MATH 100. Intermediate Algebra

Instructor(s):  Staff

Required text(s):  Ron Larson. Intermediate Algebra (WebAssign eBook) 5th ed.​

Textbook notes:  Students are required to have access to WebAssign for this course. Students buying used textbooks should arrange to purchase WebAssign separately

Prerequisites:  None

Course description:  Fundamentals of algebra. Graphs of linear equations, polynomials and factoring, first and second-degree equations and inequalities, radicals and exponents, and systems of equations. Word problems emphasized throughout the course.

Syllabus:  Common

  

MATH 108. Real World Modeling

Instructor(s):  Staff

Required text(s):  Consortium for Mathematics and Its Applications (COMAP), S. Garfunkel, ed. For All Practical Purposes: Mathematical Literacy in Today's World. 9th ed. ISBN-13: 978-1429243162. New York: W. H. Freeman, 2011. Print.

Prerequisites:  None

Course description:  An introduction to mathematical modeling. Topics chosen from linear programming, probability theory, Markov chains, scheduling problems, coding theory, social choice, voting theory, geometric concepts, game theory, graph theory, combinatorics, networks. Emphasis placed upon demonstrating the usefulness of mathematical models in other disciplines, especially the social science and business.

Syllabus:  Common

  

MATH 117. Precalculus I

Instructor(s):  Staff

Required text(s):  Eric Connally, Hughes-Hallett, D., and Gleason, A. M. Functions Modeling Change: A Preparation for Calculus. 5th ed. New Jersey: Wiley, 2015. Packaged with WileyPlus.​

Prerequisites:  MATH 100 or Math Diagnostic Test

Course description:  Inverse functions, quadratic functions, complex numbers. Detailed study of polynomial functions including zeros, factor theorem, and graphs. Rational functions, exponential and logarithmic functions and their applications. Systems of equations, inequalities, partial fractions, linear programming, sequences and series. Word problems are emphasized throughout the course.

Syllabus:  Common

  

MATH 118. Precalculus II

Instructor(s):  Staff

Required text(s):  Eric Connally, Hughes-Hallett, D., and Gleason, A. M. Functions Modeling Change: A Preparation for Calculus. 5th ed. New Jersey: Wiley, 2015. Packaged with WileyPlus.​

Prerequisites:  MATH 117 or Math Diagnostic Test

Course description:  Functions and change with an emphasis on linear, quadratic, exponential, and logarithmic functions and their graphs. Specific geometric topics include concavity and how transformations affect graphs. Topics in trigonometry include radians, sinusoidal functions, identities, sum/difference formulas, double/half angle formulas, and trigonometric equations. Other topics include polar coordinates.

Syllabus:  Common

  

MATH 123. Topics in Single Variable Calculus

Instructor(s):  Dr. Peter Tingley

Required text(s):  Stewart, James. Calculus: Early Transcendentals. 8th ed.

Prerequisites:  Prerequisite: MATH131 or 132.

Course description:  This seminar will cover topics from MATH161/162 which are not covered in MATH131/132. The purpose is to allow students who have taken the MATH131/132 sequence to transition to MATH263. The seminar will consist of students working through several booklets, partly in-class and partly as homework. After each, students must pass a quiz. Students must agree to complete this work by week 6 of the semester. The class must be taken pass/fail.

  

MATH 131. Applied Calculus I

Instructor(s):  Staff

Required text(s):  Hughes-Hallett, Deborah, et al. Applied & Single Variable Calculus for Loyola University Chicago, Custom (WebAssign eBook). 4th ed.

Print text (optional): ISBN-13: 9781118747476. Hoboken, NJ: Wiley, 2013.

Prerequisites:  MATH 118 or Math Diagnostic Test

Course description:  An introduction to differential and integral calculus, with an emphasis on applications. This course is intended for students in the life and social sciences, computer science, and business. Topics include: modeling change using functions including exponential and trigonometric functions, the concept of the derivative, computing the derivative, applications of the derivative to business and life, social, and computer sciences, and an introduction to integration. This course is not a substitute for MATH 161.

Syllabus:  Common

  

MATH 132. Applied Calculus II

Instructor(s):  Staff

Required text(s):  Hughes-Hallett, Deborah, et al. Applied & Single Variable Calculus for Loyola University Chicago, Custom (WebAssign eBook). 4th ed.

Print text (optional): ISBN-13: 9781118747476. Hoboken, NJ: Wiley, 2013.

Prerequisites:  MATH 131 or MATH 161

Course description:  A continuation of MATH 131. Topics include: properties of the integral, techniques of integration, numerical methods, improper integrals, applications to geometry, physics, economics, and probability theory, introduction to differential equations and mathematical modeling, systems of differential equations, power series. This course is not a substitute for MATH 162.

Syllabus:  Common

  

MATH 161. Calculus I

Instructor(s):  Staff

Required text(s):  Stewart, James. Calculus: Early Transcendentals (WebAssign eBook). 8th ed.

Print text (optional): ISBN-13: 978-1285741550. Boston: Centage Learning, 2015.

Prerequisites:  MATH 118

Course description:  A traditional introduction to differential and integral calculus. Functions, limits, continuity, differentiation, intermediate and mean-value theorems, curve sketching, optimization problems, related rates, definite and indefinite integrals, fundamental theorem of calculus, logarithmic and exponential functions. Applications to physics and other disciplines.

Syllabus:  Common

  

MATH 162. Calculus II

Instructor(s):  Staff

Required text(s):  Stewart, James. Calculus: Early Transcendentals (WebAssign eBook). 8th ed.

Print text (optional): ISBN-13: 978-1285741550. Boston: Centage Learning, 2015.

Prerequisites:  MATH 161

Course description:  A continuation of MATH 161. Calculus of logarithmic, exponential, inverse trigonometric, and hyperbolic functions. Techniques of integration. Applications of integration to volume, surface area, arc length, center of mass, and work. Numerical sequences and series. Study of power series and the theory of convergence. Taylor's theorem with remainder.

Syllabus:  Common

  

MATH 201. Introduction to Discrete Mathematics & Number Theory (002)

Instructor(s):  Emily Peters

Required text(s):  Discrete Mathematics with Ducks, by sarah-marie belcastro. June 21, 2012 by A K Peters/CRC Press Textbook. ISBN 9781466504998

Prerequisites:  MATH 161

Course description:  This course serves primarily as an introduction to understanding and constructing proofs for students planning to take advanced 300-level courses in mathematics. Topics include: mathematical induction, the Euclidean algorithm, congruences, divisibility, counting/combinatorics, and graph theory.

  

MATH 201. Introduction to Discrete Mathematics & Number Theory (001)

Instructor(s):  Dr. Anthony Giaquinto

Required text(s):  Discrete Mathematics with Ducks, by sarah-marie belcastro. June 21, 2012 by A K Peters/CRC Press Textbook. ISBN 9781466504998

Prerequisites:  MATH 161

Course description:  This course serves primarily as an introduction to understanding and constructing proofs for students planning to take advanced 300-level courses in mathematics. Topics include: mathematical induction, the Euclidean algorithm, congruences, divisibility, counting/combinatorics, and graph theory.

  

Math 212. Linear Algebra (002)

Instructor(s):  Peter Tingley

Required text(s):  Anton, Howard. Elementary Linear Algebra. 11th ed. ISBN-13: 978-1118473504. New York: John Wiley, 2013. Print.

Prerequisites:  MATH 132 or MATH 162

Course description:  This course will be a mathematically rigorous introduction to the basic concepts, theory, and applications of linear algebra. Proofs of basic results will be provided where appropriate. Students may be required to write simple proofs on homework assignments and tests. Linear algebra techniques are important because of their many applications in science, economics, business, engineering, and the life sciences. Moreover, linear algebra constitutes a bridge from basic to more advanced mathematics.

  

MATH 212. Linear Algebra (001)

Instructor(s):  Dr. John G. Del Greco

Required text(s):  Anton, Howard. Elementary Linear Algebra. 11th ed. ISBN-13: 978-1118473504. New York: John Wiley, 2013. Print.

Prerequisites:  MATH 132 or MATH 162

Course description:  This course will be a mathematically rigorous introduction to the basic concepts, theory, and applications of linear algebra. Proofs of basic results will be provided where appropriate. Students may be required to write simple proofs on homework assignments and tests. Linear algebra techniques are important because of their many applications in science, economics, business, engineering, and the life sciences. Moreover, linear algebra constitutes a bridge from basic to more advanced mathematics.

  

MATH 215. [ COMP 215 ] Object-Oriented Programming for Mathematics

Instructor(s):  Dr. Christine Haught

Required text(s):  TBA

Prerequisites:  MATH 162

Course description:  Math 215 is an introductory programming course for students interested in mathematics and scientific applications. No previous programming experience is required. This course can be used to satisfy the Comp 170 requirement in the math major. Students will learn object-oriented programming using the programming language Python. Python is easy to learn and we will quickly be able to solve interesting problems with it. Programming examples will come from mathematics, physics, bioinformatics and other scientific computing applications. In particular we will work with examples from calculus, number theory, statistics, geometry, fractals and linear algebra. The course is programming intensive. There will be weekly programming assignments as well as frequent in-class exercises. There will be approximately 10 quizzes during the term, a final project and a final exam.

  

MATH 263. Multivariable Calculus

Instructor(s):  Staff

Required text(s):  Stewart, James. Calculus: Early Transcendentals (WebAssign eBook). 8th ed.

Print text (optional): ISBN-13: 978-1285741550. Boston: Cengage Learning, 2015.

Prerequisites:  MATH 162

Course description:  Vectors and vector algebra, curves and surfaces in space, functions of several variables, partial derivatives, the chain rule, the gradient vector, LaGrange multipliers, multiple integrals, volume, surface area, the Change of Variables theorem, line integrals, surface integrals, Green's theorem, the Divergence Theorem, and Stokes' Theorem.

Syllabus:  Common

  

MATH 264. Ordinary Differential Equations (002)

Instructor(s):  Dr. Cristina Popovici

Required text(s):  Boyce, William E., and DiPrima, Richard C., Elementary Differential Equations, 10th Edition; ISBN: 978-1-118-61743-4 (E-Text); 978-1-118-15739-8 (Loose-leaf); 978-0-470-45832-7 (Hardcover). Wiley, 2013.

Prerequisites:  MATH 263 or MATH 263 concurrently

Course description:  This is an introductory course in ordinary differential equations. Topics to be discussed include linear and nonlinear first order differential equations such as separable, exact, homogeneous, and Bernoulli equations, second order linear equations, the Laplace transform and its applications to solving initial value problems, and systems of linear first-order differential equations. Homework will be assigned regularly throughout the semester. There will be weekly quizzes, two midterms, and a comprehensive final exam.

  

MATH 264. Ordinary Differential Equations

Instructor(s):  Rafal Goebel

Required text(s):  Fundamentals of Differential Equations, by Nagle, Saff, and Snider. 5th edition, or a newer one. 5th edition is ISBN-13: 978-0201338683, ISBN-10: 0201338688.

Prerequisites:  Math 263 is a corequisite. Being comfortable with differentiation and integration is desired.

Course description:  Differential equations can model how things change in time. These things can be population sizes, say for a growing population of bacteria (or zombies!) or for oscillating populations of predators and prey; temperature of your favorite cold beverage when left out in the sun; mechanical systems like weights on a spring or planets around the sun; currents in an electrical circuits; positions of autonomous robots on Mars; amounts of compounds during a chemical reaction; and more. The course will be a fairly standard introduction to differential equations. Students will learn how to model things as listed above, and more, using differential equations; how to solve differential equations, at least those that can be solved; how to predict how solutions to differential equations behave even if the solutions cannot be found explicitly; and possibly how to use mathematical software to help with these learning objective.

  

MATH 277. Problem-Solving Seminar

Instructor(s):  Dr. Stephen London

Required text(s):  None

Prerequisites:  None

Course description:  In a seminar setting, students discuss and present proofs (or computer examples) as solutions to challenging and interesting problems including those from the Putnam and Virginia Tech mathematics competitions. Techniques are drawn from numerous areas of mathematics such as calculus of one and several variables, combinatorics, number theory, geometry, linear algebra, and abstract algebra.

  

MATH 301. History of Mathematics

Instructor(s):  Dr. Steven L. Jordan

Required text(s):  NONE

Recommended text(s):  Recommended: History of Mathematics, 3rd ed (2009), by Victor Katz. Pearson, Publisher. Hardback has ISBN-10: 0321387007, ISBN-13: 9780321387004.

Textbook notes:  You may use hardback, paperback, Kindle, or rent.

Prerequisites:  MATH 132 or Math 162. MATH 201 is recommended.

Course description:  In this course students will study some of the most influential and insightful mathematics from the time of Babylonian cuneiform tablets, through the invention of calculus and beyond.

This course is designed to give prospective math teachers, math majors, philosophy majors, history majors and others an appreciation of the universal appeal and the triumphs of mathematics in many cultures and times. Students will learn the mathematical concepts (e.g., Euclid’s notion of “number”), techniques (e.g., continued fractions), algorithms (e.g., Chinese Remainder Theorem), contexts (e.g., mathematical astronomy), and influential institutions (e.g., the House of Wisdom) that permeate our mathematical and scientific heritage.

The approach will emphasize historical scholarship and mathematical problem-solving. We will use original source materials – which are surprisingly accessible. These “documents” demonstrate the thinking behind great mathematics through the centuries, in diverse cultures, and in different subjects: geometry, analysis, number theory, etc. Main topics: Plimpton 322, Rhind Papyrus, Euclid’s Elements, Archimedes’ The Sand Reckoner, Ptolemy’s Table of Chords, Diophantus, Sun-Tsu, al-Khowarizmi, Brahmagupta and Indian mathematics, Mayan mathematics, Robert Recorde, Isaac Newton and Leibniz, Fermat and Descartes, solution to cubics, Gauss’ contributions, species of numbers, mathematical tables and machines, unsolved problems and contests (e.g., Hilbert’s Problems), institutions and mathematical genealogy. Additional or alternate topics may be included depending on the interest of students.

Syllabus:  We will prepare a collection of biographies of women and other mathematicians who serve as role models for students from underrepresented communities. Teachers in this course will tailor their reports so that they are appropriate for lessons and classroom use.

Outcomes/Expectations: Students will
Exhibit fluency in major concepts, techniques, algorithms, contexts, of mathematics throughout the ages, and in diverse civilizations
Extend the historical mathematics to appropriate new settings.
Explain the historical, cultural, and social settings for the mathematics and the mathematicians that we study.

  

MATH 309. [ COMP 309 COMP 409 MATH 409 ] Numerical Methods

Instructor(s):  Dr Stephen Doty

Required text(s):  L. Ridgway Scott, Numerical Analysis, Princeton University Press 2011. Print ISBN: 9780691146867; E-book ISBN: 9781400838967.

Prerequisites:  MATH 212 (Linear algebra), MATH 264 (Differential Equations, and either COMP 170 or COMP/MATH 215 (Computer Programming).

Course description:  Have you ever wondered how a pocket calculator comes up with its answers? This course provides the theoretical background for that question as well as many others. Numerical analysis is the study of algorithms for the problems of continuous mathematics (Trefethen 1992). Algorithms implies computers, and continuous mathematics implies analysis: approximation and convergence. Approximating real and complex numbers is the task of floating-point arithmetic in computer architecture; the deeper business of numerical analysis is approximating unknowns. Rapid convergence of approximations is the aim: for many problems, humans have invented algorithms that converge exceedingly fast. Many of the problems are familiar: solving equations and systems of equations, approximating functions, estimating derivatives and integrals, approximating solutions to differential equations. These problems are ubiquitous in applications of mathematics to the sciences, so numerical methods are useful in many fields. Most scientists and engineers are sooner or later faced with computing tasks that require some knowledge of numerical analysis. As you probably know, most non-linear problems cannot be solved exactly; indeed, Abel and Galois proved that exactly solving polynomial equations of degree higher than four is usually impossible. Even for polynomials, the simplest imaginable non-linear functions, often the best that we can do is to approximate the solutions. For this course you will need access to a computer and the internet. Prerequisites are: MATH 212 (Linear algebra), MATH 264 (Differential Equations, and either COMP 170 or COMP/MATH 215 (Computer Programming).

  

MATH 315. [ MATH 415 ] Advanced Topics in Linear Algebra

Instructor(s):  Dr. Joseph Mayne

Required text(s):  Sheldon Axler, Linear Algebra Done Right, 3rd Edition, Springer, (2015). ISBN: 978-3-319-11079-0.

Prerequisites:  MATH 313

Course description:  This course is a continuation of Mathematics 212, Linear Algebra. The emphasis will be on abstract vector spaces over the fields of real and complex numbers. There will a review of the basic properties of vector spaces and their subspaces. Continuing the study of vector spaces and linear transformations on finite-dimensional spaces, topics will be chosen from: change of basis, trace, determinants, eigenvalues, invariant subspaces, linear functionals, dual spaces, inner product spaces, adjoint transformations, the Spectral Theorem, the characteristic and minimal polynomials, and Jordan canonical form.

  

MATH 353. Introduction to Complex Analysis

Instructor(s):  Dr. John G. Del Greco

Required text(s):  E. B. Saff and Snider, A. D., Fundamentals of Complex Analysis with Applications to Engineering and Science. 3rd ed. New Jersey: Pearson, 2003. Print. ISBN-13: 978-0134689487 ISBN-10: 0134689488

Prerequisites:  Math 264

Course description:  In complex analysis we are interested in extending results using real numbers in algebra and analysis to analogous results using the field of complex numbers. Applications of this extension occur in electrical engineering, signal processing, quantum mechanics, and various mathematical fields such as number theory and real analysis. Many concepts and results that seem non-intuitive when encountered in real analysis become “natural” when extended to their complex versions. We will study analytic functions, integration, infinite series, residue theory and conformal mappings. Grading will be based on homework sets, three tests during the semester, and a final examination

  

Math 360. [ Math 460 ] Theory of Games

Instructor(s):  Dr. Peter Tingley

Required text(s):  Barron, E. N. Game Theory: An Introduction. 2nd ed. ISBN-13: 978-1118216934. New York: John Wiley Interscience, 2013. Print.

Prerequisites:  MATH162. Some 200 level math or stats recommended.

Course description:  Throughout many fields (economics, biology, politics, engineering, sports...most of life really) people must work towards goals while other forces are acting against them. Any such situation can be thought of as a game, where the "players" make various decisions while trying to achieve goals which may be in conflict. Game theory studies methods of making "good" decisions. Often this reduces to quite elegant mathematics. We will study that math, and consider some applications. Mathematica and/or Gambit Software will be used at times, although no prior knowledge of programming is required. There will be two midterms and a cumulative final exam, and homework will be regularly assigned and graded.

  

MATH 409. [ COMP 309 COMP 409 MATH 309 ] Numerical Methods

Instructor(s):  Dr Stephen Doty

Required text(s):  L. Ridgway Scott, Numerical Analysis, Princeton University Press 2011. Print ISBN: 9780691146867; E-book ISBN: 9781400838967.

Prerequisites:  MATH 212 (Linear algebra), MATH 264 (Differential Equations, and either COMP 170 or COMP/MATH 215 (Computer Programming).

Course description:  Have you ever wondered how a pocket calculator comes up with its answers? This course provides the theoretical background for that question as well as many others. Numerical analysis is the study of algorithms for the problems of continuous mathematics (Trefethen 1992). Algorithms implies computers, and continuous mathematics implies analysis: approximation and convergence. Approximating real and complex numbers is the task of floating-point arithmetic in computer architecture; the deeper business of numerical analysis is approximating unknowns. Rapid convergence of approximations is the aim: for many problems, humans have invented algorithms that converge exceedingly fast. Many of the problems are familiar: solving equations and systems of equations, approximating functions, estimating derivatives and integrals, approximating solutions to differential equations. These problems are ubiquitous in applications of mathematics to the sciences, so numerical methods are useful in many fields. Most scientists and engineers are sooner or later faced with computing tasks that require some knowledge of numerical analysis. As you probably know, most non-linear problems cannot be solved exactly; indeed, Abel and Galois proved that exactly solving polynomial equations of degree higher than four is usually impossible. Even for polynomials, the simplest imaginable non-linear functions, often the best that we can do is to approximate the solutions. For this course you will need access to a computer and the internet. Prerequisites are: MATH 212 (Linear algebra), MATH 264 (Differential Equations, and either COMP 170 or COMP/MATH 215 (Computer Programming).

  

MATH 415. [ MATH 315 ] Advanced Topics in Linear Algebra

Instructor(s):  Dr. Joseph Mayne

Required text(s):  Sheldon Axler, Linear Algebra Done Right, 3rd Edition, Springer, (2015). ISBN: 978-3-319-11079-0.

Prerequisites:  MATH 313

Course description:  This course is a continuation of Mathematics 212, Linear Algebra. The emphasis will be on abstract vector spaces over the fields of real and complex numbers. There will a review of the basic properties of vector spaces and their subspaces. Continuing the study of vector spaces and linear transformations on finite-dimensional spaces, topics will be chosen from: change of basis, trace, determinants, eigenvalues, invariant subspaces, linear functionals, dual spaces, inner product spaces, adjoint transformations, the Spectral Theorem, the characteristic and minimal polynomials, and Jordan canonical form.

  

Math 460. [ Math 360 ] Theory of Games

Instructor(s):  Dr. Peter Tingley

Required text(s):  Barron, E. N. Game Theory: An Introduction. 2nd ed. ISBN-13: 978-1118216934. New York: John Wiley Interscience, 2013. Print.

Prerequisites:  MATH162. Some 200 level math or stats recommended.

Course description:  Throughout many fields (economics, biology, politics, engineering, sports...most of life really) people must work towards goals while other forces are acting against them. Any such situation can be thought of as a game, where the "players" make various decisions while trying to achieve goals which may be in conflict. Game theory studies methods of making "good" decisions. Often this reduces to quite elegant mathematics. We will study that math, and consider some applications. Mathematica and/or Gambit Software will be used at times, although no prior knowledge of programming is required. There will be two midterms and a cumulative final exam, and homework will be regularly assigned and graded.

  

STAT 103. Fundamentals of Statistics

Instructor(s):  Staff

Required text(s):  C.H. Brase and C.P. Brase. Understanding Basic Statistics, 7th ed (WebAssign eBook). Cengage.

Prerequisites:  None

Course description:  An introduction to statistical reasoning. Students learn how statistics has helped to solve major problems in economics, education, genetics, medicine, physics, political science, and psychology. Topics include: design of experiments, descriptive statistics, mean and standard deviation, the normal distribution, the binomial distribution, correlation and regression, sampling, estimation, and testing of hypothesis.

Syllabus:  Common

  

STAT 203. Introduction to Probability and Statistics

Instructor(s):  Dr. John G. Del Greco

Required text(s):  Barron, E. N. and John G. Del Greco, Probability & Statistics , Preliminary version. Available only at the book store.

Prerequisites:  Math 132 or Math 162 (with a grade of at least C). Math 263 is recommended as a prerequisite or taken concurrently.

Course description:  Stat 203 will be a rigorous course in probability and statistics. It is calculus based and is required of all statistics and mathematics majors as well as engineering science students. It is recommended for physics, chemistry, and biology majors. Stat 203 covers the essential topics in probability and statistics with derivations of most of the results. It can be used as a stand-alone course or a foundation for advanced study in probability and statistics. We will have two midterms and a final exam. A TI-8x is required for this course. The following topics will be covered: axiomatic probability, random variables (distributions, mean, variance, moment-generating functions), sampling distributions for the normal random variable, statistical intervals, hypotheses testing, and linear regression.

  

STAT 303. SAS Programming and Applied Statistics

Instructor(s):  Dr. Michael Perry

Required text(s):  None

Recommended text(s):  R. Cody & Smith, Applied Statistics and the SAS Programming

Additional notes:  Laptop and SAS On Demand account is required. We will set up a SAS On Demand account on the first day of class.

Prerequisites:  STAT 103, STAT 203 or STAT 335

Course description:  This course is an introduction to writing and executing SAS programs under the Windows environment in the context of applied statistics problems. SAS procedures are used to read and analyze various types of data sets as they apply to t-tests, simple and multiple regressions, ANOVA, categorical analysis, and repeated measures. Students will be graded on homework, quizzes, one take home test and one project with a presentation. The course will require a significant amount of computer coding.

  

STAT 307. [ STAT 407 ] Statistical Design and Analysis of Experiments

Instructor(s):  Timothy E. O'Brien, Ph.D.

Required text(s):  Montgomery, Douglas C. (2013), Design and Analysis of Experiments, 8th Edition, Wiley, ISBN: 9781118146927.

Prerequisites:  STAT-203 or STAT-335 or equivalent, or permission of the instructor. STAT-308/408 (or exposure to regression methods) strongly recommended.

Course description:  As no subject is more central to the development of statistical methods, this course provides students with a thorough introduction to statistical experimental design and to the statistical methods used to analyze the resulting data. The concepts of comparative experiments, analysis of variance (ANOVA) and mean separation procedures will be reviewed; blocking (complete and incomplete) will be discussed, as will be factorial designs, fractional factorial designs, and confounding. The course will focus on biometric applications such as clinical trials, HIV studies, and environmental and agricultural research, but industrial and other examples will occasionally be provided to show the breadth of application of experimental design ideas. Students will develop expertise using the SAS and R computer packages, although no previous programming experience will be assumed. Grading is based on participation, homework assignments, a project/paper, exam(s) and a final.

  

STAT 308. Applied Regression Analysis

Instructor(s):  Michael Perry

Required text(s):  Applied Regression Analysis and Other Multivariable Methods 5th Edition - Kleinbaum, Kupper, Nizam, Rosenberg. (Customized version for Loyola)

Prerequisites:  STAT 203 or STAT 335 (or permission of instructor)

Course description:  This course provides students with a thorough introduction to applied regression methodology. The concept of simple linear regression will be reviewed, and multiple linear regression, transformations, indicator variables, multicollinearity, diagnostics, model building, polynomial regression, logistic regression, nonparametric regression and time series analysis will be discussed. The course will focus on applications such as those from biometry and biostatistics (clinical trials, HIV studies, etc.), sports, engineering, agriculture and environmental science. Students are required to analyze real-life datasets using the R statistical software, although no previous programming experience is assumed. Quizzes, exams, and take-home assignments and projects will be used to determine the final grade in the course.

  

STAT 388. [ STAT 488 ] Topics in Statistics: Sampling Methods

Instructor(s):  Dr. Gregory J. Matthews

Required text(s):  Lohr, Sharon. Sampling: Design and Analysis. 2nd ed. ISBN-13: 978-0495105275. Boston, MA: Brooks/Cole, 2010. Print.

Prerequisites:  STAT 203 or STAT 335 or equivalent, or permission of instructor.

Course description:  This course focuses on the statistical aspects of collecting and analyzing data from a sample. After a review of probability concepts used in sampling, we will cover the fundamental topics of simple random, systematic, stratified and cluster sampling, as well as ratio and regression estimation. More complex sampling methods will also be discussed, along with methods of dealing with nonresponse and measurement error. A familiarity with basic ides of expectation, sampling distributions, confidence intervals and linear regression is assumed. The focus throughout this course will be on applications and real-life data sets; as such, theorems and proofs will not be emphasized.

  

STAT 388. Applied Survival Analysis

Instructor(s):  Swarnali Banerjee

Required text(s):  Survival Analysis Techniques for Censored and Truncated Data by Klein and Moeschberger (2nd Edition)

Prerequisites:  STAT 203 or STAT 335

Course description:  Modern statistical methods are covered to analyze data that is right-, left- and/or interval-censored. Nonparametric approaches such as the Kaplan-Meier estimation technique, log-rank test and proportional-hazards model are considered as are parametric methods such as those based on the Exponential and Weibull distribution. Accelerated failure time models and nonlinear models are also discussed. Students will develop expertise using SAS (and R) computer packages, although no previous programming experience will be assumed.

  

STAT 390. Undergraduate Seminar

Instructor(s):  Timothy E. O'Brien, Ph.D.

Required text(s):  Lander, J.P., R for Everyone, 2017 (Second Edition), Pearson, ISBN-13: 978-0-13-454692-6; ISBN: 0-13-454692-X.

Prerequisites:  Senior standing and the completion of STAT-304.

Course description:  The seminar will cultivate students' presentation skills through participation in and critical discussion of brief lectures on familiar and unfamiliar topics; preparation and presentation of two brief lectures by the student (one on a familiar topic from the curriculum, one on a higher level material not customarily from the curriculum); and preparation of an extended abstract summarizing the advanced material presented. Outcomes: Students will gain the ability to present material in Statistics, and their applications to a general audience.

  

STAT 396. Actuarial Seminar I

Instructor(s):  Swarnali Banerjee

Required text(s):  ACTEX Study Manual for SOA Exam P

Prerequisites:  MATH 263 MATH 212, STAT 304 are strongly recommended.

Course description:  The seminar provides a comprehensive review of the probability topics that most commonly appear on the Actuarial Exam P or (CAS Exam 1). Topics covered include: axiomatic probability, combinatorial probability, conditional probability and Bayes' Theorem, independence, random variables and their various distributions, joint distributions, marginal distributions, conditional distributions of two of more random variables including joint moment generating functions and transformation techniques.

  

STAT 404. Probability and Statistics I

Instructor(s):  Dr. Shuwen Lou

Required text(s):  Robert V. Hogg, McKean, Joseph W., and Craig, Alan T., Introduction to Mathematical Statistics. 7th ed. Boston, MA: Pearson, 2013. Print.

Prerequisites:  Stat 335 or Stat 203

Course description:  This is the first semester of a two-semester sequence. The first semester is essentially an exploration of probability as a mathematical model of chance phenomena. The second semester explores the statistical analyses based on these models. Topics to be covered include discrete and continuous random variables, transformations, multivariate distributions, correlation, independence, variance-covariance, special distributions (binomial, Poisson, gamma, chi-square, beta, normal, multivariate normal, t, and F), expectations of functions, convergence in probability, convergence in distribution, moment generating functions, and the central limit theorem.

  

STAT 407. [ STAT 307 ] Statistical Design and Analysis of Experiments

Instructor(s):  Timothy E. O'Brien, Ph.D.

Required text(s):  Montgomery, Douglas C. (2013), Design and Analysis of Experiments, 8th Edition, Wiley, ISBN: 9781118146927.

Prerequisites:  STAT-203 or STAT-335 or equivalent, or permission of the instructor. STAT-308/408 (or exposure to regression methods) strongly recommended.

Course description:  As no subject is more central to the development of statistical methods, this course provides students with a thorough introduction to statistical experimental design and to the statistical methods used to analyze the resulting data. The concepts of comparative experiments, analysis of variance (ANOVA) and mean separation procedures will be reviewed; blocking (complete and incomplete) will be discussed, as will be factorial designs, fractional factorial designs, and confounding. The course will focus on biometric applications such as clinical trials, HIV studies, and environmental and agricultural research, but industrial and other examples will occasionally be provided to show the breadth of application of experimental design ideas. Students will develop expertise using the SAS and R computer packages, although no previous programming experience will be assumed. Grading is based on participation, homework assignments, a project/paper, exam(s) and a final.

  

STAT 411. Applied Survival Analysis

Instructor(s):  Swarnali Banerjee

Required text(s):  Survival Analysis Techniques for Censored and Truncated Data by Klein and Moeschberger (2nd Edition)

Prerequisites:  Some background in basic statistical methods or biostatistics, or permission of instructor.

Course description:  Modern statistical methods are covered to analyze data that is right-, left- and/or interval-censored. Nonparametric approaches such as the Kaplan-Meier estimation technique, log-rank test and proportional-hazards model are considered as are parametric methods such as those based on the Exponential and Weibull distribution. Accelerated failure time models and nonlinear models are also discussed. Students will develop expertise using the SAS (and R) computer packages, although no previous programming experience will be assumed.

  

STAT 488. [ STAT 388 ] Topics in Statistics: Sampling Methods

Instructor(s):  Dr. Gregory J. Matthews

Required text(s):  Lohr, Sharon. Sampling: Design and Analysis. 2nd ed. ISBN-13: 978-0495105275. Boston, MA: Brooks/Cole, 2010. Print.

Prerequisites:  STAT 203 or STAT 335 or equivalent, or permission of instructor.

Course description:  This course focuses on the statistical aspects of collecting and analyzing data from a sample. After a review of probability concepts used in sampling, we will cover the fundamental topics of simple random, systematic, stratified and cluster sampling, as well as ratio and regression estimation. More complex sampling methods will also be discussed, along with methods of dealing with nonresponse and measurement error. A familiarity with basic ides of expectation, sampling distributions, confidence intervals and linear regression is assumed. The focus throughout this course will be on applications and real-life data sets; as such, theorems and proofs will not be emphasized.

  

STAT 488. Statistical Consulting

Instructor(s):  Swarnali Banerjee

Required text(s):  Cabrera,J. and McDougall, A. Statistical Consulting, Chapman & Hall.

Prerequisites:  Stat 404/405 and Stat 408 or permission of instructor.

Course description:  Students will be placed into groups of 4-5 students and assigned a client to work with for the duration of the semester. Each group will provide regular updates on the progress of the project via an oral presentation approximately every few weeks. Additionally, at the end of the semester each group will submit a well-written report documenting the problem, the data, the work they did, and future idea for new directions. In addition to this group project, each individual will be required to present topics previously chosen (needs approval). Presentations must be accompanied by well written, informative slides. Student will also be graded based on their participation during class. This includes, but is not limited to, asking relevant questions during the group and individual presentations.