2020-21 Catalog

Mathematics

Mathematics is a subject of great intrinsic power and beauty. It is the universal language of science, and is essential for a clear and complete understanding of virtually all phenomena. Mathematical training prepares a student to express and analyze problems and relationships in a logical manner in a wide variety of disciplines including the physical, engineering, social, biological, and medical sciences, business, and pure mathematics itself. This is a principal reason behind the perpetual need and demand for mathematicians in education, research centers, government, and industry.

The department offers three major programs leading to the degrees of bachelor of arts with major in mathematics, bachelor of science in mathematics, and bachelor of science in statistics. It also offers several minor programs for undergraduates. Students can earn their bachelor and master of education (M.Ed.) degree in elementary education or secondary education plus Pennsylvania teacher certification in 5 years.

At the graduate level, the department offers programs leading to the degrees of master of science in mathematics, master of science in applied mathematics, master of science in statistics, doctor of philosophy in mathematics, and doctor of philosophy in applied mathematics. The department is a part of the interdisciplinary program in analytical finance.

Calculus Sequences

Many degree programs throughout the university include a mathematics requirement consisting of a sequence in calculus. The Department of Mathematics offers four calculus sequences:

MATH 021
MATH 022
MATH 023
Calculus I
and Calculus II
and Calculus III
12
MATH 031
MATH 032
MATH 033
Honors Calculus I
and Honors Calculus II
and Honors Calculus III
12
MATH 051
MATH 052
Survey of Calculus I
and Survey of Calculus II
7
MATH 081
MATH 082
Calculus with Business Applications I
and Calculus with Business and Economics Applications II
8

The MATH 021, MATH 022, MATH 023 sequence is a systematic development of calculus. Most students of mathematics, science, and engineering, will take some or all of this sequence.

As an honors sequence, the MATH 031, MATH 032, MATH 033 sequence covers essentially the same material but in greater depth and with more attention to rigor and proof. This sequence should be considered by students who have demonstrated exceptional ability in mathematics. 

The MATH 051, MATH 052 sequence is a survey of calculus. This sequence is not sufficient preparation for most subsequent mathematics courses. Students contemplating further study in mathematics should consider MATH 021, MATH 022 instead.

 MATH 081, MATH 082 sequence is a survey with business applications. This sequence is not sufficient preparation for most subsequent mathematics courses. Students contemplating further study in mathematics should consider MATH 021MATH 022 instead.

MATH 075, MATH 076 is a two-semester sequence that substitutes for MATH 021, covering the same material but at a slower pace.

The MATH 031, MATH 032, MATH 033 sequence will be accepted in place of MATH 021,MATH 022,MATH 023. MATH 021, MATH 022 will be accepted in place of MATH 051, MATH 052MATH 021 will be accepted in place of MATH 081. Credit will be awarded for only one course in each of the following groups:

Group 1
MATH 021Calculus I4
MATH 075
MATH 076
Calculus I, Part A
and Calculus I, Part B
4
MATH 031Honors Calculus I4
MATH 051Survey of Calculus I4
MATH 081Calculus with Business Applications I4
Group 2
MATH 022Calculus II4
MATH 032Honors Calculus II4
MATH 052Survey of Calculus II3
MATH 082Calculus with Business and Economics Applications II4
Group 3
MATH 023Calculus III4
MATH 033Honors Calculus III4

Undergraduate Degree Programs

The Department of Mathematics offers degree programs in Mathematics and Statistics. These programs have the flexibility and versatility needed to prepare students for a wide variety of careers in government, industry, research and education.

Students in the degree programs in mathematics must satisfy three types of requirements: Core Mathematics Requirements, Advanced Mathematics Electives and General Electives. The Core Mathematics Requirement ensures a common core of knowledge appropriate for students in each program. The Advanced Mathematics Electives consist of courses with specific mathematical or statistical content chosen by the student in consultation with the major advisor to complement the student's interest and career aspirations. With these further breadth and greater depth of knowledge are achieved. The General Electives consist of additional courses chosen from among those offered by the university faculty. Students can use these electives to pursue interests beyond the major, or may use these to expand upon the basic requirements of the degree program. Students are strongly encouraged to use some of these electives to earn a minor in another discipline.

Students in the degree program in statistics must satisfy four types of requirements beyond those required by the college: Required Major Courses, Major Electives, Professional Electives and General Electives.

Each student is provided a faculty advisor to guide an individual program and supervise the selection of electives.

B.A. with a major in Mathematics

The B.A. program in mathematics emphasizes fundamental principles as well as the mastery of techniques required for the effective use of mathematics. The program provides a solid foundation for those who want to pursue a mathematically oriented career or advanced study in any mathematically oriented field.

Requirements

Calculus requirement:12
Calculus I
and Calculus II
and Calculus III
Core Requirements15
MATH 163Introduction to Mathematical Reasoning3
MATH 242Linear Algebra3-4
MATH 243Algebra3,4
MATH 301Principles of Analysis I3-4
Advanced Mathematics Electives15-20
At least five courses (minimum of 15 credits) from the approved list; at least one of these must be at the 300 level; at most one course may be taken outside the department; chosen in consultation with major advisor.
Total Credits42-47

The Writing Intensive requirement is achieved by MATH 243 and MATH 301.

A student must achieve an average of 2.0 or higher in major courses.

B.S. in Mathematics

The BS in Mathematics program provides a more extensive and intensive study of mathematics and its applications. This program is especially recommended for students intending to pursue advanced study in mathematics, applied mathematics, or closely related fields. 

Requirements

Calculus Requirement12
Calculus I
and Calculus II
and Calculus III
Core Requirements15
MATH 163Introduction to Mathematical Reasoning3
MATH 242Linear Algebra3-4
MATH 243Algebra3-4
MATH 301Principles of Analysis I3-4
Advanced Mathematics Electives24-32
At least eight courses (minimum of 24 credits) from the approved list; at least four of these must be at the 300 level; at most two courses may be taken outside the department; chosen in consultation with major advisor.
Two approved(*) CSE courses. (CSE 1 and CSE 2 together are NOT sufficient to satisfy this requirement.)5-6
(*)Computer sciences courses must include a programming component. The CSE requirement is waived for students with a minor in Computer Science.
Total Credits56-65

The Writing Intensive requirement is achieved by MATH 243 and MATH 301.

A student must achieve an average of 2.0 or higher in major courses.

List of approved Advanced Mathematics electives:

The list of Advanced Mathematics electives (ADV List) consists of the following courses:

  • MATH 208, MATH 229, MATH 230, MATH 234, MATH 252, MATH 263, MATH 264;
  • All 300 level courses offered by the Mathematics Department except MATH 301 (required core course), MATH 371 (see below) and MATH 391 (see below);
  • Notes:
    • Together, MATH 202 and MATH 203 (as a three credit combination), is accepted as one  Advanced Mathematics elective;
    • With prior approval, one  Advanced Mathematics elective (3 credits) may be replaced with three credits of (a combination of) MATH 271(Readings), MATH 371(Readings), MATH 291(Undergraduate Research) or MATH 391(Senior Thesis) completed over one or two semesters;
    • All 400 level courses are accepted as Advanced Mathematics electives.  (Note.  To enroll in a 400 level course, an undergraduate must successfully petition the appropriate university committee.)

Suggested Concentrations:

Applied Mathematical Modeling Concentration: This concentration should be considered by students interested in graduate study in applied mathematics or computational mathematics.  The eight Advanced Mathematics electives are selected in consultation with a major advisor and must include the following:

  • MATH 230
  • MATH 319
  • At least two courses selected from: MATH 320, MATH 322, MATH 323, MATH 341
  • At least two additional courses selected from:
    • MATH 202/203, MATH 208, MATH 263, MATH 264, MATH 252
    • MATH 305, MATH 306, MATH 309, MATH 310, MATH 311, MATH 312, MATH 320, MATH 322, MATH 323, MATH 334, MATH 338, MATH 340, MATH 341, MATH 343
  • At least two additional courses selected from the list of approved Advanced Mathematics Electives (see ADV List below)
  • At least four of these courses must be at the 300 level.

Probability and Statistics Concentration: This concentration should be considered by students interested in actuarial science.  The eight Advanced Mathematics electives are selected in consultation with a major advisor and must include the following:

  • MATH 263
  • MATH 264
  • At least two courses selected from: MATH 310, MATH 312, MATH 334, MATH 338
  • At least two additional courses selected from:
    • MATH 202/203, MATH 208, MATH 252,
    • MATH 305, MATH 306, MATH 309, MATH 310, MATH 311, MATH 312, MATH 320, MATH 322, MATH 323, MATH 334, MATH 338, MATH 340, MATH 341, MATH 343
  • At least two additional courses selected from the list of approved Advanced Mathematics Electives (see ADV List below)
  • At least four of these courses must be at the 300 level.

Theoretical Mathematics Concentration: This concentration should be considered by students interested in graduate study in mathematics or applied mathematics.  The eight Advanced Mathematics electives are selected in consultation with a major advisor and must include the following:

  • MATH 327
  • MATH 302 or MATH 316
  • At least two additional courses selected from: MATH 302, MATH 305, MATH 307, MATH 311, MATH 316, MATH 319, MATH 331, MATH 342
  • At least four additional courses selected, in consultation with the major advisor, from the list of approved Advanced Mathematics Electives (see ADV List below)
  • At least four of these courses must be at the 300 level.

Other concentration: Students, in consultation with the major advisor, may design their own concentration by selecting a coherent list of eight Advanced Mathematics electives from the list of approved courses (see ADV List above).  For instance, this option should be considered by students with an interest in data science, computer science, or mathematical economics.

 B.S. in Statistics

Statistics provides a body of principles for designing the process of data collection, for summarizing and interpreting data, and for drawing valid conclusions from data. It thus forms a fundamental tool in the natural and social sciences as well as business, medicine, and other areas of research. Mathematical principles, especially probability theory, underlie all statistical analyses.

 The BS in Statistics program offers two tracks: the standard track and the applied track.

STANDARD TRACK

Required Major courses
MATH 021
MATH 022
MATH 023
Calculus I
and Calculus II
and Calculus III
12
MATH 264Introduction to Statistical Reasoning and Methods4
Select one of the following (+):3-4
Linear Methods
Applied Linear Algebra
Linear Algebra
(+) MATH 241 is recommended. For students who may need more preparation, MATH 205 can be used as a major elective.
MATH 263Introduction to the Theory of Probability3
or MATH 309 Probability with Applications and Simulations
MATH 310Random Processes and Applications3-4
MATH 312Statistical Computing and Applications3-4
MATH 334Mathematical Statistics3-4
MATH 338Linear Models in Statistics with Applications3-4
MATH 365Statistical Machine Learning3-4
MATH 374Statistical Project3
Two approved (*) CSE courses. (CSE 1 and CSE 2 together are NOT sufficient to satisfy this requirement.)5-7
(*) Computer sciences courses must include a programming component. The CSE requirement is waived for students with a minor in Computer Science.
Major Electives
At least two courses with specific mathematical or statistical content chosen with the approval of the faculty advisor8
Professional Electives
Courses selected from two or three fields of application of statistics and probability with the approval of the faculty advisor (#)15
(#) Courses taken as part of a minor can be used as professional electives.
Total Credits68-76

The Writing Intensive requirement is achieved by MATH 374.

APPLIED TRACK

Required Major courses
MATH 021Calculus I4
MATH 022
MATH 023
Calculus II
and Calculus III
4-8
or MATH 082 Calculus with Business and Economics Applications II
MATH 264Introduction to Statistical Reasoning and Methods4
Select one of the following (+):3-4
Linear Methods
Applied Linear Algebra
Linear Algebra
(+) MATH 241 is recommended. For students who may need more preparation, MATH 205 can be used as a major elective.
MATH 309Probability with Applications and Simulations3
MATH 312Statistical Computing and Applications3-4
MATH 334Mathematical Statistics3-4
MATH 339Time Series and Forecasting3-4
MATH 365Statistical Machine Learning3-4
MATH 374Statistical Project3
Two approved (*) CSE courses. (CSE 1 and CSE 2 together are NOT sufficient to satisfy this requirement.)5-7
(*) Computer sciences courses must include a programming component. The CSE requirement is waived for students with a minor in Computer Science.
Major Electives
At least three courses with specific mathematical or statistical content chosen with the approval of the faculty advisor12
Professional Electives
Courses selected from two or three fields of application of statistics and probability with the approval of the faculty advisor (#)15
(#) Courses taken as part of a minor can be used as professional electives.
Total Credits65-76

The Writing Intensive requirement is achieved by MATH 374.

CONCENTRATION IN ACTUARIAL SCIENCE

Major Electives must include:

MATH 202Actuarial Exam I1
MATH 203Actuarial Exam II - Financial Mathematics2

Professional Electives (15 credit hours) must include at least three of these courses:

ACCT 151Introduction to Financial Accounting3
ECO 029Money, Banking, and Financial Markets3
ECO 119Intermediate Macroeconomic Analysis3
ECO 146Intermediate Microeconomic Analysis3
FIN 125Introduction to Finance3

Departmental Honors

Students may earn departmental honors by writing a thesis during their senior year. Students are accepted into the program during their junior year by the department chairperson. This acceptance is based upon the student's grades and a thesis proposal, which the student must prepare in conjunction with a thesis advisor selected by the student. An oral presentation as well as a written thesis are required for completion of the program.

Minor Programs

The department offers minor programs in different branches of the mathematical sciences. The requirement consists of a Calculus course ( MATH 023 or MATH 033 or MATH 052 or MATH 082 depending on the minor) and four additional courses shown below for each of the programs. At most one of the five courses in the minor program may also be required in the major program or another minor. For substitutions, the student should consult the chairperson.

Minor in Pure Mathematics

MATH 023Calculus III4
MATH 242Linear Algebra3-4
MATH 243Algebra3-4
MATH 301Principles of Analysis I3-4
Select one of the following:3-4
Principles of Analysis II
Mathematical Logic
General Topology I
Complex Analysis
Introduction to Differential Equations
Ordinary Differential Equations
Groups and Rings
Differential Geometry of Curves and Surfaces
Number Theory
Total Credits16-20

Minor in Applied Mathematics

MATH 023Calculus III4
MATH 341Mathematical Models and Their Formulation3
Select three of the following:9-10
Linear Methods
Complex Variables
Numerical Methods
Probability and Statistics
Applied Linear Algebra
Linear Algebra
Introduction to the Theory of Probability
Introduction to Statistical Reasoning and Methods
Introduction to Differential Equations
Ordinary Differential Equations
Methods of Applied Analysis I
Methods of Applied Analysis II
Total Credits16-17

Minor in Probability and Statistics 

MATH 023Calculus III4
or MATH 052 Survey of Calculus II
or MATH 082 Calculus with Business and Economics Applications II
MATH 263Introduction to the Theory of Probability3
or MATH 309 Probability with Applications and Simulations
Select one of the following:3-4
Basic Statistics
Probability and Statistics
Introduction to Statistical Reasoning and Methods
Select two of the following:6-8
Random Processes and Applications
Statistical Computing and Applications
Mathematical Statistics
Linear Models in Statistics with Applications
Time Series and Forecasting
Statistical Machine Learning
Total Credits16-19

Minor in Actuarial Science

MATH 023Calculus III3-4
or MATH 052 Survey of Calculus II
or MATH 082 Calculus with Business and Economics Applications II
MATH 263Introduction to the Theory of Probability3
or MATH 309 Probability with Applications and Simulations
MATH 310Random Processes and Applications3-4
MATH 202Actuarial Exam I1
MATH 203Actuarial Exam II - Financial Mathematics2
Select one of the following:3
Fundamentals of Accounting
Introduction to Financial Accounting
Intermediate Macroeconomic Analysis
Intermediate Microeconomic Analysis
Total Credits15-17

For information on examinations of actuarial societies, students may consult their minor advisor.

Graduate Programs in Mathematics

The department offers graduate programs leading to the degrees of master of science in mathematics, applied mathematics, or statistics, and the doctor of philosophy in mathematics or applied mathematics.

The Department does not offer a doctorate in statistics. However, students may choose statistics or mathematical statistics as a concentration in the doctor of philosophy programs in mathematics and applied mathematics. The Department is a part of the interdisciplinary program in Analytical Finance. For details on the Master of Science in Analytical Finance see the Interdisciplinary Graduate Study and Research, Analytical Finance section.

To begin graduate work in mathematics a student must present evidence of adequate undergraduate preparation. The undergraduate program should have included a year of advanced calculus, a semester of linear algebra, and a semester of abstract algebra.

M.S. in Mathematics or Applied Mathematics

The master's program requires 30 credit hours of graduate courses with at least 18 credit hours at the 400 level. With the permission of the chairperson, up to six credit hours of these courses can be replaced by a thesis. All students in the master's program must also pass a comprehensive examination. The M.S. degree can serve both as a final degree in mathematics or as an appropriate background for the Ph.D. degree.

M.S. in Statistics

This program requires 30 credit hours of graduate courses with at least 18 hours of 400-level STAT or MATH courses. The choice of courses must be approved by the graduate advisor, and up to six hours of coursework may be replaced with a thesis. All students in the program must also pass a comprehensive examination.

The M.S. program in statistics has two tracks:

statistics track

The statistics track has recommended courses:

MATH 309Probability with Applications and Simulations3
MATH 312Statistical Computing and Applications3-4
STAT 410Random Processes and Applications3
STAT 434Mathematical Statistics3
STAT 438Linear Models In Statistics with Applications3
STAT 471Topics in Statistical Learning and Computing3
Electives
STAT 412Advanced Applied Statistics3
Select three other possible electives:9
Seminar in Statistics and Probability
Seminar in Statistics and Probability
Time Series and Forecasting
Topics In Mathematical Statistics
Statistical Machine Learning
Statistical Practice
Modern Nonparametric Methods in Statistics
Product Quality
Time Series Analysis
Design of Experiments
Time Series Analysis
Topics in Game Theory
Fundamentals of Machine Learning
Introduction to Machine Learning
Data Mining
Applied Data Mining
Total Credits30-31

stochastic modeling track

The stochastic modeling track has recommended courses:

MATH 309Probability with Applications and Simulations3
MATH 401Real Analysis I3
STAT 410Random Processes and Applications3
STAT 463Advanced Probability3
Electives
MATH 341Mathematical Models and Their Formulation3
STAT 434Mathematical Statistics3
STAT 438Linear Models In Statistics with Applications3
STAT 464Advanced Stochastic Processes3
Select two other possible electives:
Seminar in Statistics and Probability
Seminar in Statistics and Probability
Time Series and Forecasting
Statistical Machine Learning
Topics in Statistical Learning and Computing
Statistical Practice
Real Analysis II
Numerical Analysis
Stochastic Calculus
Financial Stochastic Analysis
Topics in Game Theory
Advanced Programming Techniques
Nondeterministic Models in Engineering
Optimization Models and Applications
Stochastic Models and Applications
Time Series Analysis
Dynamic Programming
Queueing Systems

Ph.D. in Mathematics

The plan of work toward the doctor of philosophy degree will include a comprehensive examination, a qualifying examination, and an advanced topic examination. A language exam may be required at the discretion of the doctoral committee. The qualifying examination tests the student’s command of algebra and real analysis. The content of the advanced topic examination is determined by a department committee. A general examination, the doctoral dissertation and its defense complete the work for the Ph.D. degree.

Each candidate's plan of work must be approved by a special committee of the department. A Ph.D. student is required to have 18 credits of approved graduate level course work beyond the master's level. Successful completion of MATH 316 and MATH 307 is required of all students. After completion of 18 credits a student is required to take at least one course per academic year other than MATH 409 and MATH 499.

Ph.D. in Applied Mathematics

The plan of work toward the doctor of philosophy degree will include a comprehensive examination, a qualifying examination, and an advanced topic examination. A language examination may be required at the discretion of the doctoral committee. The Ph.D. in Applied Mathematics qualifying examination tests the student's command of Statistics and Applied Probability or of Real Analysis and Differential Equations. The content of the advanced topic examination is determined by a department committee. A general examination, the doctoral dissertation and its defense complete the work for the Ph.D. degree.

Each candidate's plan of work must be approved by a special committee of the department. A Ph.D. student is required to have 18 credits of approved graduate level course work beyond the master's level. After completion of 18 credits a student is required to take at least one course per academic year other than MATH 409 and MATH 499.

Mathematics Courses

MATH 000 Preparation for Calculus 2 Credits

Intensive review of fundamental concepts in mathematics utilized in calculus, including functions and graphs, exponentials and logarithms, and trigonometry. This course is for students who need to take MATH 51, 81, or 21, but who require additional preparation in precalculus. The credits for this course do not count toward graduation, but do count toward GPA and current credit count. Consent of department.
Attribute/Distribution: MA

MATH 005 Introduction to Mathematical Thought 3 Credits

Meaning, content, and methods of mathematical thought illustrated by topics that may be chosen from number theory, abstract algebra, combinatorics, finite or nonEuclidean geometries, game theory, mathematical logic, set theory, topology.
Attribute/Distribution: MA

MATH 009 Introduction to Finite Mathematics 4 Credits

Systems of linear equations, matrices, introduction to linear programming. Sets, counting methods, probability, random variables, introduction to Markov chains.
Attribute/Distribution: MA

MATH 012 Basic Statistics 4 Credits

A first course in the basic concepts and methods of statistics with illustrations from the social, behavioral, and biological sciences. Descriptive statistics; frequency distributions, mean and standard deviation, two-way tables, correlation and regression; random sampling, rules of probability, probability distributions and parameters, parameter estimation, confidence intervals, hypothesis testing, statistical significance. Note: Mathematics and Statistics majors may not receive credit for both MATH 012 & ECO 045.
Attribute/Distribution: MA

MATH 021 Calculus I 4 Credits

Functions and graphs; limits and continuity; derivative, differential, and applications; indefinite and definite integrals; trigonometric, logarithmic, exponential, and hyperbolic functions.
Attribute/Distribution: MA

MATH 022 Calculus II 4 Credits

Applications of integration; techniques of integration; separable differential equations; infinite sequences and series; Taylor's Theorem and other approximations; curves and vectors in the plane.
Prerequisites: MATH 021 or MATH 076
Attribute/Distribution: MA

MATH 023 Calculus III 4 Credits

Vectors in space; partial derivatives; Lagrange multipliers; multiple integrals; vector analysis; line integrals; Green's Theorem, Gauss's Theorem.
Prerequisites: MATH 022
Attribute/Distribution: MA

MATH 031 Honors Calculus I 4 Credits

Same topics as in MATH 021, but taught from a more thorough and rigorous point of view.
Attribute/Distribution: MA

MATH 032 Honors Calculus II 4 Credits

Same topics as in MATH 022, but taught from a more thorough and rigorous point of view.
Prerequisites: MATH 031 or MATH 021
Attribute/Distribution: MA

MATH 033 Honors Calculus III 4 Credits

Same topics as in MATH 023, but taught from a more thorough and rigorous point of view.
Prerequisites: MATH 022 or MATH 032
Attribute/Distribution: MA

MATH 043 Survey of Linear Algebra 3 Credits

Matrices, vectors, vector spaces and mathematical systems, special kinds of matrices, elementary matrix transformations, systems of linear equations, convex sets, introduction to linear programming.
Attribute/Distribution: MA

MATH 051 Survey of Calculus I 4 Credits

Limits. The derivative and applications to extrema, approximation, and related rates. Exponential and logarithm functions, growth and decay. Integration. Trigonometric functions and related derivatives and integrals.
Attribute/Distribution: MA

MATH 052 Survey of Calculus II 3 Credits

Techniques of integration. Differential equations. Probability and calculus. Partial derivatives and extrema. Multiple integrals and applications.
Prerequisites: MATH 051 or MATH 021 or MATH 076 or MATH 081
Attribute/Distribution: MA

MATH 075 Calculus I, Part A 2 Credits

Covers the same material as the first half of MATH 021. Meets three hours per week, allowing more class time for each topic than does MATH 021.
Attribute/Distribution: MA

MATH 076 Calculus I, Part B 2 Credits

Continuation of MATH 075, covering the second half of MATH 021. Meets three hours per week.
Prerequisites: MATH 075
Attribute/Distribution: MA

MATH 081 Calculus with Business Applications I 4 Credits

Limits and continuity; exponential, logarithmic and trigonometric functions; derivatives; extrema; approximations; indefinite and definite integrals. Applications with emphasis on business and economics.
Attribute/Distribution: MA

MATH 082 Calculus with Business and Economics Applications II 4 Credits

Integration by parts, Riemann sums; differential equations; series; Taylor series. Vectors, inner products and projections; functions of several variables, partial derivatives. Multiple integrals; vector-valued functions. Applications with emphasis on finance and economics.
Prerequisites: MATH 081 or MATH 021 or MATH 076 or MATH 051
Attribute/Distribution: MA

MATH 114 (PHIL 114) Symbolic Logic 4 Credits

A first course in logical theory, introducing the notions of logical consequence and proof, as well as related concepts such as consistency and contigency. Formal systems taught may include: term, sentence logic, and predicate logic.
Attribute/Distribution: MA

MATH 130 (BIOS 130) Biostatistics 4 Credits

Elements of statistics and probability with emphasis on biological applications. Statistical analysis of experimental and observational data.
Prerequisites: MATH 052 or MATH 022

MATH 163 Introduction to Mathematical Reasoning 3 Credits

An introduction to the discipline of mathematics for students considering a major in mathematics. Provides an introduction to rigorous mathematical reasoning, including basic proof techniques (e.g., basic propositional calculus, induction, contradiction) and key concepts which recur throughout mathematics (e.g., universal and existential quantifiers, equivalence classes, basic set theory). Students majoring in mathematics should complete this course before MATH 242, MATH 243 or MATH 301 and are encouraged to complete this course in the first or second year of study.
Prerequisites: MATH 021

MATH 171 Readings 1-3 Credits

Study of a topic in mathematics under individual supervision. Intended for students with specific interests in areas not covered in the listed courses. Consent of department chair required.
Attribute/Distribution: MA

MATH 201 Problem Solving 1 Credit

Practice in solving challenging mathematics problems using a variety of techniques. Permission of instructor required.
Repeat Status: Course may be repeated.
Attribute/Distribution: MA

MATH 202 Actuarial Exam I 1 Credit

Preparation for the first actuarial exam – probability. Problems in calculus and probability with insurance applications.
Prerequisites: (MATH 023 or MATH 052 or MATH 082) and (MATH 231 or MATH 263)

MATH 203 Actuarial Exam II - Financial Mathematics 2 Credits

Preparation for the second actuarial exam - financial mathematics. Mathematics of interest and investments, interest rate measurement, present value, annuities, loan repayment schemes, bond valuation, introduction to derivative securities. Practice in solving problems from past exams.
Prerequisites: MATH 022 or MATH 082
Attribute/Distribution: MA

MATH 205 Linear Methods 3 Credits

Linear differential equations and applications; matrices and systems of linear equations; vector spaces; eigenvalues and application to linear systems of differential equations.
Prerequisites: MATH 022

MATH 208 Complex Variables 3 Credits

Functions of a complex variable; calculus of residues; contour integration; applications to conformal mapping and Laplace transforms.
Prerequisites: MATH 023

MATH 214 (PHIL 214) Topics in Philosophical Logic 4 Credits

Topics may include the many systems of non-classical logic, truth theory, the impact of incompleteness and undecidability results on philosophy, the foundational projects of various philosopher/mathematicians, or the work of an important figure in the history of philosophical logic. Consent of instructor required.
Repeat Status: Course may be repeated.
Attribute/Distribution: MA

MATH 229 Geometry 3-4 Credits

Discussion of geometry as an axiomatic system. Euclid's postulates. History of and equivalent versions of Euclid's fifth postulate. Finite projective geometries. NonEuclidean geometries based upon negation of the fifth postulate: Geometry on the sphere; Hyperbolic and elliptic geometries. Examination of the concepts of “straight”, angle, parallel, symmetry and duality in each of these geometries. Applications of the different geometries will be considered.
Attribute/Distribution: MA

MATH 230 Numerical Methods 3 Credits

Representation of numbers and rounding error; polynomial and spline interpolation; numerical differentiation and integration; numerical solution of nonlinear systems; numerical solution of initial and boundary value problems; Monte Carlo methods. Knowledge of MATLAB or PYTHON or C required.
Prerequisites: MATH 205 or MATH 241 or MATH 242

MATH 231 Probability and Statistics 3 Credits

Probability and distribution of random variables; populations and random sampling; chi-square and t distributions; estimation and tests of hypotheses; correlation and regression theory of two variables. Not available for credit to students who have completed both MATH 263 and MATH 264.
Prerequisites: MATH 022 or MATH 052 or MATH 082

MATH 234 Fractal Geometry 3 Credits

Metric spaces and iterated function systems; various types of fractal dimension; Julia and Mandelbrot sets. Other topics such as chaos may be included. Small amount of computer use.
Prerequisites: MATH 023

MATH 241 Applied Linear Algebra 3,4 Credits

The theoretical basis for applying linear algebra in other fields, including statistics. Topics will include systems of equations, vector spaces, matrices, and linear transformations. Additional topics will include matrix factorizations (including LU, QR, eigen-decomposition, and SVD) and how they can be used in computer analysis of data sets. Some students may optionally choose to take MATH 205 as preparation for this course. Not available for credit to students who have completed MATH 242 or STAT 342.
Prerequisites: MATH 022 or MATH 082

MATH 242 Linear Algebra 3-4 Credits

An introduction to the study of vector spaces and linear transformations, with emphasis on mathematical rigor. Not available for credit to students who have completed MATH 241 / STAT 342.
Prerequisites: MATH 022 and MATH 163

MATH 243 Algebra 3,4 Credits

Introduction to basic concepts of modern algebra: groups, rings, and fields.
Prerequisites: MATH 242

MATH 252 Introduction to Combinatorics and Graph Theory 3 Credits

Topics in combinatorics and graph theory chosen to introduce the subjects and some of their common proof techniques. Sequences and recursive formulas; counting formulas; bijections; inclusion/exclusion; the Pigeonhole Principle; generating functions; equivalence relations. Graph theory topics include trees, connectivity, traversability, matching and coloring. Not available for credit to students who have completed MATH 305.
Prerequisites: MATH 022

MATH 261 (CSE 261) Discrete Structures 3 Credits

Topics in discrete mathematical structures chosen for their applicability to computer science and engineering. Sets, propositions, induction, recursion; combinatorics; binary relations and functions; ordering, lattices and Boolean algebra; graphs and trees; groups and homomorphisms.
Prerequisites: MATH 021 or MATH 076

MATH 263 Introduction to the Theory of Probability 3 Credits

An introduction to the basics of Calculus-based theory of Probability. Includes combinatorial techniques, events, independence, and conditional probability; most important discrete and continuous probability distributions, expectation and variance; joint distributions and covariance; moment generating functions; basic form of the Laws of Large Numbers and the Central Limit Theorem. Focuses on use of concepts to solve problems. Prior knowledge of Probability not required. Not available for credit to students who have completed (MATH 231 and MATH 264) or MATH 309.
Prerequisites: MATH 023 or MATH 052 or MATH 082
Can be taken Concurrently: MATH 023

MATH 264 Introduction to Statistical Reasoning and Methods 4 Credits

Introduction to the basic concepts, logic and issues involved in statistical reasoning and statistical methods used to analyze data and evaluate studies. Topics include descriptive statistics and exploratory data analysis; elementary probability and statistical inference. Examples drawn from various areas of application. Use of computer software (e.g., Minitab, R) to facilitate understanding and to complete data analysis. Three lectures and one computer laboratory. Not available for credit to students who have completed both MATH 231 and MATH 263.
Prerequisites: MATH 021 or MATH 051 or MATH 081

MATH 271 Readings 1-3 Credits

Study of a topic in mathematics under individual supervision. Intended for students with specific interests in areas not covered in the listed courses. Consent of department chair required.
Repeat Status: Course may be repeated.
Attribute/Distribution: MA

MATH 291 Undergraduate Research 1-4 Credits

Research in mathematics or statistics under the direction of a faculty member. Department permission required.
Repeat Status: Course may be repeated.
Attribute/Distribution: ND

MATH 300 Apprentice Teaching 1-4 Credits

Repeat Status: Course may be repeated.

MATH 301 Principles of Analysis I 3-4 Credits

Existence of limits, continuity and uniform continuity; HeineBorel Theorem; existence of extreme values; mean value theorem and applications; conditions for the existence of the Riemann integral; absolute and uniform convergence; emphasis on theoretical material from the calculus of one variable.
Prerequisites: MATH 023

MATH 302 Principles of Analysis II 3-4 Credits

Continuation of MATH 301. Functions of several variables; the implicit function theorem, and further topics with applications to analysis and geometry.
Prerequisites: MATH 301
Attribute/Distribution: MA

MATH 303 (PHIL 303) Mathematical Logic 3-4 Credits

Detailed proofs are given for the basic mathematical results relating the syntax and semantics of firstorder logic (predicate logic): the Soundness and Completeness (and Compactness) Theorems, followed by a brief exposition of the celebrated limitative results of Gödel, Turing, and Church on incompleteness and undecidability. The material is conceptually rigorous and mathematically mature; the necessary background is a certain degree of mathematical sophistication or a basic knowledge of symbolic logic. Consent of instructor required.
Attribute/Distribution: MA

MATH 304 Axiomatic Set Theory 3-4 Credits

A development of set theory from axioms; relations and functions; ordinal and cardinal arithmetic; recursion theorem; axiom of choice; independence questions. Consent of instructor required.
Attribute/Distribution: MA

MATH 305 Enumerative Combinatorics 3 Credits

An introduction to basic theoretical results and techniques of enumerative combinatorics such as combinatorial identities, generating functions, inclusion/exclusion, recurrence relations, bijective proofs and permutations. Additional topics will be covered as time permits.
Prerequisites: MATH 242

MATH 307 General Topology I 3-4 Credits

An introductory study of topological spaces, including metric spaces, separation and countability axioms, connectedness, compactness, product spaces, quotient spaces, function spaces.
Prerequisites: MATH 301
Attribute/Distribution: MA

MATH 309 Probability with Applications and Simulations 3 Credits

Foundations of Probability; Random Variables; Probability Models; Expectations and Moment Generating Functions; Joint and Conditional Distributions; Functions of Random Variables. Introduction to fundamental ideas and techniques of stochastic modeling, with an emphasis on the applications. The last part of the course is devoted to techniques and methods of Monte Carlo simulation. R or other software will be used in this course.
Prerequisites: MATH 023 or MATH 052 or MATH 082

MATH 310 Random Processes and Applications 3-4 Credits

Theory and applications of stochastic processes. Limit theorems, introduction to random walks, Markov chains, Poisson processes, birth and death processes, and Brownian motion. Applications to financial mathematics, biology, business and engineering.
Prerequisites: MATH 263 or MATH 309 or (MATH 231 and (MATH 205 or MATH 241), )

MATH 311 Graph Theory 3 Credits

An introduction to basic theoretical results and techniques of graph theory such as trees, connectivity, matchings, coloring, planar graphs and Hamiltonicity. Additional topics will be covered as time permits.
Prerequisites: MATH 163 or MATH 252 or CSE 140

MATH 312 Statistical Computing and Applications 3,4 Credits

Use of statistical computing packages; exploratory data analysis; Monte Carlo methods; randomization and resampling, application and interpretation of a variety of statistical methods in real world problems.
Prerequisites: MATH 012 or MATH 231 or MATH 264 or ECO 045

MATH 316 Complex Analysis 3-4 Credits

Concept of analytic function from the points of view of the CauchyRiemann equations, power series, complex integration, and conformal mapping.
Prerequisites: MATH 301
Attribute/Distribution: MA

MATH 319 Introduction to Differential Equations 3 Credits

An introductory, yet rigorous treatment of topics in differential equations chosen to prepare students for advanced work in mathematics or applied mathematics. Homogeneous and non-homogeneous linear differential equations, existence and uniqueness theorems, Gronwall's inequality; systems of first order linear differential equations; autonomous first-order systems: critical points, stability, bifurcation; series and periodic solutions, Fourier series and their convergence; introduction to numerical simulation methods.
Prerequisites: MATH 242 or MATH 205 or MATH 241

MATH 320 Ordinary Differential Equations 3-4 Credits

The analytical and geometric theory of ordinary differential equations, including such topics as linear systems, systems in the complex plane, oscillation theory, stability theory, geometric theory of nonlinear systems, finite difference methods, general dynamical systems.
Prerequisites: MATH 023 and (MATH 205 or MATH 319)

MATH 321 Topics in Discrete Mathematics 3 Credits

Selected topics in areas of discrete mathematics. Consent of department chair required.
Repeat Status: Course may be repeated.
Attribute/Distribution: MA

MATH 322 Methods of Applied Analysis I 3 Credits

Fourier series, eigenfunction expansions, SturmLiouville problems, Fourier integrals and their application to partial differential equations; special functions. Emphasis is on a wide variety of formal applications rather than logical development.
Prerequisites: MATH 205 or MATH 319

MATH 323 Methods of Applied Analysis II 3 Credits

Green's functions; integral equations; variational methods; asymptotic expansions, method of saddle points; calculus of vector fields, exterior differential calculus.
Prerequisites: MATH 322
Attribute/Distribution: MA

MATH 327 Groups and Rings 3-4 Credits

An intensive study of the concepts of group theory including the Sylow theorems, and of ring theory including unique factorization domains and polynomial rings.
Prerequisites: MATH 242 and MATH 243
Attribute/Distribution: MA

MATH 329 Computability Theory 3-4 Credits

Core development of classical computability theory: enumeration, index and recursion theorems, various models of computation and Church's Thesis, uncomputability results, introduction to reducibilities and their degrees (in particular, Turing degrees, or degrees of uncomputability), computable operators and their fixed points.
Attribute/Distribution: MA

MATH 331 Differential Geometry of Curves and Surfaces 3 Credits

Local and global differential geometry of curves and surfaces in Euclidean 3space. Frenet formulas for curves, isoperimetric inequality, 4vertex theorem; regular surfaces, first fundamental form, Gauss map, second fundamental form; curvatures for curves and surfaces and their relations; The GaussBonnet theorem.
Prerequisites: MATH 023 and (MATH 205 or MATH 242)

MATH 334 Mathematical Statistics 3-4 Credits

Populations and random sampling; sampling distributions; theory of statistical estimation; criteria and methods of point and interval estimation; theory of testing statistical hypotheses.
Prerequisites: MATH 263 or MATH 309

MATH 338 Linear Models in Statistics with Applications 3,4 Credits

Least square principles in multiple regression and their interpretations; estimation, hypotheses testing, confidence and prediction intervals, modeling, regression diagnostic, multicollinearity, model selection, analysis of variance and covariance; logistic regression. Introduction to topics in time series analysis such as ARMA, ARCH, and GARCH models. Applications to natural sciences, finance and economics. Use of computer packages.
Prerequisites: (MATH 012 or MATH 231 or MATH 264) and (MATH 043 or MATH 205 or MATH 241 or MATH 242 or STAT 342)

MATH 339 3,4 Credits

This course introduces the student to the statistical analysis of time series data and useful models: autocorrelation, stationarity, trend removal, and seasonal adjustment, basic time series models like AR, MA, ARMA; estimation, forecasting, and GARCH models; multivariate models, and factor models. The course emphasizes the main ideas and the most popular and widely used methods, and the use of a computer to practice the methods. Knowledge of scientific programming in a language such as R required.
Prerequisites: (MATH 264 or MATH 312) and (MATH 263 or MATH 309)

MATH 340 (CSE 340) Design and Analysis of Algorithms 3 Credits

Algorithms for searching, sorting, manipulating graphs and trees, finding shortest paths and minimum spanning trees, scheduling tasks, etc.: proofs of their correctness and analysis of their asymptotic runtime and memory demands. Designing algorithms: recursion, divide-and-conquer, greediness, dynamic programming. Limits on algorithm efficiency using elementary NP-completeness theory.
Prerequisites: (MATH 021 or MATH 031 or MATH 076) and CSE 140 and CSE 017

MATH 341 Mathematical Models and Their Formulation 3 Credits

Mathematical modeling of engineering and physical systems with examples drawn from diverse disciplines. Emphasis is on building models of real world problems and the analysis as well as numerical simulations of the models.
Prerequisites: MATH 205 or MATH 241 or MATH 242

MATH 342 Number Theory 3-4 Credits

Basic concepts and results in number theory, including such topics as primes, the Euclidean algorithm, Diophantine equations, congruences, quadratic residues, quadratic reciprocity, primitive roots, number-theoretic functions, distribution of primes, Pell’s equation, Fermat’s theorem, partitions. Consent of instructor required.
Attribute/Distribution: MA

MATH 343 Introduction To Cryptography 3,4 Credits

Classical elementary cryptography: Caesar cipher, other substitution ciphers, block ciphers, general linear ciphers. Fast random encryption (DES and AES: Advanced Encryption Standard). Public key systems (RSA and discrete logs). Congruences, modular arithmetic, fast exponentiation, polynomials, matrices. Distinction between polynomial time (primality), Subexponential time (factoring) and fully Exponential computation (elliptic curves). Introduction to sieving and distributed computation. Consent of instructor required.
Attribute/Distribution: MA

MATH 350 Special Topics 3 Credits

A course covering special topics not sufficiently covered in listed courses. Consent of department chair required.
Repeat Status: Course may be repeated.
Attribute/Distribution: MA

MATH 365 Statistical Machine Learning 3,4 Credits

This course provides a broad introduction to concepts, methods, and practices of statistical machine learning: parametric and nonparametric regression, logistic regression, classification, and basic neural networks; kernel and nearest neighbor estimation, clustering, Bayesian and mixture models. In addition, we will explore selected topics like model selection, cross-validation; PCA, dimension reduction, regularized regression; trees, and ensemble learning. Knowledge of scientific programming in a language such as R required.
Prerequisites: (MATH 205 or MATH 241 or MATH 242) and (MATH 264 or MATH 312) and (MATH 263 or MATH 309)

MATH 371 Readings 1-3 Credits

The study of a topic in mathematics under appropriate supervision, designed for the individual student who has studied extensively and whose interests lie in areas not covered in the listed courses. Consent of department chair required.
Repeat Status: Course may be repeated.
Attribute/Distribution: MA

MATH 374 Statistical Project 3 Credits

Supervised field project or independent reading in statistics or probability. Consent of department chair required.
Attribute/Distribution: MA

MATH 381 Undergraduate Research 1-4 Credits

Research in mathematics or statistics under the direction of a faculty member. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 391 Senior Honors Thesis 3 Credits

Independent research under faculty supervision, culminating in a thesis presented for departmental honor. Consent of department chair required.
Repeat Status: Course may be repeated.
Attribute/Distribution: MA

MATH 401 Real Analysis I 3 Credits

Set theory, real numbers; introduction to measures, Lebesgue measure; integration, general convergence theorems; differentiation, functions of bounded variation, absolute continuity; Lp spaces.
Prerequisites: MATH 301

MATH 402 Real Analysis II 3 Credits

Metric spaces; introduction to Banach and Hilbert space theory; Fourier series and Fejer operators; general measure and integration theory, RadonNikodym and Riesz representation and theorems; LebesgueStieljtes integral.
Prerequisites: MATH 307 or MATH 401

MATH 403 Topics in Real Analysis 3 Credits

Intensive study of topics in analysis with emphasis on recent developments. Requires permission of the department chair.
Repeat Status: Course may be repeated.

MATH 404 Topics in Mathematical Logic 3 Credits

Intensive study of topics in mathematical logic. Consent of instructor required.
Repeat Status: Course may be repeated.

MATH 405 Partial Differential Equations I 3 Credits

Classification of partial differential equations; methods of characteristics for first order equations; methods for representing solutions of the potential, heat, and wave equations, and properties of the solutions of these equations; maximum principles.
Prerequisites: MATH 319 or MATH 320

MATH 406 Partial Differential Equations II 3 Credits

Continuation of MATH 405. Emphasis on second order equations with variable coefficients and systems of first order partial differential equations.
Prerequisites: MATH 405

MATH 408 Algebraic Topology I 3 Credits

Polyhedra; fundamental groups; simplicial and singular homology.

MATH 409 Mathematics Seminar 1-6 Credits

An intensive study of some field of mathematics not offered in another course. Consent of department chair required.

MATH 410 Independent study 1-4 Credits

The study of a topic in mathematics under appropriate supervision, designed for the individual student who has studied extensively and whose interests lie in areas not covered in the listed courses. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 416 Complex Function Theory 3 Credits

Continuation of MATH 316.
Prerequisites: MATH 316

MATH 421 Introduction To Wavelets 3 Credits

Continuous and discrete signals; review of Fourier analysis; discrete wavelets; time frequency spaces; Haar and Walsh systems; multiresolution analysis; Hilbert spaces; quadratic mirror filters; fast wavelet transforms; computer code; applications to filtering, compression, and imaging.
Prerequisites: ECE 108 or MATH 205

MATH 423 Differential Geometry I 3 Credits

Differential manifolds, tangent vectors and differentials, submanifolds and the implicit function theorem. Lie groups and Lie algebras, homogeneous spaces. Tensor and exterior algebras, tensor fields and differential forms, de Rham cohomology, Stokes' theorem, the Hodge theorem. Must have completed MATH 301, or MATH 243 or MATH 205 with permission of instructor.

MATH 424 Differential Geometry II 3 Credits

Curves and surfaces in Euclidean space; mean and Gaussian curvatures, covariant differentiation, parallelism, geodesics, GaussBonnet formula. Riemannian metrics, connections, sectional curvature, generalized GaussBonnet theorem. Further topics.
Prerequisites: MATH 423

MATH 428 Fields And Modules 3 Credits

Field theory, including an introduction to Galois theory; the theory of modules, including tensor products and classical algebras.
Prerequisites: MATH 327

MATH 430 Numerical Analysis 3 Credits

Multistep methods for ordinary differential equations; finite difference methods for partial differential equations; numerical approximation of functions. Use of computer required.
Prerequisites: MATH 230

MATH 435 Functional Analysis I 3 Credits

Banach spaces and linear operators; separation and extension theorems; open mapping and uniform boundedness principles; weak topologies; local convexity and duality; Banach algebras; spectral theory of operators; and compact operators.
Prerequisites: MATH 307 and MATH 401

MATH 441 (CSE 441) Advanced Algorithms 3 Credits

Algorithms for searching, sorting, manipulating graphs and trees, scheduling tasks, finding shortest path, matching patterns in strings, cryptography, matroid theory, linear programming, max-flow, etc., and their correctness proofs and analysis of their time and space complexity. Strategies for designing algorithms, e.g. recursion, divide-and-conquer, greediness, dynamic programming. Limits on algorithm efficiency are explored through NP completeness theory. Quantum computing is briefly introduced. Credit will not be given for both CSE 340 (MATH 340) and CSE 441 (MATH 441).

MATH 444 Algebraic Topology II 3 Credits

Continuation of MATH 408. Cohomology theory, products, duality.
Prerequisites: MATH 408

MATH 445 Topcs in Algebraic Topology 3 Credits

Selected topics reflecting the interests of the professor and the students.
Prerequisites: MATH 444

MATH 449 Topics In Algebra 3 Credits

Intensive study of topics in algebra with emphasis on recent developments. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 450 Special Topics 3 Credits

Intensive study of some field of the mathematical sciences not covered in listed courses. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 455 Topics In Number Theory 3 Credits

Selected topics in algebraic and/or analytic number theory. Consent of instructor required.
Repeat Status: Course may be repeated.

MATH 461 Topics In Mathematical Statistcs 3 Credits

An intensive study of one or more topics such as theory of statistical tests, statistical estimation, regression, analysis of variance, nonparametric methods, stochastic approximation, and decision theory.
Repeat Status: Course may be repeated.
Prerequisites: MATH 334 and MATH 401

MATH 462 Modern Nonparametric Methods in Statistics 3 Credits

Classical and modern methods of nonparametric statistics; order and rank statistics; tests based on runs, signs, ranks, and order statistics; distribution free statistical procedures for means, variances, correlations, and trends; relative efficiency; KolmogorovSmirnov statistics; statistical applications of Brownian process; modern techniques such as robust methods, nonparametric smoothing, and bootstrapping; additional topics such as nonparametric regression and dimension reduction.
Prerequisites: (MATH 334 or STAT 334) and (MATH 338 or STAT 338)

MATH 463 (STAT 463) Advanced Probability 3 Credits

Measure theoretic foundations; random variables, integration in a measure space, expectations; convergence of random variables and probability measures; conditional expectations; characteristic functions; sums of random variables, limit theorems.
Prerequisites: MATH 309 and MATH 401

MATH 464 Advanced Stochastic Process 3 Credits

Theory of stochastic processes; stopping times; martingales; Markov processes; Brownian motion; stochastic calculus; Brownian bridge, laws of suprema; Gaussian processes.
Prerequisites: MATH 309 and MATH 401

MATH 465 Topics in Probability 3 Credits

Selected topics in probability. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 467 Stochastic Calculus 3 Credits

Brownian Motion, Martingales. Introduction to the theory of Stochastic Calculus, Itô Formula, and Stochastic Differential Equations, Black-Scholes model. Development of the Martingale Representation Theorem and Girsanov's theorem for change of measure. Multidimensional Stochastic Calculus. Applications to different problems from finance, physics, biology, etc.
Prerequisites: MATH 231 or MATH 309

MATH 468 Financial Stochastic Analysis 3 Credits

Basic mathematical concepts behind pricing of derivative securities. Hedging and pricing by arbitrage in the setting of binary trees and Black-Scholes model. Application of Stochastic Calculus to the pricing of a variety of financial instruments: multiple stock models, American and exotic options, and foreign currency interest rate. Heath-Jarrow-Morton model for the term structure of interest rates and short rate models. Applications of the theory to a variety of interest rates contracts including swaps, caps, floors, swap options.
Prerequisites: MATH 467

MATH 470 Proseminar 1-3 Credits

Preparation for entering the mathematics profession. Topic of emphasis typically include methods of teaching mathematics, commonly available research tools and the publication process, the responsibilities of an academic position, and searching for a job. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 471 Homological Algebra 3 Credits

Modules, tensor products, categories and functors, homology functors, projective and injective modules.
Prerequisites: MATH 428

MATH 472 Group Representations 3 Credits

Linear representations and character theory with emphasis on the finite and compact cases.
Prerequisites: MATH 428

MATH 475 Topics in Geometry 3 Credits

Selected topics in geometry, such as geometric analysis, algebraic geometry, complex geometry, characteristic classes, geometric flows or geometric measure theory, with emphasis on recent developments. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 485 Topics in Financial Mathematics 3 Credits

Selected topics in financial mathematics. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 490 Thesis 1-6 Credits

MATH 491 Research 1-4 Credits

Research in mathematics or statistics under the direction of a faculty member. Consent of department chair required.
Repeat Status: Course may be repeated.

MATH 499 Dissertation 1-15 Credits

Repeat Status: Course may be repeated.

Statistics Courses

STAT 342 Applied Linear Algebra 3 Credits

The theoretical basis for applying linear algebra in other fields, including statistics. Topics will include systems of equations, vector spaces, matrices, and linear transformations. Additional topics will include matrix factorizations (including LU, QR, eigen-decomposition, and SVD) and how they can be used in computer analysis of data sets. Some students may optionally choose to take MATH 205 as preparation for this course. Not available for credit to students who have completed MATH 241 or MATH 242.
Prerequisites: MATH 022

STAT 408 Seminar in Statistics and Probability 1-6 Credits

Intensive study of some field of statistics or probability not offered in another course. Consent of department required.

STAT 409 Seminar in Statistics and Probability 1-6 Credits

Intensive study of some field of statistics or probability not offered in another course. Consent of department required.

STAT 410 Random Processes and Applications 3 Credits

See MATH 310.

STAT 412 Advanced Applied Statistics 3 Credits

Selected advanced topics in applied statistics. Possible topics include nonparametric statistics, multivariate statistics, generalized linear model, survival analysis, time series analysis or other modern applied statistical methods with application to real world problems. Topics could vary from one semester to another depending on the interests of the faculty member and the students.
Repeat Status: Course may be repeated.

STAT 434 Mathematical Statistics 3 Credits

See MATH 334.

STAT 438 Linear Models In Statistics with Applications 3 Credits

See MATH 338.

STAT 439 Time Series and Forecasting 3 Credits

See MATH 339.

STAT 461 Topics In Mathematical Statistics 3 Credits

See MATH 461.

STAT 462 Modern Nonparametric Methods in Statistics 3 Credits

See MATH 462.

STAT 463 (MATH 463) Advanced Probability 3 Credits

See MATH 463.
Prerequisites: MATH 309 and MATH 401

STAT 464 Advanced Stochastic Processes 3 Credits

See MATH 464.

STAT 465 Statistical Machine Learning 3 Credits

See MATH 365.

STAT 471 Topics in Statistical Learning and Computing 3 Credits

Selected advanced topics in statistical learning and computing. Possible topics include linear and nonlinear regression, applied spatial statistics, applied multivariate and longitudinal data analysis, functional data analysis, survival analysis, data analytics, statistical methods that use intensive-computing or simulations, data mining techniques, with application and interpretation of a variety of statistical methods in real world problems. Topics could vary from one semester to another depending on the interests of the faculty member and the students.
Repeat Status: Course may be repeated.

STAT 474 Statistical Practice 3 Credits

Outside university consulting practice that is led by faculty members and experienced members from companies in the region. The live consulting projects provide working examples from which students gain practical experience in statistical practice. Students use this experience to assemble a portfolio of materials that demonstrates the knowledge and skills they have gained during their time in the program. This also offers opportunities to interface with working professionals through the practical training experience. Permission of instructor required.
Repeat Status: Course may be repeated.
Prerequisites: MATH 312 and STAT 438 and STAT 434 and (STAT 465 or STAT 471)

Professors. Huai-Dong Cao, PhD (Princeton University); Donald M Davis, PhD (Stanford University); Wei-Min Huang, PhD (University of Rochester); Garth Isaak, PhD (Rutgers University); David L. Johnson, PhD (Massachusetts Institute of Technology); Terrence J. Napier, PhD (University of Chicago); Mark Skandera, PhD (Massachusetts Institute of Technology); Steven H. Weintraub, PhD (Princeton University); Linghai Zhang, PhD (University of Minnesota Minneapolis)

Associate Professors. Daniel Conus, PhD (Swiss Federal Institute of Technology); Robert W. Neel, PhD (Harvard University); Xiaofeng Sun, PhD (Stanford University); Susan Szczepanski, PhD (Rutgers University New Brunswick); Ping-Shi Wu, PhD (University of California, Davis); Yue Yu, DA (Brown University)

Assistant Professors. Zhaoxing Gao, PhD (Hong Kong University of Science and Technology); Andrew Harder, PhD (University of Alberta); Angela Hicks, PhD (University of California, San Diego); Si Tang, PhD (University of Chicago); Lei Wu, PhD (Brown University)

Professors Of Practice. Vincent E Coll, PhD (University of Pennsylvania); Megan Ann Cream, PhD (Emory University); Miranda Ijang Teboh Ewungkem, PhD (Lehigh University)

Emeriti. Bruce A. Dodson, PhD (State University of NY at Stony Brook); Bennett Eisenberg, PhD (Massachusetts Institute of Technology); Jerry P. King, PhD (University of Kentucky Fort Knox); Clifford S. Queen, PhD (Ohio State University); Eric P. Salathe, PhD (Brown University); Andrew K Snyder, PhD (Lehigh University); Lee J. Stanley, PhD (University of California, Berkeley); Ramamirtham Venkataraman, PhD (Brown University); Joseph E. Yukich, PhD (Massachusetts Institute of Technology)

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