## Spring 2017

#### MATH 125-01

### Epidemiology

**Days:**MWF**Meeting Time:**01:10 pm-02:10 pm**Room:**OLRI 101**Instructor:**Kelsey McDonald

**Notes:** *First day attendance required; ACTC students may register on December 2nd with permission of the instructor*

Epidemiology is the study of the distribution and determinants of disease and health in human populations and the application of this understanding to the solution of public health problems. Topics include measurement of disease and health, the outbreak and spread of disease, reasoning about cause and effect, analysis of risk, detection and classification, and the evaluation of trade-offs. The course is designed to fulfill and extend the professional community's consensus definition of undergraduate epidemiology. In addition to the techniques of modern epidemiology, the course emphasizes the historical evolution of ideas of causation, treatment, and prevention of disease. The course is a required component of the concentration in Community and Global Health. (4 credits)

#### MATH 135-01

### Applied Multivariable Calculus I

**Days:**TR**Meeting Time:**08:00 am-09:30 am**Room:**OLRI 243**Instructor:**Kristin Heysse

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

This course focuses on calculus useful for applied work in the natural and social sciences. There is a strong emphasis on developing scientific computing and mathematical modeling skills. The topics include functions as models of data, differential calculus of functions of one and several variables, integration, differential equations, and estimation techniques. Case studies are drawn from varied areas, including biology, chemistry, economics, and physics. Every semester. (4 credits)

#### MATH 135-02

### Applied Multivariable Calculus I

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**OLRI 243**Instructor:**Kristin Heysse

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

This course focuses on calculus useful for applied work in the natural and social sciences. There is a strong emphasis on developing scientific computing and mathematical modeling skills. The topics include functions as models of data, differential calculus of functions of one and several variables, integration, differential equations, and estimation techniques. Case studies are drawn from varied areas, including biology, chemistry, economics, and physics. Every semester. (4 credits)

#### MATH 137-02

### Applied Multivariable Calculus II

**Days:**MWF**Meeting Time:**01:10 pm-02:10 pm**Room:**NEILL 400**Instructor:**Lori Ziegelmeier

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences at a more rigorous level than Math 135. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, and differential equations, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle. Attention is given to both symbolic and numerical computing. Every semester. (4 credits)

#### MATH 137-03

### Applied Multivariable Calculus II

**Days:**MWF**Meeting Time:**02:20 pm-03:20 pm**Room:**NEILL 400**Instructor:**Lori Ziegelmeier

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences at a more rigorous level than Math 135. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, and differential equations, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle. Attention is given to both symbolic and numerical computing. Every semester. (4 credits)

#### MATH 155-01

### Intro to Statistical Modeling

**Days:**MWF**Meeting Time:**09:40 am-10:40 am**Room:**OLRI 241**Instructor:**Christina Knudson

**Notes:** *First day attendance required; ACTC students may register on December 2nd with permission of the instructor*

An introductory statistics course with an emphasis on multivariate modeling. Topics include descriptive statistics, experiment and study design, probability, hypothesis testing, multivariate regression, single and multi-way analysis of variance, logistic regression. (4 credits)

#### MATH 155-02

### Intro to Statistical Modeling

**Days:**MWF**Meeting Time:**10:50 am-11:50 am**Room:**OLRI 241**Instructor:**Vittorio Addona

**Notes:** *First day attendance required; ACTC students may register on December 2nd with permission of the instructor*

An introductory statistics course with an emphasis on multivariate modeling. Topics include descriptive statistics, experiment and study design, probability, hypothesis testing, multivariate regression, single and multi-way analysis of variance, logistic regression. (4 credits)

#### MATH 155-03

### Intro to Statistical Modeling

**Days:**MWF**Meeting Time:**12:00 pm-01:00 pm**Room:**OLRI 241**Instructor:**Vittorio Addona

**Notes:** *First day attendance required; ACTC students may register on December 2nd with permission of the instructor*

An introductory statistics course with an emphasis on multivariate modeling. Topics include descriptive statistics, experiment and study design, probability, hypothesis testing, multivariate regression, single and multi-way analysis of variance, logistic regression. (4 credits)

#### MATH 155-04

### Intro to Statistical Modeling

**Days:**MWF**Meeting Time:**01:10 pm-02:10 pm**Room:**OLRI 243**Instructor:**Christina Knudson

**Notes:** *First day attendance required; ACTC students may register on December 2nd with permission of the instructor*

#### MATH 155-05

### Intro to Statistical Modeling

**Days:**MWF**Meeting Time:**02:20 pm-03:20 pm**Room:**OLRI 243**Instructor:**Vittorio Addona

**Notes:** *First day attendance required; ACTC students may register on December 2nd with permission of the instructor*

#### MATH 236-02

### Linear Algebra

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 243**Instructor:**Nicole Bridgland

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

This course blends mathematical computation, theory, abstraction, and application. It starts with systems of linear equations and grows into the study of matrices, vector spaces, linear independence, dimension, matrix decompositions, linear transformations, eigenvectors, and their applications. (4 credits).

#### MATH 237-01

### Applied Multivariable Calculus III

**Days:**MWF**Meeting Time:**01:10 pm-02:10 pm**Room:**OLRI 241**Instructor:**Thomas Halverson

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

For Fall 2014 this course will be offered as Multivariable Calculus, with the following description:

Differentiation and integration of functions of two and three variables. Applications of these, including optimization techniques. Also includes introduction to vector calculus, with treatment of vector fields, line and surface integrals, and Green’s Theorem. (4 credits)

For Spring 2015 this course will be offered as Applied Multivariable Calculus III, with the following description:

This course focuses on calculus useful for the mathematical and physical sciences. Topics include: scalar and vector-valued functions and derivatives; parameterization and integration over regions, curves, and surfaces; the divergence theorem; and Taylor series. Attention is given to both symbolic and numerical computing. Applications drawn from the natural sciences, probability, and other areas of mathematics. Every semester. (4 credits)

#### MATH 237-02

### Applied Multivariable Calculus III

**Days:**MWF**Meeting Time:**02:20 pm-03:20 pm**Room:**OLRI 150**Instructor:**Thomas Halverson

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

For Fall 2014 this course will be offered as Multivariable Calculus, with the following description:

Differentiation and integration of functions of two and three variables. Applications of these, including optimization techniques. Also includes introduction to vector calculus, with treatment of vector fields, line and surface integrals, and Green’s Theorem. (4 credits)

For Spring 2015 this course will be offered as Applied Multivariable Calculus III, with the following description:

This course focuses on calculus useful for the mathematical and physical sciences. Topics include: scalar and vector-valued functions and derivatives; parameterization and integration over regions, curves, and surfaces; the divergence theorem; and Taylor series. Attention is given to both symbolic and numerical computing. Applications drawn from the natural sciences, probability, and other areas of mathematics. Every semester. (4 credits)

#### MATH 253-01

### Statistical Computing and Machine Learning

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 258**Instructor:**Daniel Kaplan

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

An introduction to multivariate statistical analysis. Emphasizes rationales, applications, and interpretations using advanced statistical software. Examples drawn primarily from economics, education, psychology, sociology, political science, biology and medicine. Topics may include: simple/multiple regression, one-way/two-way ANOVA, logistic regression, discriminant analysis, multivariable correlation. Additional topics may include analysis of covariance, factor analysis, cluster analysis. (4 credits)

#### MATH 279-01

### Discrete Mathematics

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 241**Instructor:**Andrew Beveridge

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

An introduction to the basic techniques and methods used in combinatorial problem-solving. Includes basic counting principles, induction, logic, recurrence relations, and graph theory. (4 credits)

#### MATH 312-01

### Differential Equations

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**OLRI 258**Instructor:**Chad Higdon-Topaz

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

Introduction to the theory and application of differential equations. Solving linear and first-order systems using algebra, linear algebra, and complex numbers. Using computers to solve equations both symbolically and numerically and to visualize the solutions. Qualitative methods for nonlinear dynamical systems. Applications to diverse areas of modeling. (4 credits)

#### MATH 354-01

### Probability

**Days:**TR**Meeting Time:**03:00 pm-04:30 pm**Room:**OLRI 241**Instructor:**Alicia Johnson

**Notes:** *First day attendance required; ACTC students may register on December 2nd with permission of the instructor*

An introduction to probability theory and application. Fundamental probability concepts include: sample spaces, combinatorics, conditional probability, independence, random variables, probability distributions, expectation, variance, moment-generating functions, and limit theorems. Special course topics vary and may include: computer simulation, stochastic processes, and statistical inference. (4 credits)

#### MATH 365-01

### Computational Linear Algebra

**Days:**TR**Meeting Time:**08:00 am-09:30 am**Room:**OLRI 245**Instructor:**David Shuman

**Notes:** *Cross-listed with COMP 365-01; ACTC Students may register on December 2nd with permission of the instructor*

This course covers a central point of contact between mathematics and computer science. Many of the computational techniques important in science, commerce, and statistics are based on concepts from linear algebra: subspaces, projection, matrix decompositions, etc. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing; solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, Monte Carlo techniques. Applications throughout the sciences and statistics. Course is cross-listed with Computer Science 365. (4 credits).

#### MATH 365-02

### Computational Linear Algebra

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**OLRI 245**Instructor:**David Shuman

**Notes:** *Cross-listed with COMP 365-02; ACTC Students may register on December 2nd with permission of the instructor*

This course covers a central point of contact between mathematics and computer science. Many of the computational techniques important in science, commerce, and statistics are based on concepts from linear algebra: subspaces, projection, matrix decompositions, etc. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing; solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, Monte Carlo techniques. Applications throughout the sciences and statistics. Course is cross-listed with Computer Science 365. (4 credits).

#### MATH 376-01

### Algebraic Structures

**Days:**TR**Meeting Time:**03:00 pm-04:30 pm**Room:**OLRI 205**Instructor:**Ian Whitehead

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

Introduction to abstract algebraic theory with emphasis on finite groups, rings, fields, constructibility, introduction to Galois theory. (4 credits)

#### MATH 378-01

### Complex Analysis

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 245**Instructor:**Chad Higdon-Topaz

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

A course in the study of functions of complex numbers, a topic which touches fields as varied as number theory, applied mathematics, physics, engineering, algebraic geometry, and more. We cover: geometry and algebra of complex numbers; complex functions; differentiation and integration, including the CauchyRiemann equations, Cauchy's theorem, and the Cauchy integral formula; Taylor series, Laurent series, and the Residue Theorem. Throughout, we emphasize complex functions as transformations of the plane, and also make a strong

connection to applications. This course is appropriate both for students with an interest and background in theoretical mathematics and proof, and students whose primary interest is the application of mathematics to other fields. (4 credits)

#### MATH 454-01

### Bayesian Statistics

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 205**Instructor:**Alicia Johnson

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

Bayesian statistics, an alternative to the traditional frequentist approach taken in our other statistics courses, is playing an increasingly integral role in modern statistics. Highlighted by Nate Silver of fivethirtyeight.com and Baseball Prospectus fame, Bayesian statistics has even reached a popular audience. This course explores the Bayesian philosophy, the Bayesian approach to statistical analysis, Bayesian computing, as well as both sides of the frequentist versus Bayesian debate. Topics include Bayes’ Theorem, prior and posterior probability distributions, Bayesian regression, Bayesian hierarchical models, and an introduction to Markov chain Monte Carlo techniques. (4 credits)

#### MATH 471-01

### Topology

**Days:**MWF**Meeting Time:**09:40 am-10:40 am**Room:**OLRI 245**Instructor:**Lori Ziegelmeier

**Notes:** *ACTC students may register on December 2nd with permission of the instructor*

A course in both theoretical and computational mathematics. It covers fundamental ideas from point set topology-continuity, convergence, and connectedness-as well as selected topics from algebraic topology the fundamental group, elementary homotopy theory, and homology. This theoretical framework provides a backbone to understand new advances in computational topology via persistent homology. Applications are chosen from diverse fields

such as biological aggregations, medicine, image processing, signal processing, and sensor networks. This course counts towards the capstone requirement. (4 credits)

#### MATH 479-01

### Network Science

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**OLRI 205**Instructor:**Andrew Beveridge

**Notes:** *Cross-listed with COMP 479-01; ACTC Students may register on December 2nd with permission of the instructor*

The modern Information Age has produced a wealth of data about the complex networks that tie us together. In response, the field of Network Science has arisen, bringing together mathematics, computer science, sociology, biology, economics and other fields. This course will explore the fundamental questions and the mathematical tools of Network Science. This includes: the structure of complex networks, including connectedness, centrality and “long tails”; community detection; random/strategic models for network formation; diffusion/contagion and “tipping points” on networks; and algorithms for analyzing complex networks. Cross-listed with Computer Science 479. (4 credits)

## Fall 2016

#### MATH 125-01

### Epidemiology

**Days:**MWF**Meeting Time:**12:00 pm-01:00 pm**Room:**OLRI 241**Instructor:**Vittorio Addona

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

Epidemiology is the study of the distribution and determinants of disease and health in human populations and the application of this understanding to the solution of public health problems. Topics include measurement of disease and health, the outbreak and spread of disease, reasoning about cause and effect, analysis of risk, detection and classification, and the evaluation of trade-offs. The course is designed to fulfill and extend the professional community's consensus definition of undergraduate epidemiology. In addition to the techniques of modern epidemiology, the course emphasizes the historical evolution of ideas of causation, treatment, and prevention of disease. The course is a required component of the concentration in Community and Global Health. (4 credits)

#### MATH 135-01

### Applied Multivariable Calculus I

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**NEILL 400**Instructor:**Chad Higdon-Topaz

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

This course focuses on calculus useful for applied work in the natural and social sciences. There is a strong emphasis on developing scientific computing and mathematical modeling skills. The topics include functions as models of data, differential calculus of functions of one and several variables, integration, differential equations, and estimation techniques. Case studies are drawn from varied areas, including biology, chemistry, economics, and physics. Every semester. (4 credits)

#### MATH 135-02

### Applied Multivariable Calculus I

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**NEILL 400**Instructor:**Chad Higdon-Topaz

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

#### MATH 135-03

### Applied Multivariable Calculus I

**Days:**TR**Meeting Time:**03:00 pm-04:30 pm**Room:**OLRI 205**Instructor:**Lori Ziegelmeier

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

#### MATH 137-01

### Applied Multivariable Calculus II

**Days:**MWF**Meeting Time:**09:40 am-10:40 am**Room:**OLRI 241**Instructor:**Thomas Halverson

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences at a more rigorous level than Math 135. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, and differential equations, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle. Attention is given to both symbolic and numerical computing. Every semester. (4 credits)

#### MATH 137-02

### Applied Multivariable Calculus II

**Days:**MWF**Meeting Time:**10:50 am-11:50 am**Room:**OLRI 241**Instructor:**Thomas Halverson

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

#### MATH 137-03

### Applied Multivariable Calculus II

**Days:**TR**Meeting Time:**03:00 pm-04:30 pm**Room:**OLRI 243**Instructor:**Elise Delmas

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

#### MATH 155-01

### Intro to Statistical Modeling

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**OLRI 241**Instructor:**Alicia Johnson

**Notes:** *First day attendance required; ACTC students may register on April 29th with permission of the instructor*

#### MATH 155-02

### Intro to Statistical Modeling

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 241**Instructor:**Alicia Johnson

**Notes:** *First day attendance required; ACTC students may register on April 29th with permission of the instructor*

#### MATH 155-03

### Intro to Statistical Modeling

**Days:**TR**Meeting Time:**03:00 pm-04:30 pm**Room:**OLRI 241**Instructor:**Alicia Johnson

**Notes:** *First day attendance required; ACTC students may register on April 29th with permission of the instructor*

#### MATH 155-04

### Intro to Statistical Modeling

**Days:**MWF**Meeting Time:**01:10 pm-02:10 pm**Room:**OLRI 243**Instructor:**Christina Knudson

**Notes:** *First day attendance required; ACTC students may register on April 29th with permission of the instructor*

#### MATH 155-05

### Intro to Statistical Modeling

**Days:**MWF**Meeting Time:**02:20 pm-03:20 pm**Room:**OLRI 243**Instructor:**Christina Knudson

**Notes:** *First day attendance required; ACTC students may register on April 29th with permission of the instructor*

#### MATH 194-01

### Thinking Like an Engineer

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**MAIN 111**Instructor:**Flath, Michelfelder

**Notes:** *First Year Course only; cross-listed with PHIL 194-01* From driverless cars to wearable computers, from microwave ovens to mobile phones and tabletop robots, we all live and think in an environment saturated by the products of engineering thinking. But, what does it mean to think? And what does it mean to think like an engineer? In this course, team-taught between a mathematician with a background in engineering and a philosopher of technology, you will have an opportunity to explore questions such as these. The course will be grounded in an emerging understanding of engineering as an interdisciplinary field, where design problems are not solely technical, but are inseparable from ethical, social, political, economic, and historical dimensions. We will begin the course with a reading about engineering by the Spanish philosopher Ortega y Gasset, and end by looking at debates over engineering for human enhancement. In between, you’ll have the opportunity to read and discuss works by both philosophers and engineers. You’ll learn how values can be unintentionally embedded into engineered objects that reinforce gender and other stereotypes, but can also be consciously embedded for the aims of social justice and sustainability. You will be making arguments and also be making things, including a team-developed engineering project. Your path in this course will be illuminated by discussions about electrical power, solar energy, and lightbulb design. All students are welcome, both those who are interested in pursuing their academic interests in design, engineering, ethics, and/or philosophy, or those who want to better understand the engineered world as a consumer, citizen, or simply as a reflective human being.

#### MATH 194-02

### Political Participation: Politics of Mathematics and Elections

**Days:**TR**Meeting Time:**03:00 pm-04:30 pm**Room:**CARN 06A**Instructor:**Dolan, Saxe

**Notes:** *Cross-listed with POLI 202-01* It’s almost fall 2016 and the presidential election is looking an exciting one! Who else is up for election? How do elections work in the U.S. and in other democracies? What is meant by a ‘representative’ democracy? How is it decided how many Congressional representatives each state has? What are the costs and benefits of political participation? This course will focus on the various ways in which mathematics and political science interact. Topics covered will include the role of elections and representative government in the United States, comparison of electoral systems used around the world, the apportionment problem, redistricting and gerrymandering, weighted voting systems and voting power, the costs and benefits associated with political participation, and predicting electoral outcomes. Work during the semester will include some ‘math’ problems (associated, for example, with weighted voting); student presentations on Congressional races that we will follow leading up to election day; and several short written assignments. NOTE: Course counts for math/natural science general distribution if registered for as MATH 194-02 and social science general distribution if registered for as POLI 202.

#### MATH 236-01

### Linear Algebra

**Days:**MWF**Meeting Time:**09:40 am-10:40 am**Room:**NEILL 304**Instructor:**David Shuman

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

This course blends mathematical computation, theory, abstraction, and application. It starts with systems of linear equations and grows into the study of matrices, vector spaces, linear independence, dimension, matrix decompositions, linear transformations, eigenvectors, and their applications. (4 credits).

#### MATH 236-02

### Linear Algebra

**Days:**MWF**Meeting Time:**10:50 am-11:50 am**Room:**NEILL 304**Instructor:**David Shuman

**Notes:** *ACTC students may register on Aprilg 29th with permission of the instructor*

This course blends mathematical computation, theory, abstraction, and application. It starts with systems of linear equations and grows into the study of matrices, vector spaces, linear independence, dimension, matrix decompositions, linear transformations, eigenvectors, and their applications. (4 credits).

#### MATH 237-01

### Applied Multivariable Calculus III

**Days:**MWF**Meeting Time:**02:20 pm-03:20 pm**Room:**NEILL 304**Instructor:**David Ehren

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

For Fall 2014 this course will be offered as Multivariable Calculus, with the following description:

Differentiation and integration of functions of two and three variables. Applications of these, including optimization techniques. Also includes introduction to vector calculus, with treatment of vector fields, line and surface integrals, and Green’s Theorem. (4 credits)

For Spring 2015 this course will be offered as Applied Multivariable Calculus III, with the following description:

This course focuses on calculus useful for the mathematical and physical sciences. Topics include: scalar and vector-valued functions and derivatives; parameterization and integration over regions, curves, and surfaces; the divergence theorem; and Taylor series. Attention is given to both symbolic and numerical computing. Applications drawn from the natural sciences, probability, and other areas of mathematics. Every semester. (4 credits)

#### MATH 237-02

### Applied Multivariable Calculus III

**Days:**MWF**Meeting Time:**03:30 pm-04:30 pm**Room:**NEILL 304**Instructor:**David Ehren

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

For Fall 2014 this course will be offered as Multivariable Calculus, with the following description:

#### MATH 253-01

### Statistical Computing and Machine Learning

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 258**Instructor:**Daniel Kaplan

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

An introduction to multivariate statistical analysis. Emphasizes rationales, applications, and interpretations using advanced statistical software. Examples drawn primarily from economics, education, psychology, sociology, political science, biology and medicine. Topics may include: simple/multiple regression, one-way/two-way ANOVA, logistic regression, discriminant analysis, multivariable correlation. Additional topics may include analysis of covariance, factor analysis, cluster analysis. (4 credits)

#### MATH 279-01

### Discrete Mathematics

**Days:**MWF**Meeting Time:**09:40 am-10:40 am**Room:**NEILL 400**Instructor:**Andrew Beveridge

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

An introduction to the basic techniques and methods used in combinatorial problem-solving. Includes basic counting principles, induction, logic, recurrence relations, and graph theory. (4 credits)

#### MATH 279-02

### Discrete Mathematics

**Days:**MWF**Meeting Time:**10:50 am-11:50 am**Room:**NEILL 400**Instructor:**Andrew Beveridge

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

An introduction to the basic techniques and methods used in combinatorial problem-solving. Includes basic counting principles, induction, logic, recurrence relations, and graph theory. (4 credits)

#### MATH 312-01

### Differential Equations

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**OLRI 243**Instructor:**Daniel Flath

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

Introduction to the theory and application of differential equations. Solving linear and first-order systems using algebra, linear algebra, and complex numbers. Using computers to solve equations both symbolically and numerically and to visualize the solutions. Qualitative methods for nonlinear dynamical systems. Applications to diverse areas of modeling. (4 credits)

#### MATH 354-01

### Probability

**Days:**MWF**Meeting Time:**10:50 am-11:50 am**Room:**OLRI 243**Instructor:**Christina Knudson

**Notes:** *First day attendance required; ACTC students may register on April 29th with permission of the instructor*

An introduction to probability theory and application. Fundamental probability concepts include: sample spaces, combinatorics, conditional probability, independence, random variables, probability distributions, expectation, variance, moment-generating functions, and limit theorems. Special course topics vary and may include: computer simulation, stochastic processes, and statistical inference. (4 credits)

#### MATH 361-01

### Theory of Computation

**Days:**MWF**Meeting Time:**02:20 pm-03:20 pm**Room:**OLRI 241**Instructor:**Susan Fox

**Notes:** *Any Sophmore, Junior, or Senior who is a declared Mathematics or AMS major, and has the prereqs, should be able to register without instructor signature; cross-listed with COMP 261-01; first day attendance required; ACTC students may register on April 29th with permission of the instructor*

A discussion of the basic theoretical foundations of computation as embodied in formal models and descriptions. The course will cover finite state automata, regular expressions, formal languages, Turing machines, computability and unsolvability, and the theory of computational complexity. Introduction to alternate models of computation and recursive function theory. (4 credits)

#### MATH 377-01

### Real Analysis

**Days:**TR**Meeting Time:**01:20 pm-02:50 pm**Room:**CARN 06A**Instructor:**Karen Saxe

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

Basic theory for the real numbers and the notions of limit, continuity, differentiation, integration, convergence, uniform convergence, and infinite series. Additional topics may include metric and normed linear spaces, point set topology, analytic number theory, Fourier series. Fall semester. (4 credits)

#### MATH 379-01

### Combinatorics

**Days:**MWF**Meeting Time:**02:20 pm-03:20 pm**Room:**OLRI 101**Instructor:**Andrew Beveridge

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

Advanced counting techniques. Topics in graph theory, combinatorics, graph algorithms, and generating functions. Applications to other areas of mathematics as well as modeling, operations research, computer science and the social sciences. Odd numbered fall semesters. (4 credits)

#### MATH 432-01

### Mathematical Modeling

**Days:**TR**Meeting Time:**03:00 pm-04:30 pm**Room:**OLRI 256**Instructor:**Chad Higdon-Topaz

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

Draws on the student's general background in mathematics to construct models for problems arising from such diverse areas as the physical sciences, life sciences, political science, economics, and computing. Emphasis will be on the design, analysis, accuracy, and appropriateness of a model for a given problem. Case studies will be used extensively. Specific mathematical techniques will vary with the instructor and student interest. This course counts toward the capstone requirement. (4 credits)

#### MATH 437-01

### Topics in Applied Math

**Days:**TR**Meeting Time:**09:40 am-11:10 am**Room:**OLRI 245**Instructor:**David Shuman

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

Topics in applied mathematics chosen from: Fourier analysis; partial differential equations; wavelets; signal processing; time-frequency analysis; stochastic processes; optimization; computational geometry; and more. Topics are examined in theoretical and applied contexts, and from analytical and computational viewpoints. This course counts toward the capstone requirement.

(4 credits)

#### MATH 453-01

### Survival Analysis

**Days:**MWF**Meeting Time:**09:40 am-10:40 am**Room:**OLRI 245**Instructor:**Vittorio Addona

**Notes:** *ACTC students may register on April 29th with permission of the instructor*

Survival analysis refers to a set of methods used for modeling "timetoevent" or "duration" data. In many studies, the outcome of interest is the time between between events (e.g. onset of Alzheimer's until death, time unlit default on a loan, unemployment duration, mariage duration, removaltorecurrence of a tumor, emergency room length of stay). Survival analysis evolved from a practical reality: the precise values of data are often unknown. We will introduce the concepts of censoring and truncation, and discuss the KaplanMeier curve,

parametric regression models, Cox's proportional hazards model, and timevarying covariates. The course will have an applied focus. Examples may be drawn from a variety of fields including, but not restricted to, medicine, economics, sociology, and political science. The course will count toward completion of the concentration in Community and Global Health. This

course counts toward the capstone requirement.