Instructor(s):  Staff

Required text(s):  McCallum, Connally, Hughes-Hallett et al. Algebra: Form and Function. 2nd edition. (with WileyPlus ebook)

Textbook notes:  Students buying used textbooks should arrange to purchase WileyPlus separately. Instructions for students to obtain the e-book and to use WileyPlus: use your Loyola email address to create a WileyPlus account. Your professor will include details on WileyPlus in the syllabus.

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

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

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

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

Instructor(s):  Emily Peters

Required text(s):  none

Prerequisites:  Pre or corequisite: Math 131 or 161

Course description:  This one-credit seminar is designed for freshman and sophomore students who are interested in mathematics. It provides a glimpse into the world of mathematics beyond elementary calculus. It aims to be informal, lively and thought-provoking. In the age of enlightenment, scientists used mathematics to model physical phenomena and in doing so changed the world. In the age of information, we are using mathematics to model social phenomena. Find out about the principals behind: *encoding secure information on the internet *fair voting in a democracy *how google decides what order to display search results in *modelling the spread of disease *matching future doctors and hospitals for residency *understanding how information spreads through networks and other topics! There are no exams in this class; grades will be based on participation and occasional written homework.

Instructor(s):  Staff

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

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

Instructor(s):  Staff

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

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

Instructor(s):  Staff

Required text(s):  Dwyer and Gruenwald. Calculus: Resequenced for Students in Stem (WileyPlus eBook). preliminary edition.

Print text (optional): ISBN-13: 978-1119321590.

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

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

Instructor(s):  Dr. Brian Seguin

Required text(s):  Mathematics: A Discrete Introduction (3rd edition) by Edward Scheinerman ISBN-13: 978-0840065285 ISBN-10: 0840065280

Prerequisites:  MATH 161

Course description:  This course covers topics from discrete mathematics and number theory, areas of mathematics not seen in calculus courses and abundant in applications, and provides students with the concepts and techniques of mathematical proof needed in 300-level courses in mathematics. In particular, students will obtain an understanding of the basic concepts and techniques involved in constructing rigorous proofs of mathematical statements.

Instructor(s):  Alan Saleski

Required text(s):  Richard Hammack, Book of Proof (3rd edition), Hammack Pub. (2018) ISBN-13 9780989472128 Also available as a PDF on the author's website.

Additional notes:  This is a writing-intensive course. In addition to weekly homework, students will submit two papers.

Prerequisites:  MATH 161

Course description:  This writing-intensive course in Discrete Mathematics attempts to engage and expose the student to several different topics in discrete mathematics (including induction, naive set theory, number theory, combinatorics, algebraic structures, basic logic, equivalence relations, injective and surjective maps, and cardinality.) The primary desired outcome is for the student to learn how to read and write precise and unambiguous mathematical proofs at a beginning level. Such skills should prepare students to enter 300-level courses such as Abstract Algebra and Real Analysis.

Syllabus:  Sets; logic; counting; direct proof; contrapositive proof; proof by contradiction; mathematical induction; relations; functions, bijections; cardinality. In addition, students will write two papers, each on a mathematical theme as will be discussed in class. Outcome: Students will obtain an understanding of the basic concepts and techniques involved in constructing rigorous proofs of mathematical statements.

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.

Instructor(s):  Dr. Aaron Lauve

Required text(s):  Strang, Gilbert. Introduction to Linear Algebra. 5th edition. ISBN-13: 978-0980232776. Wellesley-Cambridge Press. 2016. Print.

Prerequisites:  Math 132 or Math 162.

Course description:  Linear systems are ubiquitous in mathematics, science, engineering, and the social sciences. (For example, statisticians and economists often employ linear models to analyze otherwise intractable problems with many variables.) Evidently, a systematic approach for solving linear systems would be immensely valuable. This course begins by giving one approach, the algorithm of Gaussian Elimination, then continues by developing, rigorously, the important axioms and theorems of linear algebra that are hiding behind this elegant algorithm. Motivating examples will frequently be illustrated using the computer algebra packages Sage and MATLAB.

Syllabus:  An introduction to linear algebra in abstract vector spaces with particular emphasis on finite dimensional Euclidean space. Topics: Gaussian elimination, matrix algebra, linear independence, span, basis, linear transformations, Gram-Schmidt, determinants, eigenvalues, eigenvectors, and diagonalization. Some of the basic theorems will be proved rigorously; other results will be demonstrated informally. Applications will be emphasized throughout. Assessments: weekly quizzes and online homework; two in-term exams; and a final exam.

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

Instructor(s):  Dr. John G. Del Greco

Required text(s):  Nagle, R. Kent, Saff, Edward B., and Edward B. Snider. Fundamentals of Differential Equations. 9th ed. MyLab Math with Pearson e-Text, ISBN-13: 9780134764832

Prerequisites:  MATH 263. Being able to differentiate and integrate functions is an essential skill when studying differential equations. Students will be assumed to be proficient in the techniques of differentiation and integration.

Course description:  This course will be a rigorous treatment of ordinary differential equations. The course will emphasize solutions techniques although some applications will be considered.

Topics will include first- and second-order linear differential equations and methods for their solution: separable of variables and exact equations, integrating factors for linear equations, substitutions and transformations, method of undetermined coefficients, variation of parameters, Laplace transformations, series solutions, systems of differential equations, and phase-plane analysis.

Written homework will be assigned at the end of every class. There should be about 20-25 written homework assignments given during the semester. Each assignment will require at least an hour or two to complete. Homework will count for a significant part of a student's grade.

Instructor(s):  Dr. Anthony Giaquinto

Required text(s):  Nagle, R. Kent, Saff, Edward B., and Edward B. Snider. Fundamentals of Differential Equations. 9th ed. MyLab Math with Pearson e-Text, ISBN-13: 9780134764832

Prerequisites:  MATH 263 or MATH 263 concurrently

Course description:  This course is an introduction to the study of ordinary differential equations and their appplication to physical systems. Topics will include Solution of First-Order ODE's by analytical, graphical and numerical methods; Linear ODE's, Especially Second Order with Constant Coefficients; Undetermined Coefficients and Variation of Parameters; Series Solutions; Complex Numbers and Exponentials; Laplace Transform Methods; Non-linear Autonomous Systems: Critical Point Analysis and Phase Plane Diagrams.

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.

Instructor(s):  Mr. Frederic Mahieu

Required text(s):  A History of Mathematics, An Introduction (3rd Edition), Victor J. Katz ISBN-13: 978-0134689524 ISBN-10: 9780134689524

Textbook notes:  The required textbook above will be a (precious) base of discussion for our class, and the main resource for exercises. However, I’ll share with students copies of many other sources: source books, other popular history textbooks, and books about the Math Culture (mathematicians, numbers, applications of Math to Music, Art, and other fields).

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

Course description:  The purpose of this course is « quadri-dimensional »: 1. Give you a global knowledge of the History of Math (periods, mathematicians, concepts, numbers, theorems) that will be useful if you want to become a math teacher, a scientist or a researcher, but also if you are a math lover or if you are just curious about Math. The history of Math is fascinating, full of captivating anecdotes, and this class will help you understand the role of Math in the evolution of our society. 2. Dig deeper on some famous Math results, proofs and methods. Let’s do some Math in the style of mathematicians from the Antiquity to the 21st century! 3. Give you a Math Culture with the influence of Math on Art, Music, Architecture and other fields, in the past 2500 years. 4. Applications of Math to the real world: Finance, Meteorology, AI, Animated Movies, Environment, etc. We’ll use original source materials as much as possible to understand the spirit of mathematicians and the historical context behind the great discoveries in Math. The class will be about reading, discussing, studying, watching, doing, experimenting, interviewing historians/specialists, writing essays or presenting a research study. But most of it, it will be about having fun and learn great things about Math and its fascinating History.

Instructor(s):  Dr. Emmanuel Barron

Required text(s):  A First Course in Probability. Sheldon Ross, Pearson Publishing, 10th Edition, ISBN 978-0-13-475311-9

Textbook notes:  9th Edition is ok.

Prerequisites:  MATH263

Course description:  An introduction to probability, including random variables, mean, variance, and basic theorems such as the Law of Large Numbers and the Central Limit Theorem.

Instructor(s):  Dr. Anthony Giaquinto

Required text(s):  Abstract Algebra, Theory and Application, Thomas Judson http://abstract.ups.edu/

Prerequisites:  MATH 201 and MATH 212

Course description:  This course provides an introduction to abstract algebra. We will consider various algebraic structures including groups, rings, and fields, but will mainly focus on groups, with an emphasis throughout on their important role in various types of symmetry. Many of the abstract concepts will be considered only after first focusing on concrete examples as symmetry of planar figures, platonic solids as well as permutation groups and modular arithmetic. The theoretical part of the course will cover the basic structure theory: homomorphisms, subgroups, cosets, factor groups, and isomorphism theorems. Other topics will be introduced as time permits.

Instructor(s):  Dr. Aaron Lauve

Required text(s):  Strang, Gilbert. Linear Algebra and Its Applications. 4th edition. ISBN-13: 978-0030105678. Cengage Learning. 2006. Print.

Prerequisites:  Math 313 (or another proof-based course beyond Math 201).

Course description:  This course is a continuation of Math 212 - Linear Algebra. It's goal is move beyond the abstract theory and develop practical linear algebraic methods. This includes iterative methods for solving matrix equations and finding eigenvectors; important matrix factorizations used in representation theory, applied mathematics, engineering, statistics, and data science; principal component analysis; and so on.

Syllabus:  Assessments: fortnightly quizzes and homework, with some programming exercises; two in-term exams; and a final exam. Graduate students taking Math 415 will be given assessments commensurate with their standing; and will be responsible for presenting a lecture on an optional/applied topic of their choosing.

Instructor(s):  Dr. Tuyen Tran

Required text(s):  Introduction to Analysis - Maxwell Rosenlicht

Prerequisites:  Math 201, Math 212

Course description:  A rigorous treatment of properties and applications of real numbers and real-valued functions of a real variable. Topics include: metric spaces, sequences and their convergence, continuity and differentiability of functions. After the course, students will be expected to formulate mathematical arguments and proofs.

Instructor(s):  Rafal Goebel

Required text(s):  Saff and Snider, Fundamentals of Complex Analysis with Applications to Engineering, Science, and Mathematics, 3rd Edition.

Prerequisites:  MATH 264 and MATH 351

Course description:  Complex analysis is essential for studying real-life problems in sciences and engineering. The course is an introduction to complex analysis, starting from basic topics like complex numbers, analytic functions, and their integration and including selected more advanced topics and applications to, for example, electrical circuits, signal processing or to other areas of mathematics, for example linear algebra and differential equations. In the class, students will be expected to acquire proficiency in computational complex analysis as well as in reading, formulating, and understanding mathematical results and proofs involving complex analysis.

Instructor(s):  Peter Tingley

Required text(s):  Game Theory: An Introduction, Second Edition, by E. N. Barron, Wiley, 2013, ISBN 978-1-118-21693-4

Prerequisites:  MATH 162

Course description:  This is a mathematically rigorous introduction to the theory of games. Game theory is a branch of applied mathematics founded by John von Neumann with applications to economics, business, political science, optimization, differential equations, optimal transport, etc. It is the theory of finding optimal strategies in conflict or cooperative situations. It brings together most of undergraduate mathematics subjects to produce a subject which is important and fun to study.

Syllabus:  Two-person zero-sum games. Saddle points and mixed strategies. N-person non-zero sum games. Nash equilibria. Cooperative games with characteristic functions. Evolutionary population games.

Instructor(s):  Emily Peters

Required text(s):  not yet determined

Prerequisites:  MATH 313

Course description:  Representation theory is the study of groups, not as abstract algebraic objects, but in context: as symmetries of vector spaces (say, the plane or three-dimensional space), where they were first observed. We can then use the well-developed tools of linear algebra (say, matrices) to study groups! This course will be heavily motivated by examples, and we will build towards understanding applications of representation theory in physics and chemistry.

Instructor(s):  Dr. Aaron Lauve

Required text(s):  Strang, Gilbert. Linear Algebra and Its Applications. 4th edition. ISBN-13: 978-0030105678. Cengage Learning. 2006. Print.

Prerequisites:  Math 313 (or another proof-based course beyond Math 201).

Course description:  This course is a continuation of Math 212 - Linear Algebra. It's goal is move beyond the abstract theory and develop practical linear algebraic methods. This includes iterative methods for solving matrix equations and finding eigenvectors; important matrix factorizations used in representation theory, applied mathematics, engineering, statistics, and data science; principal component analysis; and so on.

Syllabus:  Assessments: fortnightly quizzes and homework, with some programming exercises; two in-term exams; and a final exam. Graduate students taking Math 415 will be given assessments commensurate with their standing; and will be responsible for presenting a lecture on an optional/applied topic of their choosing.

Instructor(s):  Dr. Tuyen Tran

Required text(s):  Introduction to Analysis - Maxwell Rosenlicht

Prerequisites:  Math 201, Math 212

Course description:  A rigorous treatment of properties and applications of real numbers and real-valued functions of a real variable. Topics include: metric spaces, sequences and their convergence, continuity and differentiability of functions. After the course, students will be expected to formulate mathematical arguments and proofs.

Instructor(s):  Peter Tingley

Required text(s):  Game Theory: An Introduction, Second Edition, by E. N. Barron, Wiley, 2013, ISBN 978-1-118-21693-4

Prerequisites:  MATH 162

Course description:  This is a mathematically rigorous introduction to the theory of games. Game theory is a branch of applied mathematics founded by John von Neumann with applications to economics, business, political science, optimization, differential equations, optimal transport, etc. It is the theory of finding optimal strategies in conflict or cooperative situations. It brings together most of undergraduate mathematics subjects to produce a subject which is important and fun to study.

Syllabus:  Two-person zero-sum games. Saddle points and mixed strategies. N-person non-zero sum games. Nash equilibria. Cooperative games with characteristic functions. Evolutionary population games.

Instructor(s):  Emily Peters

Required text(s):  not yet determined

Prerequisites:  MATH 313

Course description:  Representation theory is the study of groups, not as abstract algebraic objects, but in context: as symmetries of vector spaces (say, the plane or three-dimensional space), where they were first observed. We can then use the well-developed tools of linear algebra (say, matrices) to study groups! This course will be heavily motivated by examples, and we will build towards understanding applications of representation theory in physics and chemistry.

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

Instructor(s):  Swarnali Banerjee, Ph.D.

Required text(s):  Probability and Statistics for Engineering and the Sciences by Jay L. Devore.

Recommended text(s):  Essentials of Probability and Statistics for Engineers and Scientists by Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers and Keying Ye

Prerequisites:  MATH 162 or 132 (with grade of "C" or better).

Course description:  An introduction to statistical methodology and theory using the techniques of one-variable calculus. Topics include: experimental design, descriptive statistics, probability theory, sampling theory, inferential statistics, estimation theory, testing hypotheses, correlation theory, and regression.

Instructor(s):  Dr. Emmanuel Barron

Required text(s):  A First Course in Probability. Sheldon Ross, Pearson Publishing, 10th Edition, ISBN 978-0-13-475311-9

Textbook notes:  9th Edition is ok.

Prerequisites:  MATH263

Course description:  An introduction to probability, including random variables, mean, variance, and basic theorems such as the Law of Large Numbers and the Central Limit Theorem.

Instructor(s):  Dr. Xiaoli Kong

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.

Instructor(s):  Dr. Michael Perry

Required text(s):  Collett, David, Modelling Survival Data in Medical Research, 3rd. CRC Press, 2015 ISBN 978-1-4398-5678-9

Recommended text(s):  Allison, Paul D. Survival Analysis Using SAS: A Practical Guide 2nd, SAS Institute, 2010 Lee, Elisa and John Wang, Statistical Methods for Survival Data Analysis

Textbook notes:  The Allison textbook is a good resource for learning the SAS code. I have a pdf file for those preferring to use R, but it is not a comprehensive. There is no comprehensive book in R for Survival Analysis.

Additional notes:  STAT 308/408 recommend. There is significant regression analysis involved with this class.

Prerequisites:  STAT 203, STAT 335

Course description:  Time-to-event data, also referred to as survival data or failure-time data arise in situations where the actual response measurements are not known, but are known to be below or above a threshold or within an interval. This course focuses on methods for analyzing such data. We first consider descriptive methods for survival data including the survival function and its estimation using the Kaplan-Meier method and how to use and compare estimated survival functions. Then we discuss several important regression models for survival data: semi-parametric models such as proportional hazards regression models and parametric models including exponential, Weibull and log-logistic regression models. Using ideas not unlike those used in linear regression models we will describe techniques for model development, including selecting covariates, identifying influential and poorly fit subjects, and assessing overall goodness-of-fit. In this course, students will be required to analyze real-life data sets using the Minitab, R and/or SAS statistical packages.

Instructor(s):  Dr. Shuwen Lou

Required text(s):  Rosner, Bernard. Fundamentals of Biostatistics. 8th edition. Boston: Cengage Learning, 2015.

Prerequisites:  MATH 162 or 132; BIOL 102

Course description:  An introduction to statistical methods used in designing biological experiments and in data analysis. Topics include probability and sampling distribution, design of biological experiments and analysis of variance, regression and correlation, stochastic processes, and frequency distributions. Additionally, the course will include programming in R and analyzing R output. (Note: Students may not receive credit for both STAT 203 & 335.

Instructor(s):  Bret Longman

Required text(s): 

Prerequisites:  STAT 203 or STAT 335

Course description: 

Instructor(s):  Dr. Matthews

Required text(s): 

Prerequisites: 

Course description: 

Instructor(s):  Swarnali Banerjee, Ph.D.

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

Prerequisites:  MATH 263, MATH 212, MATH/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.

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:  None

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.

Instructor(s):  Dr. Michael Perry

Required text(s):  Collett, David, Modelling Survival Data in Medical Research, 3rd. CRC Press, 2015 ISBN 978-1-4398-5678-9

Recommended text(s):  Allison, Paul D. Survival Analysis Using SAS: A Practical Guide 2nd, SAS Institute, 2010 Lee, Elisa and John Wang, Statistical Methods for Survival Data Analysis

Textbook notes:  The Allison textbook is a good resource for learning the SAS code. I have a pdf file for those preferring to use R, but it is not a comprehensive. There is no comprehensive book in R for Survival Analysis.

Additional notes:  STAT 308/408 recommend. There is significant regression analysis involved with this class.

Prerequisites:  STAT 203, STAT 335

Course description:  Time-to-event data, also referred to as survival data or failure-time data arise in situations where the actual response measurements are not known, but are known to be below or above a threshold or within an interval. This course focuses on methods for analyzing such data. We first consider descriptive methods for survival data including the survival function and its estimation using the Kaplan-Meier method and how to use and compare estimated survival functions. Then we discuss several important regression models for survival data: semi-parametric models such as proportional hazards regression models and parametric models including exponential, Weibull and log-logistic regression models. Using ideas not unlike those used in linear regression models we will describe techniques for model development, including selecting covariates, identifying influential and poorly fit subjects, and assessing overall goodness-of-fit. In this course, students will be required to analyze real-life data sets using the Minitab, R and/or SAS statistical packages.

Instructor(s):  Swarnali Banerjee, Ph.D.

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 3-5 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 student 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.