Mathematics and Statistics Classes

Spring 2018 Fall 2018 Spring 2019

Spring 2018

Number / Section	Name	Days	Time	Room	Instructor	Avail. / Max.
MATH 112-01	Introduction to Data Science	Days: TR	Time: 08:00 am-09:30 am	Room: OLRI 254	Instructor: Shilad Sen	Avail./Max.: Closed -2 / 24
Cross-listed with COMP 112-01; first day attendance required; ACTC students may register on December 1st with permission of instructor; limit reflects saving 2 seats for first year students Details This course provides an introduction to the handling, analysis, and interpretation of the big datasets now routinely being collected in science, commerce, and government. Students achieve facility with a sophisticated, technical computing environment. The course aligns with techniques being used in several courses in the natural and social sciences, statistics, and mathematics. The course is intended to be accessible to all students, regardless of background. General Education Requirements: Quantitative Thinking Q2 Distribution Requirements: Natural science and mathematics Course Materials
MATH 135-01	Applied Multivariable Calculus I	Days: MWF	Time: 09:40 am-10:40 am	Room: NEILL 304	Instructor: Kristin Heysse	Avail./Max.: Closed -1 / 32
ACTC students may register on December 1st with permission of instructor; limits reflects saving eight seats for first years students Details 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. Applications are drawn from varied areas, including biology, chemistry, economics, and physics. Prerequisite(s): None. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 135-02	Applied Multivariable Calculus I	Days: MWF	Time: 12:00 pm-01:00 pm	Room: OLRI 241	Instructor: David Ehren	Avail./Max.: Closed -1 / 32
ACTC students may register on December 1st with permission of instructor; limit reflects saving 8 seats for first year students. Details 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. Applications are drawn from varied areas, including biology, chemistry, economics, and physics. Prerequisite(s): None. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-01	Applied Multivariable Calculus II	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 254	Instructor: William Mitchell	Avail./Max.: 0 / 32
Limit reflects saving eight seats for first year students Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-02	Applied Multivariable Calculus II	Days: MWF	Time: 10:50 am-11:50 am	Room: OLRI 254	Instructor: William Mitchell	Avail./Max.: 2 / 32
ACTC students may register on December 1st with permission of instructor; limit reflects saving eight seats for first year students. Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-03	Applied Multivariable Calculus II	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 241	Instructor: Joseph Benson	Avail./Max.: 6 / 32
ACTC students may register on December 1st with permission of instructor; limit reflects saving eight seats for first year students Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-01	Intro to Statistical Modeling	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 254	Instructor: Alicia Johnson	Avail./Max.: Closed -2 / 28
First day attendance required; ACTC students may register on December 1st with permission of instructor; limit reflects saving six seats for first year students Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-02	Intro to Statistical Modeling	Days: TR	Time: 03:00 pm-04:30 pm	Room: OLRI 254	Instructor: Alicia Johnson	Avail./Max.: Closed 0 / 28
First day attendance required; ACTC students may register on December 1st with permission of instructor; limit reflects saving six seats for first year students Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-03	Intro to Statistical Modeling	Days: TR	Time: 08:00 am-09:30 am	Room: NEILL 304	Instructor: Lisa Lendway	Avail./Max.: Closed 1 / 28
ACTC students may register on December 1st with permission of instructor; limit reflects saving six seats for first year students Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-04	Intro to Statistical Modeling	Days: TR	Time: 09:40 am-11:10 am	Room: NEILL 304	Instructor: Lisa Lendway	Avail./Max.: Closed 1 / 28
ACTC students may register on December 1st with permission of instructor; limit reflects saving six seats for first year students Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 236-01	Linear Algebra	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 241	Instructor: Thomas Halverson	Avail./Max.: Closed 0 / 32
ACTC students may register on December 1st with permission of instructor Details Linear algebra is one of the pillars of mathematics, both pure and applied. Linear relations can be used to model phenomena from numerous disciplines in the mathematical sciences, physical sciences, social sciences, engineering, and computer science. This introduction to linear algebra 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, linear transformations, orthogonality and projections, eigenvectors, and their applications. The resulting linear algebraic framework is a flexible and powerful way to approach multidimensional problems. Prerequisite(s): MATH 279 or MATH 137, or with permission of instructor, MATH 135 General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 236-02	Linear Algebra	Days: MWF	Time: 10:50 am-11:50 am	Room: OLRI 241	Instructor: Thomas Halverson	Avail./Max.: Closed 1 / 32
ACTC students may register on December 1st with permission of instructor Details Linear algebra is one of the pillars of mathematics, both pure and applied. Linear relations can be used to model phenomena from numerous disciplines in the mathematical sciences, physical sciences, social sciences, engineering, and computer science. This introduction to linear algebra 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, linear transformations, orthogonality and projections, eigenvectors, and their applications. The resulting linear algebraic framework is a flexible and powerful way to approach multidimensional problems. Prerequisite(s): MATH 279 or MATH 137, or with permission of instructor, MATH 135 General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 237-01	Applied Multivariable Calculus III	Days: MWF	Time: 09:40 am-10:40 am	Room: NEILL 400	Instructor: Joseph Benson	Avail./Max.: 2 / 32
ACTC students may register on December 1st with permission of instructor; limit reflects saving eight seats for first year students Details 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. Prerequisite(s): MATH 137 or a strong high school calculus at the level of AP calculus with a BC score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 237-02	Applied Multivariable Calculus III	Days: MWF	Time: 10:50 am-11:50 am	Room: NEILL 400	Instructor: Joseph Benson	Avail./Max.: Closed 4 / 32
ACTC students may register on December 1st with permission of instructor;limit reflects saving eight seats for first year students Details 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. Prerequisite(s): MATH 137 or a strong high school calculus at the level of AP calculus with a BC score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 253-01	Statistical Computing and Machine Learning	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 258	Instructor: Alicia Johnson	Avail./Max.: Closed -1 / 24
First day attendance required; ACTC students may register on December 1st with permission of instructor Details Statistics as applied to "big data," including large numbers of variables. The linear and logistic modeling techniques from Math 155 will be augmented with computer-based methods of data exploration, visualization, data mining, supervised and unsupervised clustering, and other techniques central to machine learning. The course also deals with methods of combining and organizing data from diverse sources and the high-level statistical computer programming needed to carry out sophisticated data analysis and graphical presentation. Prerequisite(s): MATH 155 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 253-02	Statistical Computing and Machine Learning	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 245	Instructor: Lisa Lendway	Avail./Max.: Closed 0 / 24
ACTC students may register on December 1st with permission of instructor Details Statistics as applied to "big data," including large numbers of variables. The linear and logistic modeling techniques from Math 155 will be augmented with computer-based methods of data exploration, visualization, data mining, supervised and unsupervised clustering, and other techniques central to machine learning. The course also deals with methods of combining and organizing data from diverse sources and the high-level statistical computer programming needed to carry out sophisticated data analysis and graphical presentation. Prerequisite(s): MATH 155 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 279-01	Discrete Mathematics	Days: MWF	Time: 01:10 pm-02:10 pm	Room: OLRI 254	Instructor: Kristin Heysse	Avail./Max.: Closed 6 / 31
ACTC students may register on December 1st with permission of instructor Details Discrete mathematics studies collections of distinct, separate objects and is complementary to calculus (which studies continuous phenomena). This course introduces techniques for analyzing arrangements of objects and the relationships between them. The material emphasizes problem solving and logical argumentation, rather than computation. Topics include basic counting principles, induction, logic, recurrence relations, number theory, and graph theory. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 279-02	Discrete Mathematics	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 254	Instructor: Kristin Heysse	Avail./Max.: Closed 3 / 30
ACTC students may register on December 1st with permission of instructor Details Discrete mathematics studies collections of distinct, separate objects and is complementary to calculus (which studies continuous phenomena). This course introduces techniques for analyzing arrangements of objects and the relationships between them. The material emphasizes problem solving and logical argumentation, rather than computation. Topics include basic counting principles, induction, logic, recurrence relations, number theory, and graph theory. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 312-01	Differential Equations	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 250	Instructor: William Mitchell	Avail./Max.: Closed -3 / 28
ACTC students may register on December 1st with permission of instructor Details 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. Prerequisite(s): MATH 236 and MATH 237 General Education Requirements: Writing WP Distribution Requirements: Natural science and mathematics Course Materials
MATH 313-01	Advanced Symbolic Logic	Days: TR	Time: 01:20 pm-02:50 pm	Room: MAIN 002	Instructor: Janet Folina	Avail./Max.: 3 / 15
Cross-listed with PHIL 313-01 Details A second course in symbolic logic which extends the methods of logic. A main purpose of this course is to study logic itself-to prove things about the system of logic learned in the introductory course. This course is thus largely logic about logic. Topics include second order logic and basic set theory; soundness, consistency and completeness of first order logic; incompleteness of arithmetic; Turing computability; modal logic; and intuitionistic logic. Prerequisite(s): PHIL 111 or MATH 279 or permission of instructor. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 354-01	Probability	Days: MWF	Time: 03:30 pm-04:30 pm	Room: OLRI 243	Instructor: Brittany Baker	Avail./Max.: Closed 0 / 24
ACTC students may register on December 1st with permission of instructor Details 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. Prerequisite(s): MATH 237; or MATH 137 and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 361-01	Theory of Computation	Days: MWF	Time: 01:10 pm-02:10 pm	Room: OLRI 241	Instructor: Daniel Kluver	Avail./Max.: 5 / 30
Cross-listed with COMP 261-01; permission of instructor required; first day attendance required; ACTC students may register on December 1st with permission of instructor Details This course examines the theoretical foundations of computation. It explores different mathematical models that try to formalize our informal notion of an algorithm. Models include finite automata, regular expressions, grammars, and Turing machines. The course also discusses ideas about what can and cannot be computed. In addition, the course explores the basics of complexity theory, examining broad categories of problems and their algorithms, and their efficiency. The focus is on the question of P versus NP, and the NP-complete set. Prerequisite(s): COMP 124 and MATH 279, or permission of instructor General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 365-01	Computational Linear Algebra	Days: TR	Time: 08:00 am-09:30 am	Room: OLRI 245	Instructor: Lori Ziegelmeier	Avail./Max.: 8 / 24
Cross-listed with COMP 365-01, first day attendance required; ACTC students may register on December 1st with permission of instructor Details A mix of applied linear algebra and numerical analysis, 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, such as subspaces, projections, and matrix decompositions. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing. These include solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, eigenvalue and singular value decompositions, and compression. Applications throughout the natural sciences, social sciences, statistics, and computer science Prerequisite(s): COMP 120 or COMP 123, and MATH 236 General Education Requirements: Writing WP Distribution Requirements: Natural science and mathematics Course Materials
MATH 365-02	Computational Linear Algebra	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 245	Instructor: Lori Ziegelmeier	Avail./Max.: 16 / 24
Cross-listed with COMP 365-02; first day attendance required; ACTC students may register on December 1st with permission of instructor Details A mix of applied linear algebra and numerical analysis, 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, such as subspaces, projections, and matrix decompositions. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing. These include solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, eigenvalue and singular value decompositions, and compression. Applications throughout the natural sciences, social sciences, statistics, and computer science Prerequisite(s): COMP 120 or COMP 123, and MATH 236 General Education Requirements: Writing WP Distribution Requirements: Natural science and mathematics Course Materials
MATH 376-01	Algebraic Structures	Days: MWF	Time: 10:50 am-11:50 am	Room: OLRI 205	Instructor: Ian Whitehead	Avail./Max.: 17 / 24
ACTC students may register on December 1st with permission of instructor Details Introduction to algebraic structures, including groups, rings, fields, and vector spaces. Other topics may include geometric constructions, symmetry groups, algebraic coding theory, Burnside's counting theorem, Galois theory. Prerequisite(s): MATH 279 and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 378-01	Complex Analysis	Days: TR	Time: 03:00 pm-04:30 pm	Room: OLRI 245	Instructor: Andrew Beveridge	Avail./Max.: 13 / 24
ACTC students may register on December 1st with permission of instructor Details 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 Cauchy-Riemann 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. Prerequisite(s): MATH 236 and MATH 237. General Education Requirements: Distribution Requirements: Course Materials
MATH 453-01	Survival Analysis	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 245	Instructor: Vittorio Addona	Avail./Max.: Closed 2 / 24
ACTC students may register on December 1st with permission of instructor Details Survival analysis refers to a set of methods used for modeling "time-to-event" 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, marriage duration, removal-to-recurrence 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 Kaplan-Meier curve, parametric regression models, Cox's proportional hazards model, and time-varying 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. Prerequisite(s): MATH 155 and MATH 354. General Education Requirements: Writing WA Distribution Requirements: Natural science and mathematics Course Materials
MATH 455-01	Mathematical Statistics	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 243	Instructor: Vittorio Addona	Avail./Max.: Closed -1 / 20
ACTC students may register on December 1st with permission of instructor Details An important course for students considering graduate work in statistics or biostatistics, this course explores the mathematics underlying modern statistical applications. Topics include: classical techniques for parameter estimation and evaluation of estimator properties, hypothesis testing, confidence intervals, and linear regression. Special topics vary and may include: tests of independence, resampling techniques, introductory Bayesian concepts, and non-parametric methods. Though not the focus of this course, concepts will be highlighted through applications in a variety of settings. Prerequisite(s): MATH 354 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 479-01	Network Science	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 254	Instructor: Andrew Beveridge	Avail./Max.: 11 / 24
Cross-listed with COMP 479-01; ACTC students may register on December 1st with permission of instructor Details 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. Prerequisite(s): MATH 236 and MATH 379. General Education Requirements: Quantitative Thinking Q2 Writing WP Distribution Requirements: Natural science and mathematics Course Materials
MATH 494-01	Cryptography and Number Theory	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 301	Instructor: Ian Whitehead	Avail./Max.: 10 / 20
ACTC students may register on December 1st with permission of instructor Details This is a course on codes, past and present, and the mathematics underlying them. Topics will include historic ciphers, the RSA cipher, the ElGamal cipher, and related protocols. To describe these codes, we will study elementary number theory, modular arithmetic, and primality testing and factoring techniques. We will also cover advanced topics in number theory including quadratic reciprocity and the distribution of primes. Prerequisites: Comp 123, and either Math 376, 377, or 378. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials

Fall 2018

Number / Section	Name	Days	Time	Room	Instructor	Avail. / Max.
MATH 112-01	Introduction to Data Science	Days: TR	Time: 08:00 am-09:30 am	Room: OLRI 254	Instructor: David Shuman	Avail./Max.: 5 / 25
First day attendance required; cross-listed with COMP 112-01; ACTC students may register on the first day of class, with permission of instructor Details This course provides an introduction to the handling, analysis, and interpretation of the big datasets now routinely being collected in science, commerce, and government. Students achieve facility with a sophisticated, technical computing environment. The course aligns with techniques being used in several courses in the natural and social sciences, statistics, and mathematics. The course is intended to be accessible to all students, regardless of background. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 112-02	Introduction to Data Science	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 254	Instructor: David Shuman	Avail./Max.: 6 / 25
First day attendance required; cross-listed with COMP 112-02; ACTC students may register on the first day of class, with permission of instructor Details This course provides an introduction to the handling, analysis, and interpretation of the big datasets now routinely being collected in science, commerce, and government. Students achieve facility with a sophisticated, technical computing environment. The course aligns with techniques being used in several courses in the natural and social sciences, statistics, and mathematics. The course is intended to be accessible to all students, regardless of background. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 125-01	Epidemiology	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 243	Instructor: Vittorio Addona	Avail./Max.: Closed 0 / 24
ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 135-01	Applied Multivariable Calculus I	Days: MWF	Time: 10:50 am-11:50 am	Room: NEILL 400	Instructor: David Ehren	Avail./Max.: 20 / 28
ACTC students may register on the first day of class, with permission of instructor Details 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. Applications are drawn from varied areas, including biology, chemistry, economics, and physics. Prerequisite(s): None. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 135-02	Applied Multivariable Calculus I	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 254	Instructor: Kristin Heysse	Avail./Max.: 12 / 28
ACTC students may register on the first day of class, with permission of instructor Details 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. Applications are drawn from varied areas, including biology, chemistry, economics, and physics. Prerequisite(s): None. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 135-03	Applied Multivariable Calculus I	Days: TR	Time: 03:00 pm-04:30 pm	Room: OLRI 254	Instructor: Kristin Heysse	Avail./Max.: 20 / 28
ACTC students may register on the first day of class, with permission of instructor Details 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. Applications are drawn from varied areas, including biology, chemistry, economics, and physics. Prerequisite(s): None. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-01	Applied Multivariable Calculus II	Days: MWF	Time: 08:30 am-09:30 am	Room: OLRI 241	Instructor: Joseph Benson	Avail./Max.: 24 / 28
ACTC students may register on the first day of class, with permission of instructor Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-02	Applied Multivariable Calculus II	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 241	Instructor: William Mitchell	Avail./Max.: 12 / 28
ACTC students may register on the first day of class, with permission of instructor Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-03	Applied Multivariable Calculus II	Days: MWF	Time: 03:30 pm-04:30 pm	Room: OLRI 241	Instructor: William Mitchell	Avail./Max.: 25 / 28
ACTC students may register on the first day of class, with permission of instructor Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-01	Intro to Statistical Modeling	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 254	Instructor: Brianna Heggeseth	Avail./Max.: 4 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-02	Intro to Statistical Modeling	Days: MWF	Time: 10:50 am-11:50 am	Room: OLRI 254	Instructor: Brianna Heggeseth	Avail./Max.: 4 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-03	Intro to Statistical Modeling	Days: MWF	Time: 01:10 pm-02:10 pm	Room: OLRI 254	Instructor: Leslie Myint	Avail./Max.: 4 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-04	Intro to Statistical Modeling	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 254	Instructor: Leslie Myint	Avail./Max.: 6 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-05	Intro to Statistical Modeling	Days: TR	Time: 08:00 am-09:30 am	Room: OLRI 241	Instructor: Lisa Lendway	Avail./Max.: 4 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-06	Intro to Statistical Modeling	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 241	Instructor: Lisa Lendway	Avail./Max.: 5 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Quantitative Thinking Q3 Distribution Requirements: Natural science and mathematics Course Materials
MATH 236-01	Linear Algebra	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 241	Instructor: Thomas Halverson	Avail./Max.: 4 / 32
ACTC students may register on the first day of class, with permission of instructor Details Linear algebra is one of the pillars of mathematics, both pure and applied. Linear relations can be used to model phenomena from numerous disciplines in the mathematical sciences, physical sciences, social sciences, engineering, and computer science. This introduction to linear algebra 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, linear transformations, orthogonality and projections, eigenvectors, and their applications. The resulting linear algebraic framework is a flexible and powerful way to approach multidimensional problems. Prerequisite(s): MATH 279 or MATH 137, or with permission of instructor, MATH 135 General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 236-02	Linear Algebra	Days: MWF	Time: 10:50 am-11:50 am	Room: OLRI 241	Instructor: Thomas Halverson	Avail./Max.: 4 / 32
ACTC students may register on the first day of class, with permission of instructor Details Linear algebra is one of the pillars of mathematics, both pure and applied. Linear relations can be used to model phenomena from numerous disciplines in the mathematical sciences, physical sciences, social sciences, engineering, and computer science. This introduction to linear algebra 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, linear transformations, orthogonality and projections, eigenvectors, and their applications. The resulting linear algebraic framework is a flexible and powerful way to approach multidimensional problems. Prerequisite(s): MATH 279 or MATH 137, or with permission of instructor, MATH 135 General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 237-01	Applied Multivariable Calculus III	Days: MWF	Time: 10:50 am-11:50 am	Room: NEILL 304	Instructor: Joseph Benson	Avail./Max.: 13 / 28
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 137 or a strong high school calculus at the level of AP calculus with a BC score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 237-02	Applied Multivariable Calculus III	Days: MWF	Time: 02:20 pm-03:20 pm	Room: OLRI 243	Instructor: Ian Whitehead	Avail./Max.: 12 / 28
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 137 or a strong high school calculus at the level of AP calculus with a BC score of 4 or higher. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 253-01	Statistical Computing and Machine Learning	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 258	Instructor: Alicia Johnson	Avail./Max.: Closed 0 / 24
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details The linear and logistic modeling techniques from MATH 155 are augmented with the three foundational machine learning tasks: regression, classification, and clustering. The course explores techniques central to these tasks, including methods of data exploration, supervised and unsupervised learning, parametric and nonparametric modeling, and model training and evaluation. As required by the application of these sophisticated techniques, the course also introduces foundational statistical computer programming concepts. Prerequisite(s): MATH 155 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 253-02	Statistical Computing and Machine Learning	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 241	Instructor: Lisa Lendway	Avail./Max.: Closed 1 / 24
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details The linear and logistic modeling techniques from MATH 155 are augmented with the three foundational machine learning tasks: regression, classification, and clustering. The course explores techniques central to these tasks, including methods of data exploration, supervised and unsupervised learning, parametric and nonparametric modeling, and model training and evaluation. As required by the application of these sophisticated techniques, the course also introduces foundational statistical computer programming concepts. Prerequisite(s): MATH 155 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 279-01	Discrete Mathematics	Days: TR	Time: 01:20 pm-02:50 pm	Room: NEILL 400	Instructor: Andrew Beveridge	Avail./Max.: 4 / 28
ACTC students may register on the first day of class, with permission of instructor Details Discrete mathematics studies collections of distinct, separate objects and is complementary to calculus (which studies continuous phenomena). This course introduces techniques for analyzing arrangements of objects and the relationships between them. The material emphasizes problem solving and logical argumentation, rather than computation. Topics include basic counting principles, induction, logic, recurrence relations, number theory, and graph theory. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 279-02	Discrete Mathematics	Days: TR	Time: 03:00 pm-04:30 pm	Room: NEILL 400	Instructor: Andrew Beveridge	Avail./Max.: 8 / 28
ACTC students may register on the first day of class, with permission of instructor Details Discrete mathematics studies collections of distinct, separate objects and is complementary to calculus (which studies continuous phenomena). This course introduces techniques for analyzing arrangements of objects and the relationships between them. The material emphasizes problem solving and logical argumentation, rather than computation. Topics include basic counting principles, induction, logic, recurrence relations, number theory, and graph theory. General Education Requirements: Quantitative Thinking Q1 Distribution Requirements: Natural science and mathematics Course Materials
MATH 312-01	Differential Equations	Days: MWF	Time: 10:50 am-11:50 am	Room: OLRI 301	Instructor: William Mitchell	Avail./Max.: 1 / 24
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 236 and MATH 237 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 354-01	Probability	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 243	Instructor: Alicia Johnson	Avail./Max.: 7 / 24
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 237; or MATH 137 and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 354-02	Probability	Days: TR	Time: 08:00 am-09:30 am	Room: OLRI 243	Instructor: Alicia Johnson	Avail./Max.: 0 / 24
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 237; or MATH 137 and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 361-01	Theory of Computation	Days: MWF	Time: 01:10 pm-02:10 pm	Room: OLRI 243	Instructor: Daniel Kluver	Avail./Max.: 1 / 25
Permission of instructor required; first day attendance required; cross-listed with COMP 261-01; ACTC students may register on the first day of class, with permission of instructor Details This course examines the theoretical foundations of computation. It explores different mathematical models that try to formalize our informal notion of an algorithm. Models include finite automata, regular expressions, grammars, and Turing machines. The course also discusses ideas about what can and cannot be computed. In addition, the course explores the basics of complexity theory, examining broad categories of problems and their algorithms, and their efficiency. The focus is on the question of P versus NP, and the NP-complete set. Prerequisite(s): COMP 124 and MATH 279, or permission of instructor General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 377-01	Real Analysis	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 205	Instructor: Ian Whitehead	Avail./Max.: 11 / 24
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 237 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 379-01	Combinatorics	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 243	Instructor: Andrew Beveridge	Avail./Max.: 10 / 24
ACTC students may register on the first day of class, with permission of instructor Details A second course in discrete mathematics that develops more advanced counting techniques. Combinatorics is the study of arrangements, patterns and configurations. Generally speaking, we fix a set of objects and then arrange those objects into patterns satisfying special rules. Once we identify an interesting family of objects, we ask: how many are there? what are their structural properties? how can we find the "best" one(s)? Topics are drawn from graph theory, enumerative combinatorics, graph algorithms, and generating functions. Prerequisite(s): MATH 279 and MATH 237 General Education Requirements: Distribution Requirements: Course Materials
MATH 437-01	Topics in Applied Math	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 245	Instructor: David Shuman	Avail./Max.: 7 / 20
ACTC students may register on the first day of class, with permission of instructor Details 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. May be repeated for credit with departmental approval. Prerequisite(s): MATH 236 and one of the following: COMP 120 or COMP 123 or COMP 124. MATH 312 or MATH 365 recommended. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 453-01	Survival Analysis	Days: MWF	Time: 12:00 pm-01:00 pm	Room: OLRI 241	Instructor: Vittorio Addona	Avail./Max.: Closed 0 / 18
ACTC students may register on the first day of class, with permission of instructor Details Survival analysis refers to a set of methods used for modeling "time-to-event" 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, marriage duration, removal-to-recurrence 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 Kaplan-Meier curve, parametric regression models, Cox's proportional hazards model, and time-varying 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. Prerequisite(s): MATH 155 and MATH 354. General Education Requirements: Writing WA Distribution Requirements: Natural science and mathematics Course Materials
MATH 453-02	Survival Analysis	Days: MWF	Time: 01:10 pm-02:10 pm	Room: OLRI 241	Instructor: Vittorio Addona	Avail./Max.: Closed 0 / 18
ACTC students may register on the first day of class, with permission of instructor Details Survival analysis refers to a set of methods used for modeling "time-to-event" 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, marriage duration, removal-to-recurrence 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 Kaplan-Meier curve, parametric regression models, Cox's proportional hazards model, and time-varying 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. Prerequisite(s): MATH 155 and MATH 354. General Education Requirements: Writing WA Distribution Requirements: Natural science and mathematics Course Materials

Spring 2019

Number / Section	Name	Days	Time	Room	Instructor	Avail. / Max.
MATH 112-01	Introduction to Data Science	Days: TR	Time: 08:00 am-09:30 am	Room: OLRI 258	Instructor: Shilad Sen	Avail./Max.: 24 / 24
Cross-listed with COMP 112-01 Details This course provides an introduction to the handling, analysis, and interpretation of the big datasets now routinely being collected in science, commerce, and government. Students achieve facility with a sophisticated, technical computing environment. The course aligns with techniques being used in several courses in the natural and social sciences, statistics, and mathematics. The course is intended to be accessible to all students, regardless of background. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 125-01	Epidemiology	Days: MWF	Time: 01:10 pm-02:10 pm	Room:	Instructor: Vittorio Addona	Avail./Max.: 24 / 24
Details 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. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 135-01	Applied Multivariable Calculus I	Days: MWF	Time: 02:20 pm-03:20 pm	Room:	Instructor: STAFF	Avail./Max.: 28 / 28
Details 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. Applications are drawn from varied areas, including biology, chemistry, economics, and physics. Prerequisite(s): None. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 135-02	Applied Multivariable Calculus I	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 254	Instructor: Kristin Heysse	Avail./Max.: 28 / 28
Details 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. Applications are drawn from varied areas, including biology, chemistry, economics, and physics. Prerequisite(s): None. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-01	Applied Multivariable Calculus II	Days: MWF	Time: 09:40 am-10:40 am	Room:	Instructor: Joseph Benson	Avail./Max.: 28 / 28
Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-02	Applied Multivariable Calculus II	Days: MWF	Time: 10:50 am-11:50 am	Room:	Instructor: Joseph Benson	Avail./Max.: 28 / 28
Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 137-03	Applied Multivariable Calculus II	Days: MWF	Time: 03:30 pm-04:30 pm	Room:	Instructor: STAFF	Avail./Max.: 28 / 28
Details This course focuses on calculus useful for both theoretical and applied work in the mathematical, natural, and social sciences. Topics include: partial derivatives, gradients, contour plots, constrained and unconstrained optimization, Taylor polynomials, interpretations of integrals via finite sums, the fundamental theorem of calculus, double integrals over a rectangle,and differential equations. Attention is given to both symbolic and numerical computing. Prerequisite(s): MATH 135 or a year of high school calculus at the level of AP calculus with an AB score of 4 or higher. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-01	Intro to Statistical Modeling	Days: MWF	Time: 01:10 pm-02:10 pm	Room:	Instructor: David Ehren	Avail./Max.: 28 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-02	Intro to Statistical Modeling	Days: TR	Time: 08:00 am-09:30 am	Room:	Instructor: Lisa Lendway	Avail./Max.: 28 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-03	Intro to Statistical Modeling	Days: TR	Time: 09:40 am-11:10 am	Room:	Instructor: Alicia Johnson	Avail./Max.: 28 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 155-04	Intro to Statistical Modeling	Days: TR	Time: 01:20 pm-02:50 pm	Room:	Instructor: Lisa Lendway	Avail./Max.: 28 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 212-01	Philosophy of Mathematics	Days: TR	Time: 01:20 pm-02:50 pm	Room:	Instructor: Janet Folina	Avail./Max.: 15 / 15
ACTC students may register on the first day of class, with permission of instructor; cross-listed with PHIL 312-01 Details Why does 2 + 2 equal four? Can a diagram prove a mathematical truth? Is mathematics a social construction or do mathematical facts exist independently of our knowing them? Philosophy of mathematics considers these sorts of questions in an effort to understand the logical and philosophical foundations of mathematics. Topics include mathematical truth, mathematical reality, and mathematical justifications (knowledge). Typically we focus on the history of mathematics of the past 200 years, highlighting the way philosophical debates arise in mathematics itself and shape its future. Prerequisite(s): PHIL 111, MATH 279, or permission of the instructor. General Education Requirements: Distribution Requirements: Humanities Course Materials
MATH 236-01	Linear Algebra	Days: MWF	Time: 09:40 am-10:40 am	Room:	Instructor: David Shuman	Avail./Max.: 28 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details Linear algebra is one of the pillars of mathematics, both pure and applied. Linear relations can be used to model phenomena from numerous disciplines in the mathematical sciences, physical sciences, social sciences, engineering, and computer science. This introduction to linear algebra 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, linear transformations, orthogonality and projections, eigenvectors, and their applications. The resulting linear algebraic framework is a flexible and powerful way to approach multidimensional problems. Prerequisite(s): MATH 279 or MATH 137, or with permission of instructor, MATH 135 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 236-02	Linear Algebra	Days: MWF	Time: 10:50 am-11:50 am	Room:	Instructor: David Shuman	Avail./Max.: 28 / 28
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details Linear algebra is one of the pillars of mathematics, both pure and applied. Linear relations can be used to model phenomena from numerous disciplines in the mathematical sciences, physical sciences, social sciences, engineering, and computer science. This introduction to linear algebra 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, linear transformations, orthogonality and projections, eigenvectors, and their applications. The resulting linear algebraic framework is a flexible and powerful way to approach multidimensional problems. Prerequisite(s): MATH 279 or MATH 137, or with permission of instructor, MATH 135 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 237-01	Applied Multivariable Calculus III	Days: MWF	Time: 09:40 am-10:40 am	Room:	Instructor: Ian Whitehead	Avail./Max.: 28 / 28
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 137 or a strong high school calculus at the level of AP calculus with a BC score of 4 or higher. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 237-02	Applied Multivariable Calculus III	Days: MWF	Time: 10:50 am-11:50 am	Room:	Instructor: Ian Whitehead	Avail./Max.: 28 / 28
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 137 or a strong high school calculus at the level of AP calculus with a BC score of 4 or higher. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 253-01	Statistical Computing and Machine Learning	Days: MWF	Time: 09:40 am-10:40 am	Room: OLRI 254	Instructor: Leslie Myint	Avail./Max.: 24 / 24
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details The linear and logistic modeling techniques from MATH 155 are augmented with the three foundational machine learning tasks: regression, classification, and clustering. The course explores techniques central to these tasks, including methods of data exploration, supervised and unsupervised learning, parametric and nonparametric modeling, and model training and evaluation. As required by the application of these sophisticated techniques, the course also introduces foundational statistical computer programming concepts. Prerequisite(s): MATH 155 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 253-02	Statistical Computing and Machine Learning	Days: MWF	Time: 10:50 am-11:50 am	Room: OLRI 254	Instructor: Leslie Myint	Avail./Max.: 24 / 24
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details The linear and logistic modeling techniques from MATH 155 are augmented with the three foundational machine learning tasks: regression, classification, and clustering. The course explores techniques central to these tasks, including methods of data exploration, supervised and unsupervised learning, parametric and nonparametric modeling, and model training and evaluation. As required by the application of these sophisticated techniques, the course also introduces foundational statistical computer programming concepts. Prerequisite(s): MATH 155 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 279-01	Discrete Mathematics	Days: MWF	Time: 01:10 pm-02:10 pm	Room:	Instructor: Kristin Heysse	Avail./Max.: 28 / 28
ACTC students may register on the first day of class, with permission of instructor Details Discrete mathematics studies collections of distinct, separate objects and is complementary to calculus (which studies continuous phenomena). This course introduces techniques for analyzing arrangements of objects and the relationships between them. The material emphasizes problem solving and logical argumentation, rather than computation. Topics include basic counting principles, induction, logic, recurrence relations, number theory, and graph theory. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 279-02	Discrete Mathematics	Days: MWF	Time: 02:20 pm-03:20 pm	Room:	Instructor: Kristin Heysse	Avail./Max.: 28 / 28
ACTC students may register on the first day of class, with permission of instructor Details Discrete mathematics studies collections of distinct, separate objects and is complementary to calculus (which studies continuous phenomena). This course introduces techniques for analyzing arrangements of objects and the relationships between them. The material emphasizes problem solving and logical argumentation, rather than computation. Topics include basic counting principles, induction, logic, recurrence relations, number theory, and graph theory. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 312-01	Differential Equations	Days: MWF	Time: 01:10 pm-02:10 pm	Room: OLRI 254	Instructor: Joseph Benson	Avail./Max.: 24 / 24
Details 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. Prerequisite(s): MATH 236 and MATH 237 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 354-01	Probability	Days: MWF	Time: 09:40 am-10:40 am	Room:	Instructor: Vittorio Addona	Avail./Max.: 24 / 24
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 237; or MATH 137 and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 361-01	Theory of Computation	Days: MWF	Time: 01:10 pm-02:10 pm	Room:	Instructor: Susan Fox	Avail./Max.: 25 / 25
Permission of instructor required; first day attendance required; ACTC students may register on the first day of class, with permission of instructor; cross-listed with COMP 261-01 Details This course examines the theoretical foundations of computation. It explores different mathematical models that try to formalize our informal notion of an algorithm. Models include finite automata, regular expressions, grammars, and Turing machines. The course also discusses ideas about what can and cannot be computed. In addition, the course explores the basics of complexity theory, examining broad categories of problems and their algorithms, and their efficiency. The focus is on the question of P versus NP, and the NP-complete set. Prerequisite(s): COMP 124 and MATH 279, or permission of instructor General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 365-01	Computational Linear Algebra	Days: TR	Time: 08:00 am-09:30 am	Room:	Instructor: William Mitchell	Avail./Max.: 24 / 24
ACTC students may register on the first day of class, with permission of instructor; cross-listed with COMP 365-01 Details A mix of applied linear algebra and numerical analysis, 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, such as subspaces, projections, and matrix decompositions. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing. These include solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, eigenvalue and singular value decompositions, and compression. Applications throughout the natural sciences, social sciences, statistics, and computer science Prerequisite(s): COMP 120 or COMP 123, and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 365-02	Computational Linear Algebra	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 254	Instructor: William Mitchell	Avail./Max.: 24 / 24
ACTC students may register on the first day of class, with permission of instructor; cross-listed with COMP 365-02 Details A mix of applied linear algebra and numerical analysis, 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, such as subspaces, projections, and matrix decompositions. The course reviews these concepts, adopts them to large scales, and applies them in the core techniques of scientific computing. These include solving systems of linear and nonlinear equations, approximation and statistical function estimation, optimization, interpolation, eigenvalue and singular value decompositions, and compression. Applications throughout the natural sciences, social sciences, statistics, and computer science Prerequisite(s): COMP 120 or COMP 123, and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 376-01	Algebraic Structures	Days: TR	Time: 01:20 pm-02:50 pm	Room:	Instructor: Thomas Halverson	Avail./Max.: 24 / 24
ACTC students may register on the first day of class, with permission of instructor Details Introduction to algebraic structures, including groups, rings, fields, and vector spaces. Other topics may include geometric constructions, symmetry groups, algebraic coding theory, Burnside's counting theorem, Galois theory. Prerequisite(s): MATH 279 and MATH 236 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 378-01	Complex Analysis	Days: TR	Time: 09:40 am-11:10 am	Room: OLRI 245	Instructor: Andrew Beveridge	Avail./Max.: 24 / 24
ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 236 and MATH 237. General Education Requirements: Distribution Requirements: Course Materials
MATH 394-01	Correlated Data	Days: TR	Time: 09:40 am-11:10 am	Room:	Instructor: Brianna Heggeseth	Avail./Max.: 20 / 20
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details Varies by semester. Consult the department or class schedule for current listing. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 454-01	Bayesian Statistics	Days: TR	Time: 01:20 pm-02:50 pm	Room: OLRI 245	Instructor: Alicia Johnson	Avail./Max.: 16 / 16
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details 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. Prerequisite(s): MATH 155 and MATH 354. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 455-01	Mathematical Statistics	Days: TR	Time: 03:00 pm-04:30 pm	Room:	Instructor: Brianna Heggeseth	Avail./Max.: 16 / 16
First day attendance required; ACTC students may register on the first day of class, with permission of instructor Details An important course for students considering graduate work in statistics or biostatistics, this course explores the mathematics underlying modern statistical applications. Topics include: classical techniques for parameter estimation and evaluation of estimator properties, hypothesis testing, confidence intervals, and linear regression. Special topics vary and may include: tests of independence, resampling techniques, introductory Bayesian concepts, and nonparametric methods. Though not the focus of this course, concepts will be highlighted through applications in a variety of settings. Prerequisite(s): MATH 354 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 471-01	Topology	Days: MWF	Time: 02:20 pm-03:20 pm	Room:	Instructor: Ian Whitehead	Avail./Max.: 16 / 16
ACTC students may register on the first day of class, with permission of instructor Details A course in both theoretical and computational mathematics. Theoretical concepts include 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 topological data analysis. 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. Prerequisite(s): MATH 365 or MATH 376 or MATH 377 General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials
MATH 479-01	Network Science	Days: TR	Time: 03:00 pm-04:30 pm	Room: OLRI 245	Instructor: Andrew Beveridge	Avail./Max.: 15 / 15
ACTC students may register on the first day of class, with permission of instructor; cross-listed with COMP 479-01 Details 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. Prerequisite(s): MATH 236 and MATH 379. General Education Requirements: Distribution Requirements: Natural science and mathematics Course Materials

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