Undergraduate Course Listing in Applied Mathematics and Statistics
AMS 102-C Elements of Statistics
The use and misuse of statistics in real life situations; basic statistical measures of central tendency and of dispersion, frequency distributions, elements of probability, binomial and normal distributions, small and large sample hypothesis testing, confidence intervals, chi square test, and regression. May not be taken by students with credit for AMS 110, 310, 311, 312; ECO 320; POL 201; PSY 201; or SOC 202. This course has been designated as a High Demand/Controlled Access (HD/CA) course. Students registering for HD/CA courses for the first time will have priority to do so.
Prerequisite: Satisfaction of entry skill in mathematics requirement (Skill 1) or satisfactory completion of D.E.C. C or SBC: QPS; Non AMS majors only
Antirequisite: May not be taken by students with credit for AMS 110 or AMS 310.
AMS 102 Webpage
AMS 103 Applied Mathematics in Modern Technology
Technologies that drive our modern world rely critically on applied mathematics. This course explores "How does it work?" for selected technologies that rely on mathematics and statistics, e.g., internet search, social networking, financial markets, online auctions, cell phones, DNA sequencing, GPS, Wii, Google maps, and more.
Prerequisite: Level 3 or higher on the mathematics placement examination; SBC: QPS, TECH
AMS 103 Webpage
AMS 104 Introduction to Spreadsheets
Spreadsheets are a critically important tool in many careers, particularly in quantitative fields. This course explores how to use spreadsheets and how to use them to model real-world situations, such as project management, optimization, budgeting, finance, and more.
AMS 104 Webpage
AMS 110 Probability and Statistics in the Life Sciences
A survey of probability theory and statistical techniques with applications to biological and biomedical situations. Topics covered include Markov chain models; binomial, Poisson, normal, exponential, and chi square random variables; tests of hypotheses; confidence intervals; t tests; and analysis of variance, regression, and contingency tables. May not be taken for credit in addition to AMS 310. This course has been designated as a High Demand/Controlled Access (HD/CA) course. Students registering for HD/CA courses for the first time will have priority to do so. SBC: QPS
Prerequisite: AMS 151 or MAT 125 or 131 or 141.
Antirequisite: May not be taken by students with credit for AMS 102 or AMS 310
AMS 110 Webpage
AMS 151 Applied Calculus I
A review of functions and their applications; analytic methods of differentiation; interpretations and applications of differentiation; introduction to integration. Intended for CEAS majors. Not for credit in addition to MAT 125 or 126 or 131 or 141. This course has been designated as a High Demand/Controlled Access (HD/CA) course. Students registering for HD/CA courses for the first time will have priority to do so.
Prerequisite: B or higher in MAT 123, or level 5 on the mathematics placement examination. DEC: C or SBC: QPS
AMS 151 Webpage
AMS 161 Applied Calculus II
Analytic and numerical methods of integration; interpretations and applications of integration; differential equations models and elementary solution techniques; phase planes; Taylor series and Fourier series. Intended for CEAS majors. Not for credit in addition to MAT 126 or 127 or 132 or 142. This course has been designated as a High Demand/Controlled Access (HD/CA) course. Students registering for HD/CA courses for the first time will have priority to do so.
Prerequisite: C or higher in AMS 151 or MAT 131 or 141, or level 7 on the mathematics placement examination. DEC: C or SBC: QPS
AMS 161 Webpage
AMS 210 Applied Linear Algebra
An introduction to the theory and use of vectors and matrices. Matrix theory including systems of linear equations. Theory of Euclidean and abstract vector spaces. Eigenvectors and eigenvalues. Linear transformations. May not be taken for credit in addition to MAT 211. SBC: STEM+
Prerequisite: AMS 151 or MAT 131 or 141, or corequisite MAT 126 or level 7 or higher on the MPE
AMS 210 Webpage
AMS 261 Applied Calculus III
Vector algebra and analytic geometry in two and three dimensions; multivariable differential calculus and tangent planes; multivariable integral calculus; optimization and Lagrange multipliers; vector calculus including GreenÕs and StokesÕs theorems. May not be taken for credit in addition to MAT 203 or 205.
Prerequisite: AMS 161 or MAT 127 or 132 or 142 or MPE level 9. SBC: STEM+
AMS 261 Webpage
AMS 300 Writing in Applied Mathematics
See Requirements for the Major in Applied Mathematics and Statistics, Upper Division Writing Requirement.
Prerequisites: WRT 102; AMS major; U3 or U4 standing. SBC: SPK, WRTD
1 credit, S/U grading
AMS 300 Webpage
AMS 301 Finite Mathematical Structures
An introduction to graph theory and combinatorial analysis. The emphasis is on solving applied problems rather than on theorems and proofs. Techniques used in problem solving include generating functions, recurrence relations, and network flows. This course develops the type of mathematical thinking that is fundamental to computer science and operations research. SBC: STEM+
Prerequisite: AMS 210 or MAT 211 or AMS 361 or MAT 303.
AMS 301 Webpage
AMS 303 Graph Theory
Paths and circuits, trees and tree based algorithms, graph coloring, digraphs, network flows, matching theory, matroids, and games with graphs.
Prerequisite: AMS 301
AMS 303 Webpage
AMS 310 Survey of Probability and Statistics
A survey of data analysis, probability theory, and statistics. Stem and leaf displays, box plots, schematic plots, fitting straight line relationships, discrete and continuous probability distributions, conditional distributions, binomial distribution, normal and t distributions, confidence intervals, and significance tests. May not be taken for credit in addition to ECO 320. SBC: STEM+
Prerequisite: AMS 161 or MAT 127, 132, 142.
AMS 310 Webpage
AMS 311 Probability Theory
Probability spaces, random variables, moment generating functions, algebra of expectations, conditional and marginal distributions, multivariate distributions, order statistics, law of large numbers.
Prerequisites: AMS 301 and 310 or permission of instructor Corequisites: MAT 203 or 205 or AMS 261.
AMS 311 Webpage
AMS 315 Data Analysis
A continuation of AMS 310 that covers two sample t-tests, contingency table methods, the one-way analysis of variance, and regression analysis with one and multiple independent variables. Student projects analyze data provided by the instructor and require the use of a statistical computing package such as SAS or SPSS. An introduction to ethical and professional standards of conduct for statisticians will be provided.
Prerequisite: AMS 310
AMS 315 Webpage
AMS 316 Introduction to Time Series Analysis
Trend and seasonal components of time series models, autoregressive and moving average (ARMA) models, Box-Jenkins methodology, Portmanteau test, unit-root, generalized autoregressive conditionally heteroskedasticity (GARCH) models, exponential GARCH, stochastic volatility models. This course is offered as both AMS 316 and AMS 586.
Prerequisites: AMS 311 and 315
AMS 316 Webpage
AMS 317 Introduction to Linear Regression Analysis
Basic inference procedures and linear regression, model adequacy checking, transformations and weighted least squares, handling with influential observations and outliers, polynomial regression modeling, use of indicator variables, multicollinearity, variable selection, introduction of logistic regression, conventional and less common uses of linear regression in today's cutting-edge scientific research. Understanding of the basic principles for applied regression model-building techniques in various fields of study, including engineering, management and the health sciences.
Prerequisite: AMS 315
AMS 317 Webpage
AMS 318 Financial Mathematics
This course will focus on accumulation functions, yield rates, annuities, loan repayment, term structure of interest rates/spot rates/forward rates, options, duration/convexity. This course follows the syllabus for the Financial Mathematics (FM) Exam of the Society of Actuaries and prepares students to pass the FM Exam.
Prerequisite: AMS 310
AMS 318 Webpage
AMS 320 Introduction to Quantitative Finance
The course introduces the main classes of financial securities, the mathematical tools employed to model their prices, and common models for risk and investment management. Building realistic models relies on having a working knowledge of the empirical properties of financial asset returns which is another focus of the course. R is used as an environment for modeling.
Prerequisite: AMS 311
AMS 320 Webpage
AMS 325 Computer and Programming Fundamentals
Introduction to programming in MATLAB and Python, including scripting, basic data structures, algorithms, scientific computing, and software engineering. Homework projects will focus on using computation to solve linear algebra, data analysis, and other mathematical problems.
Prerequisite: AMS 210 or MAT 211; AMS Major
AMS 325 Webpage
AMS 326 Numerical Analysis
Direct and indirect methods for the solution of linear and nonlinear equations. Computation of eigenvalues and eigenvectors of matrices. Quadrature, differentiation, and curve fitting. Numerical solution of ordinary and partial differential equations.
Prerequisites: CSE 101; AMS 161; basic skills in using a high-level programming language (C, C++, or Java.)
Advisory prerequisite: AMS 210 or MAT 211
AMS 326 Webpage
AMS 332 Computational Modeling of Physiological Systems
Introduces students to the fundamental principles underlying computational modeling
of complex physiological systems. A major focus of the course will be on the process
by which a model of a biological system is developed. Students will be introduced
to the mathematical methods required for the modeling of complex systems (including
stochastic processes and both temporal and spatial dynamics) as well as to tools for
computational simulation. Roughly one half of the class will focus on models for general
cellular physiology, while the remaining half will focus on the development of higher-level
models of a particular physiological system (for example, the neurobiological systems
underlying learning). This course is offered as both AMS 332 and BIO 332 and is intended
for STEM majors who have already completed the foundational courses in their major.
Students who satisfy the pre-requisites but do not have a deeper background in some
STEM field may find the class very challenging and should ask the instructor for guidance
Prerequisites: MAT 127 or MAT 132 or higher and any one of the following: BIO 202 or BIO 203 or CHE 132 or CHE 331 or PHY 127 or PHY 132
AMS 332 Webpage
AMS 333 Computational Biology
This course introduces the use of mathematics and computer simulation to study a wide range of problems in biology. Topics include the modeling of populations, the dynamics of signal transduction and gene-regulatory networks, and simulation of protein structure and dynamics. A computer laboratory component allows students to apply their knowledge to real-world problems.
Prerequisites: AMS 161 or MAT 132; U3 or U4 standing; or permission of the instructor.
AMS 333 Webpage
AMS 335 Game Theory
Introduction to game theory fundamentals with special emphasis on problems from economics and political science. Topics include strategic games and Nash equilibrium, games in coalitional form and the core, bargaining theory, measuring power in voting systems, problems of fair division, and optimal and stable matching. This course is offered as both AMS 335 and ECO 355.
Prerequisites: MAT 126 or 131 or 141 or AMS 151; C or higher in ECO 303
AMS 335 Webpage
AMS 341 Operations Research I: Deterministic Models
Linear programming with a view toward its uses in economics and systems analysis. Linear algebra and geometric foundations of linear programming; simplex method and its variations; primal dual programs; formulation and interpretation of linear programming models, including practical problems in transportation and production control. Optional computer projects. AMS 341 and 342 may be taken in either order, though it is recommended that AMS 341 be taken first.
Prerequisites: AMS 210 or MAT 211
AMS 341 Webpage
AMS 342 Operations Research II: Stochastic Models
Methods and techniques for stochastic modeling and optimization, with applications to queueing theory, Markov chains, inventory theory, games, and decisions. AMS 341 and 342 may be taken in either order, though it is recommended that AMS 341 be taken first.
Prerequisites: AMS 210 or MAT 211; AMS 311
AMS 342 Webpage
AMS 345 Computational Geometry
The design and analysis of efficient algorithms to solve geometric problems that arise in computer graphics, robotics, geographical information systems, manufacturing, and optimization. Topics include convex hulls, triangulation, Voronoi diagrams, visibility, intersection, robot motion planning, and arrangements. This course is offered as both AMS 345 and CSE 355.
Prerequisites: AMS 301; programming knowledge of C or C++ or Java.
AMS 345 Webpage
AMS 351 Applied Algebra
Topics in algebra: groups, informal set theory, relations, homomorphisms. Applications: error correcting codes, BurnsideÕs theorem, computational complexity, Chinese remainder theorem. This course is offered as both AMS 351 and MAT 312
Prerequisite: AMS 210 or MAT 211
Advisory Prerequisite: MAT 200 or CSE 150 or CSE 215 or equivalent
AMS 351 Webpage
AMS 361 Applied Calculus IV: Differential Equations
Homogeneous and inhomogeneous linear differential equations; systems of linear differential equations; solution with power series and Laplace transforms; partial differential equations and Fourier series. May not be taken for credit in addition to the equivalent MAT 303.
Prerequisite: AMS 161 or MAT 127 or 132 or 142 or MPE level 9.
AMS 361 Webpage
AMS 380 Data Mining
This course will teach the basic ingredients of classical and contemporary statistical data mining methods including dimension reduction, variable selection, pattern recognition, and predictive modeling using traditional general linear models and generalized linear models, and modern statistical learning methods such as classification and regression tree, random forest, neural networks, etc. We will also teach how to run these procedures with the statistical programming language R.
Prerequisite: AMS 311
AMS 380 Webpage
AMS 394 Statistical Laboratory
Designed for students interested in statistics and their applications. Basic statistical techniques including sampling, design, regression, and analysis of variance are introduced. Includes the use of statistical packages such as SAS and R. Students translate realistic research problems into a statistical context and perform the analysis.
Prerequisites: AMS 310 or AMS 315
AMS 394 Webpage
AMS 410 Actuarial Mathematics
Integrates calculus and probability with risk assessment and insurance in a quantitative manner to prepare students for the first actuarial examination.
Prerequisites: AMS 261 or MAT 203 or 205; AMS 310; AMS 311 or 315.
AMS 412 Mathematical Statistics
Estimation, confidence intervals, Neyman Pearson lemma, likelihood ratio test, hypothesis testing, chi square test, regression, analysis of variance, nonparametric methods.
Prerequisite: AMS 311
AMS 412 Webpage
AMS 420 Investment Science Foundations
Focuses on fundamental principles of financial engineering and investment science
such as cash flow streams, arbitrage, risk aversion, pricing of finance instruments, interest
rate term structure, fixed income instruments duration, bond portfolio immunization,
Markowitz mean-variance portfolio theory, Capital Asset Pricing Model and fixed proportion investment strategy.
Prerequisite: Grade of B+ or higher in AMS 311
Advisory Prerequisite: AMS 341
AMS 420 Webpage
AMS 441 Business Enterprise
Explores the strategy and technology of business enterprises. Integrates the practice of engineering and quantitative methods with the operations of a business in today's globalized environment, whether in product development, financial management, or e-commerce.
Prerequisite: U3 or U4.
AMS 441 Webpage
AMS 475 and AMS 476 Undergraduate Teaching Practicum
Students assist the instructor in teaching by conducting weekly office hours, review sessions, and answering questions via electronic means. The student receives regularly scheduled supervision from the instructor. May be used as an open elective only and repeated once.
Prerequisites: A minimum GPA of 3.00 in all Stony Brook courses and demonstrated mastery of the subject at the level of "A" or "A-"; permission of department.
AMS 475 Webpage
AMS 487 Research in Applied Mathematics
An independent research project with faculty supervision. Permission to register requires a B average and the agreement of a faculty member to supervise the research. May be repeated once. Only 3 credits of research electives (AMS 487, CSE 487, MEC 499, ESE 499, ESM 499, EST 499, ISE 487) may be counted toward engineering technical elective requirements.
Prerequisites: Permission of instructor and department.
AMS 487 Webpage
AMS 492 Topics in Applied Mathematics
Treatment of an area of applied mathematics that expands upon the undergraduate curriculum. Topics may include applied mathematics, statistics, or operations research and change from semester to semester. Semester supplements to this Bulletin contain specific description when course is offered. May be repeated for credit once, as the topic changes.
Prerequisite: Permission of instructor.
AMS 492 Webpage