one additional year of graduate study, the applied statistics and actuarial science degree will provide you with a strong foundation in mathematical and statistical methodology, experience in its applications, a solid background in the use of statistical computing packages, and the skills to communicate the results of statistical analysis. The actuary degree gives you an advantage in the fields of business, government, and industry, and also prepares you for advanced study in graduate school. You'll collaborate with specialists in both scientific and nontechnical areas to design and conduct experiments and interpret the results. Diverse application areas for graduates include product design, biostatistics, actuarial science, quality control, and statistical forecasting.
Educational Approach
Early courses are designed to give you a foundation in calculus, statistics, algebra, and computer science. Application areas are very diverse and include product design, biostatistics, actuarial science, quality control, and statistical forecasting.
Real World Experiences
Students collaborate with specialists in both scientific and nontechnical areas to design and conduct experiments and interpret the results. Application areas are very diverse and include product design, biostatistics, actuarial science, quality control, and statistical forecasting.
Nature of Work
Statisticians contribute to scientific inquiry by applying their mathematical and statistical knowledge to the design of surveys and experiments; collection, processing, and analysis of data; and interpretation of the results. Statisticians may apply their knowledge of statistical methods to a variety of subject areas, such as biology, economics, engineering, medicine, public health, psychology, marketing, education, and sports. Many economic, social, political, and military decisions cannot be made without the use of statistical techniques, such as the design of experiments to gain federal approval of a newly manufactured drug. In industry, statisticians play an important role in quality control and product/process improvement based on data analysis.
Industries

Insurance 
Government (Local, State, Federal) 
Investment/Portfolio Management 
Health Care 
Defense 
Scientific and Technical Consulting 
Biotech and Life Sciences 
Telecommunications
Typical Job Titles
Actuary  Operations Research Analyst 
Financial Analyst  Teacher (secondary or postsecondary) 
Market Research Specialist  Data Analyst (e.g. biological, clinical trial) 
Quality Assurance Engineer/Analyst  Biostatistician 
Underwriter  Statistician 
Curriculum
Applied Statistics and Actuarial Science, BS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
CSCI101 
Principles of Computing
This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop stepbystep written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homeworks, group discussions and debates, and development of a term paper.

3 
MATH181 
LAS Perspective 7A (mathematical): ProjectBased Calculus I
This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals.

4 
MATH182 
LAS Perspective 7B (mathematical): ProjectBased Calculus II
This is the second in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates.

4 
MATH199 
Mathematics and Statistics Seminar
This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing.

1 
YOPS10 
RIT 365: RIT Connections
RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies.

0 
LAS Elective 
3  
First Year Writing (WI) 
3  
LAS Perspective 1 (ethical) 
3  
LAS Perspective 2 (artistic) 
3  
LAS Perspective 5‡ (natural science inquiry) 
4  
Wellness Education* 
0  
Second Year  
MATH200 
Discrete Mathematics and Introduction to Proofs
This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics.

3 
MATH221 
Multivariable and Vector Calculus
This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219.

4 
MATH241 
Linear Algebra
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.

3 
MATH251 
Probability and Statistics I
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.

3 
MATH252 
Probability and Statistics II
This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. The statistical software package MINITAB will be used for data analysis and statistical applications.

3 
MATH399 
Mathematical Sciences Job Search Seminar
This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks.

0 
Free Elective 
3  
LAS Elective 
3  
LAS Perspective 3 (global) 
3  
LAS Perspective 4 (social) 
3  
LAS Perspective 6‡ (scientific principles) 
4  
Third Year  
MATH255 
Actuarial Mathematics
This course provides challenging problems in probability whose solutions require a combination of skills that one acquires in a typical mathematical statistics curriculum. Course work synthesizes basic, essential problemsolving ideas and techniques as they apply to actuarial mathematics and the first actuarial exam.

3 
MATH261 
Topics in the Mathematics of Finance
This course examines concepts in finance from a mathematical viewpoint. It includes topics such as the BlackScholes model, financial derivatives, the binomial model, and an introduction to stochastic calculus. Although the course is mathematical in nature, only a background in calculus (including Taylor series) and basic probability is assumed; other mathematical concepts and numerical methods are introduced as needed.

3 
STAT305 
Regression Analysis
This course covers regression techniques with applications to the type of problems encountered in realworld situations. It includes use of the statistical software SAS. Topics include a review of simple linear regression, residual analysis, multiple regression, matrix approach to regression, model selection procedures, and various other models as time permits.

3 
STAT325 
Design of Experiments (WI)
This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include singlefactor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits.

3 
STAT511 
Statistical Software
This course is an introduction to two statisticalsoftware packages, SAS and R, which are often used in professional practice. Some comparisons with other statisticalsoftware packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; builtin functions; creation of new functions or macros; graphics; matrices and arrays; simulations; select statistical applications.

3 
Program Electives** 
6  
LAS Immersion 1, 2 
6  
LAS Elective 
3  
Fourth Year  
STAT405 
Mathematical Statistics I
This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference.

3 
STAT406 
Mathematical Statistics II
This course is a continuation of STAT405 covering classical and Bayesian methods in estimation theory, chisquare test, NeymanPearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference.

3 
STAT500 
Senior Capstone in Statistics
The course introduces the student to statistical situations not encountered previously in courses of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include openended analysis of data, review of statistical literature on current techniques and practice of statistics, development of statistical communication skills, and the use of statistical software tools in data analysis. Students may work individually or in a group. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Student teams are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set.

3 
LAS Immersion 3 
3  
Program Electives** 
12  
Free Elective 
3  
LAS Electives 
6  
Total Semester Credit Hours  123 
Please see General Education Curriculum–Liberal Arts and Sciences (LAS) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
‡ Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
** Two of the six program electives must be from the following list of courses: Stochastic Processes (MATH505), Statistical Quality Control (STAT315), Introduction to Time Series (STAT335), Nonparametric Statistics (STAT345), Statistical Sampling (STAT415), Multivariate Analysis (STAT425), or Statistical Linear Models (STAT435). A program elective is any MATH or STAT course with a course number higher than 250.
Accelerated dual degree options
Accelerated dual degree options are for undergraduate students with outstanding academic records. Upon acceptance, wellqualified undergraduate students can begin graduate study before completing their BS degree, shortening the time it takes to earn both degrees. Students should consult an academic adviser for more information.
Applied Statistics and Actuarial Science, BS degree/Applied and Computational Mathematics (thesis option), MS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
CSCI101 
Principles of Computing
This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop stepbystep written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homeworks, group discussions and debates, and development of a term paper.

3 
MATH181 
LAS Perspective 7A: ProjectBased Calculus I
This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals.

4 
MATH182 
LAS Perspective 7B: ProjectBased Calculus II
This is the second in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates.

4 
MATH199 
Mathematics and Statistics Seminar
This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing.

1 
YOPS10 
RIT 365: RIT Connections
RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies.

0 
LAS Elective 
3  
First Year Writing (WI) 
3  
LAS Perspective 1 (ethical) 
3  
LAS Perspective 2 (artistic) 
3  
LAS Perspective 5‡ (natural science inquiry) 
4  
LAS Perspective 6‡ (scientific principles) 
4  
Wellness Education* 
0  
Second Year  
MATH200 
Discrete Mathematics and Introduction to Proofs
This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics.

3 
MATH221 
Multivariable and Vector Calculus
This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219.

4 
MATH231 
Differential Equations
This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms.

3 
MATH241 
Linear Algebra I
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.

3 
MATH251 
Probability and Statistics I
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.

3 
MATH252 
Probability and Statistics II
This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. The statistical software package MINITAB will be used for data analysis and statistical applications.

3 
MATH399 
Mathematical Science Job Search Seminar
This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks.

0 
LAS Immersion 1, 2 
6  
LAS Perspective 3 (global) 
3  
LAS Perspective 4 (social) 
3  
Third Year  
MATH255 
Actuarial Mathematics
This course provides challenging problems in probability whose solutions require a combination of skills that one acquires in a typical mathematical statistics curriculum. Course work synthesizes basic, essential problemsolving ideas and techniques as they apply to actuarial mathematics and the first actuarial exam.

3 
MATH261 
Topics in the Mathematics of Finance
This course examines concepts in finance from a mathematical viewpoint. It includes topics such as the BlackScholes model, financial derivatives, the binomial model, and an introduction to stochastic calculus. Although the course is mathematical in nature, only a background in calculus (including Taylor series) and basic probability is assumed; other mathematical concepts and numerical methods are introduced as needed.

3 
STAT305 
Regression Analysis
This course covers regression techniques with applications to the type of problems encountered in realworld situations. It includes use of the statistical software SAS. Topics include a review of simple linear regression, residual analysis, multiple regression, matrix approach to regression, model selection procedures, and various other models as time permits.

3 
STAT325 
Design of Experiments (WI)
This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include singlefactor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits.

3 
STAT511 
Statistical Software
This course is an introduction to two statisticalsoftware packages, SAS and R, which are often used in professional practice. Some comparisons with other statisticalsoftware packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; builtin functions; creation of new functions or macros; graphics; matrices and arrays; simulations; select statistical applications.

3 
Free Electives 
6  
LAS Immersion 3 
3  
Program Electives 
9  
Fourth Year  
MATH606 
Graduate Seminar I
The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics.

1 
MATH607 
Graduate Seminar II
This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics.

1 
STAT405 
Mathematical Statistics I
This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference.

3 
STAT406 
Mathematical Statistics II
This course is a continuation of STAT405 covering classical and Bayesian methods in estimation theory, chisquare test, NeymanPearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference.

3 
STAT500 
Senior Capstone in Statistics
The course introduces the student to statistical situations not encountered previously in courses of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include openended analysis of data, review of statistical literature on current techniques and practice of statistics, development of statistical communication skills, and the use of statistical software tools in data analysis. Students may work individually or in a group. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Student teams are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set.

3 
Math Graduate Core Courses 
9  
LAS Electives 
12  
Fifth Year  
MATH790 
Research and Thesis
Masterslevel research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

7 
Math Graduate Core Course 
3  
Graduate Electives 
9  
Total Semester Credit Hours  147 
Please see General Education Curriculum–Liberal Arts and Sciences (LAS) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
‡ Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
Applied Statistics and Actuarial Science, BS degree/Applied and Computational Mathematics (project option), MS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
CSCI101 
Principles of Computing
This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop stepbystep written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homeworks, group discussions and debates, and development of a term paper.

3 
MATH181 
LAS Perspective 7A: ProjectBased Calculus I
This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals.

4 
MATH182 
LAS Perspective 7B: ProjectBased Calculus II
This is the second in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates.

4 
MATH199 
Mathematics and Statistics Seminar
This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing.

1 
YOPS10 
RIT 365: RIT Connections
RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies.

0 
LAS Elective 
3  
First Year Writing (WI) 
3  
LAS Perspective 1 (ethical) 
3  
LAS Perspective 2 (artistic) 
3  
LAS Perspective 5‡ (natural science inquiry) 
4  
LAS Perspective 6‡ (scientific principles) 
4  
Wellness Education* 
0  
Second Year  
MATH200 
Discrete Mathematics and Introduction to Proofs
This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics.

3 
MATH221 
Multivariable and Vector Calculus
This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219.

4 
MATH231 
Differential Equations
This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms.

3 
MATH241 
Linear Algebra I
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.

3 
MATH251 
Probability and Statistics I
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.

3 
MATH252 
Probability and Statistics II
This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. The statistical software package MINITAB will be used for data analysis and statistical applications.

3 
MATH399 
Mathematical Science Job Search Seminar
This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks.

0 
LAS Immersion 1, 2 
6  
LAS Perspective 3 (global) 
3  
LAS Perspective 4 (social) 
3  
Third Year  
MATH255 
Actuarial Mathematics
This course provides challenging problems in probability whose solutions require a combination of skills that one acquires in a typical mathematical statistics curriculum. Course work synthesizes basic, essential problemsolving ideas and techniques as they apply to actuarial mathematics and the first actuarial exam.

3 
MATH261 
Topics in the Mathematics of Finance
This course examines concepts in finance from a mathematical viewpoint. It includes topics such as the BlackScholes model, financial derivatives, the binomial model, and an introduction to stochastic calculus. Although the course is mathematical in nature, only a background in calculus (including Taylor series) and basic probability is assumed; other mathematical concepts and numerical methods are introduced as needed.

3 
STAT305 
Regression Analysis
This course covers regression techniques with applications to the type of problems encountered in realworld situations. It includes use of the statistical software SAS. Topics include a review of simple linear regression, residual analysis, multiple regression, matrix approach to regression, model selection procedures, and various other models as time permits.

3 
STAT325 
Design of Experiments (WI)
This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include singlefactor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits.

3 
STAT511 
Statistical Software
This course is an introduction to two statisticalsoftware packages, SAS and R, which are often used in professional practice. Some comparisons with other statisticalsoftware packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; builtin functions; creation of new functions or macros; graphics; matrices and arrays; simulations; select statistical applications.

3 
Free Electives 
6  
LAS Immersion 3 
3  
Program Electives 
9  
Fourth Year  
MATH606 
Graduate Seminar I
The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics.

1 
MATH607 
Graduate Seminar II
This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics.

1 
STAT405 
Mathematical Statistics I
This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference.

3 
STAT406 
Mathematical Statistics II
This course is a continuation of STAT405 covering classical and Bayesian methods in estimation theory, chisquare test, NeymanPearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference.

3 
STAT500 
Senior Capstone in Statistics
The course introduces the student to statistical situations not encountered previously in courses of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include openended analysis of data, review of statistical literature on current techniques and practice of statistics, development of statistical communication skills, and the use of statistical software tools in data analysis. Students may work individually or in a group. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Student teams are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set.

3 
Math Graduate Core Courses 
9  
LAS Electives 
12  
Fifth Year  
MATH790 
Research and Thesis
Masterslevel research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

4 
Math Graduate Core Course 
3  
Graduate Electives 
12  
Total Semester Credit Hours  147 
Please see General Education Curriculum–Liberal Arts and Sciences (LAS) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
‡ Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
Applied Statistics and Actuarial Science, BS degree/Applied Statistics, MS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
CSCI101 
Principles of Computing
This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop stepbystep written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homeworks, group discussions and debates, and development of a term paper.

3 
MATH181 
LAS Perspective 7A: ProjectBased Calculus I
This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals.

4 
MATH182 
LAS Perspective 7B: ProjectBased Calculus II
This is the second in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates.

4 
MATH199 
Mathematics and Statistics Seminar I
This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing.

1 
YOPS10 
RIT 365: RIT Connections
RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies.

0 
LAS Elective 
3  
First Year Writing (WI) 
3  
LAS Perspective 1 (ethical) 
3  
LAS Perspective 2 (artistic) 
3  
LAS Perspective 5‡ (natural science inquiry) 
4  
LAS Perspective 6‡ (scientific principles) 
4  
Wellness Education* 
0  
Second Year  
MATH200 
Discrete Mathematics and Introduction to Proofs
This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics.

3 
MATH221 
Multivariable and Vector Calculus
This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219.

4 
MATH241 
Linear Algebra I
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.

3 
MATH251 
Probability and Statistics I
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.

3 
MATH252 
Probability and Statistics II
This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. The statistical software package MINITAB will be used for data analysis and statistical applications.

3 
MATH399 
Mathematical Science Job Search Seminar
This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks.

0 
Program Elective 
3  
LAS Immersion 1, 2 
6  
LAS Perspective 3 (global) 
3  
LAS Perspective 4 (social) 
3  
Third Year  
MATH255 
Actuarial Mathematics
This course provides challenging problems in probability whose solutions require a combination of skills that one acquires in a typical mathematical statistics curriculum. Course work synthesizes basic, essential problemsolving ideas and techniques as they apply to actuarial mathematics and the first actuarial exam.

3 
MATH261 
Topics in the Mathematics of Finance
This course examines concepts in finance from a mathematical viewpoint. It includes topics such as the BlackScholes model, financial derivatives, the binomial model, and an introduction to stochastic calculus. Although the course is mathematical in nature, only a background in calculus (including Taylor series) and basic probability is assumed; other mathematical concepts and numerical methods are introduced as needed.

3 
STAT325 
Design of Experiments (WI)
This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include singlefactor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits.

3 
STAT405 
Mathematical Statistics I
This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference.

3 
STAT406 
Mathematical Statistics II
This course is a continuation of STAT405 covering classical and Bayesian methods in estimation theory, chisquare test, NeymanPearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference.

3 
Free Electives 
6  
LAS Immersion 3 
3  
Program Electives 
6  
Fourth Year  
STAT500 
Senior Capstone in Statistics (WI)
The course introduces the student to statistical situations not encountered previously in courses of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include openended analysis of data, review of statistical literature on current techniques and practice of statistics, development of statistical communication skills, and the use of statistical software tools in data analysis. Students may work individually or in a group. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Student teams are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set.

3 
STAT611 
Statistical Software
This course is an introduction to two statisticalsoftware packages, SAS and R, which are often used in professional practice. Some comparisons with other statisticalsoftware packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; builtin functions; creation of new functions or macros; graphics; matrices and arrays; simulations; select statistical applications.

3 
STAT631 
Foundations of Statistics
This course introduces principles of probability and statistics with a strong emphasis on conceptual aspects of statistical inference. Topics include fundamentals of probability, probability distribution functions, expectation and variance, discrete and continuous distributions, sampling distributions, confidence intervals and hypothesis tests.

3 
STAT641 
Applied Linear Models  Regression
A course that studies how a response variable is related to a set of predictor variables. Regression techniques provide a foundation for the analysis of observational data and provide insight into the analysis of data from designed experiments. Topics include happenstance data versus designed experiments, simple linear regression, the matrix approach to simple and multiple linear regression, analysis of residuals, transformations, weighted least squares, polynomial models, influence diagnostics, dummy variables, selection of best linear models, nonlinear estimation, and model building.

3 
STAT642 
Applied Linear Models  ANOVA
This course introduces students to analysis of models with categorical factors, with emphasis on interpretation. Topics include the role of statistics in scientific studies, fixed and random effects, mixed models, covariates, hierarchical models, and repeated measures.

3 
Program Elective 
3  
LAS Electives 
12  
Fifth Year  
STAT790 
Capstone Thesis/Project
This course is a graduate course for students enrolled in the Thesis/Project track of the MS Applied Statistics Program. (Enrollment in this course requires permission from the Director of Graduate Programs for Applied Statistics.)

3 
Graduate Electives 
21  
Total Semester Credit Hours  147 
Please see General Education Curriculum–Liberal Arts and Sciences (LAS) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
‡ Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
Admission Requirements
Freshman Admission
For all bachelor’s degree programs, a strong performance in a college preparatory program is expected. Generally, this includes 4 years of English, 34 years of mathematics, 23 years of science, and 3 years of social studies and/or history.
Specific math and science requirements and other recommendations
 3 years of math required; precalculus recommended
Transfer Admission
Transfer course recommendations without associate degree
Courses in liberal arts, physics, math, and chemistry
Appropriate associate degree programs for transfer
AS degree in liberal arts with math/science option
Learn about admissions, cost, and financial aid
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April 12, 2018
Playful teaching style earns assistant professor two awards
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