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Mathematics and Statistics

## Degrees and Certificates

## Classes

### MAT 1000 : Math and Stat Communities

Understanding the role of creative thinking, problem solving, and collaboration in mathematics and statistics; exploration of research and careers in the mathematical and statistical sciences; building community with fellow mathematics and statistics majors.

#### Credits

Credits 1### MAT 1220 : Discrete Math Social Sci

Discrete mathematics for the Liberal Arts student: voting methods, weighted voting, fair division, apportionment, circuits, network, trees, directed graphs, planning and scheduling, linear programming, growth and symmetry. Not open to students who have completed MAT 1505.

#### Credits

Credits 3### MAT 1230 : Intro Statistics I

Displaying and summarizing data, basic probability concepts, normal distributions, sampling distributions, estimation for a single population parameter, regression and correlation. Not open to students who have completed MAT 1505.

#### Credits

Credits 3### MAT 1235 : Intro Statistics II

Probability concepts, hypothesis testing, inferences about means, variances and proportions, contingency tables, analysis of variance. Not open to students who have completed MAT 1505.

#### Credits

Credits 3#### Prerequisites

MAT 1230 :D-

### MAT 1250 : Stats in Health Care Research

Descriptive and inferential statistics: graphical displays, estimation, & hypothesis testing. Restricted to nursing students; others by special permission only.

#### Credits

Credits 3### MAT 1260 : Elementary Statistics

Introduction to statistics including topics such as study design, graphical and numerical descriptive statistics, bivariate data analysis, probability, sampling distributions, confidence intervals, hypothesis testing, goodness of fit tests, analysis of variance; resampling and simulation using statistical software; interpreting output from and understanding selected algorithms used in statistical packages. Restricted to Part-Time Studies

#### Credits

Credits 3### MAT 1280 : Mathematics of Fairness

Examining fairness in our personal lives and in society: Voting systems and power indices, strategic political positioning spatial models, fair division, congressional district apportionment, game theory, the GINI index of economic inequality, gerrymandering.

#### Credits

Credits 3### MAT 1290 : Topics in Core Mathematics

Course in an area of pure or applied mathematics or statistics. May be repeated for credit if areas of topical focus are different. Designed specifically to satisfy the core requirement in mathematics and statistics, for students in the humanities and social sciences.

#### Credits

Credits 3### MAT 1310 : Calc Life Sci Appl I

Functions, algebra of real functions, polynomials, allometric functions, exponential and logarithmic functions, trigonometric functions, graphing, log-log and semilog graphs, sequences, difference equations, limits, continuity, the derivative, the chain rule, higher order derivatives, maxima and minima, curve sketching, applications to biology.

#### Credits

Credits 3### MAT 1312 : Biocalculus

Discrete and continuous dynamics of biological systems: discrete dynamical systems, sequences, functions, discrete and continuous limits, the derivative, the integral, methods and applications of differentiation and integration, Taylor polynomials, modeling with differential equations, Euler's method, applications to Biology.

#### Credits

Credits 4### MAT 1313 : Statistics for Life Sciences

Statistical concepts and methods with applications in biological and life sciences; data visualization, descriptive statistics, probability distributions, interval estimation and hypothesis testing for one and two variables, statistical software.

#### Credits

Credits 3### MAT 1314 : Modeling for the Life Sciences

Mathematical and statistical modeling in the Life Sciences. Topics selected from: dynamical systems, diffusion, Markov, Bayesian, connectionist, and information theory models, applied to epidemiology, ecology, neuroscience and neuron signaling, cell and molecular biology, genetics, physiology, psychology, and other areas. Pre-requisites MAT 1312 or Equivalent

#### Credits

Credits 3#### Prerequisites

MAT 1310 or MAT 1312 or MAT 1320 or MAT 1400 or MAT 1500

### MAT 1315 : Calc Life Sci Appl II

The mean-value theorem, Taylor's polynomial approximations, the anti-derivative, the definite integral, area, numerical integration, applications of the integral, techniques of integration, indeterminate forms, L'Hospital's rule,improper integrals, introduction to differential equations with applications to biological systems, numerical solutions using the computer, applications in the life sciences.

#### Credits

Credits 3#### Prerequisites

(MAT 1310 :D- or MAT 1500 :D-)

### MAT 1320 : Calculus I for Liberal Arts

Calculus for Liberal Arts students: polynomial, rational and transcendental functions, the derivative, numerical and graphical introduction to integration.

#### Credits

Credits 3### MAT 1325 : Calculus II for Liberal Arts

Techniques of differentiation and integration, applications and further developments of calculus.

#### Credits

Credits 3#### Prerequisites

(MAT 1320 :D- or MAT 1500 :D-)

### MAT 1330 : Calculus I for Business

Analysis of single variable problems: problem formulation, translation between mathematical symbols and verbal descriptions, single variable modeling with real data, rates of change, techniques of differentiation, optimazation, post-optinality analysis, continuous probability distributions, integrals, Fundamental Theorem of Calculus.

#### Credits

Credits 3### MAT 1335 : Calculus II for Business

Analysis of multivariable problems: problem formulation, translation between mathematical symbols and verbal descriptions, multivariable modeling with real data, regression analysis, partial derivatives and unconstrained optimization, Lagrange multipliers and constrained optimization, matrix algebra, linear programming.

#### Credits

Credits 3#### Prerequisites

(MAT 1330 :D- or MAT 1500 :D-)

### MAT 1400 : Business Calculus

Functions, limits, and basic definitions of differential and integral calculus. Techniques of differentiation and integration. The Fundamental Theorem of Calculus. Applications in various areas of business and economics.

#### Credits

Credits 4### MAT 1430 : Business Statistics

Statistical concepts and methods useful in analyzing problems in all areas of business. Descriptive statistics, probability, sampling distributions, confidence intervals, hypothesis testing, regression analysis, and time series. Applications in various areas of business and economics.

#### Credits

Credits 4### MAT 1500 : Calculus I

Limits, transcendental functions (logarithms, exponential functions, inverse trigonometric functions), differentiation (definition, tangent lines, rates of change, techniques, implicit differentiation, related rates), applications of differentiation (graphing, optimization), indeterminate forms and L'Hopital's Rule. Use of a computer algebra system, eg. MAPLE.

#### Credits

Credits 4### MAT 1505 : Calculus II

Integration (indefinite, definite), applications of integration (area, volume, applications to physics and economics, etc.), methods of integration, approximate integration (trapezoidal and Simpson's rules), improper integrals, differential equations, infinite sequences and series. Continued use of a computer algebra system.

#### Credits

Credits 4#### Prerequisites

MAT 1312 or MAT 1320 or MAT 1400 or MAT 1500

### MAT 2310 : Stat for Experimenters

The design and analysis of experiments, probability distributions, basic statistical inference, analysis of variance, block designs and factorial designs. For social and natural science majors.

#### Credits

Credits 3#### Prerequisites

(MAT 1315 :D- or MAT 1325 :D- or MAT 1505 :D-)

### MAT 2400 : Linear Algebra for Computing

Vectors, matrices, and matrix algebra; systems of linear equations; matrix inverses; least squares problems; eigenvalues and eigenvectors; using Python for computational linear algebra; applications from areas such as data science, computer graphics, graph algorithms, and web search.

#### Credits

Credits 4#### Prerequisites

MAT 1500

### MAT 2500 : Calculus III

Parametric equations; polar, cylindrical, and spherical coordinates; vectors and the geometry of space; vector functions (derivatives, integrals, curvature, etc.); partial derivatives; optimization; multiple integration and its applications; vector calculus (line integrals, vector analysis). Continued use of a computer algebra system.

#### Credits

Credits 4#### Prerequisites

MAT 1505 :D-

### MAT 2600 : Mathematical Reasoning & Proof

Mathematical proofs: direct, indirect, induction. Logic, set theory, relations, functions. Optional topics from algebra, number theory, combinatorics, and analysis.

#### Credits

Credits 3#### Prerequisites

MAT 1500 :D-

### MAT 2705 : Diff Equation with Linear Alg

First order and linear second order differential equations, matrices and linear equation systems, eigenvalues and eigenvectors, and linear systems of differential equations.

#### Credits

Credits 4#### Prerequisites

MAT 1505 :D-

### MAT 2930 : History of Mathematics

Development of mathematics from ancient times to the birth of calculus in the seventeenth century.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :D- and MAT 2600 :D-

### MAT 3001 : Topics in Mathematics & Stats

Lecture course in an area of mathematics or statistics. May be repeated for credit if topics are different.

#### Credits

Credits 1### MAT 3011 : Problem Solving Seminar

Explore techniques for solving mathematical problems, including problems typical of the Putman Mathematical Competition. Students solve and present solutions to problems posed.

#### Credits

Credits 1#### Prerequisites

MAT 1500

### MAT 3100 : Applied Linear Algebra

Vectors, matrices, transpose and inverse of a matrix, systems of linear equations, the four fundamental subspaces, eigenvalues and eigenvectors, symmetric matrices, matrix factorizations, applications such as information retrieval, ranking web pages, graphs and networks, least squares, and data compression.

#### Credits

Credits 3#### Prerequisites

MAT 1312 or MAT 1320 or MAT 1400 or MAT 1500

### MAT 3300 : Advanced Calculus

Real numbers, sequences, convergence, supremum and infimum, completeness of the reals, continuous functions, Intermediate Value Theorem, differentiable functions, Mean Value Theorem, Riemann integral, Fundamental Theorem of Calculus, Taylor's Theorem.

#### Credits

Credits 3#### Prerequisites

MAT 2500 :D- and (MAT 2600 :D- or HON 4151 :D-)

### MAT 3305 : Topics in Analysis

Advanced topics selected from real analysis, complex analysis, or higher analysis.

#### Credits

Credits 3#### Prerequisites

MAT 3300 :D-

### MAT 3400 : Linear Algebra

Theory of vector spaces, linear transformations, basis, and dimension. Selected topics from orthogonal transformations, least squares, eigenvalues and eigenvectors, similarity, diagonalization, matrix decompositions, infinite dimensional transformations.

#### Credits

Credits 3#### Prerequisites

MAT 2600 and (MAT 2400 or MAT 2705 or MAT 3100)

### MAT 3500 : Modern Algebra I

Topics selected from groups and subgroups, cyclic groups, permutation groups, isomorphisms, direct products, cosets and Lagrange's Theorem, normal subgroups and factor groups, group homomorphisms, the Fundamental Theorem of Finite Abelian Groups, rings, fields.

#### Credits

Credits 3#### Prerequisites

MAT 2600 :D- and MAT 2705 :D-

### MAT 3930 : History of Mathematics

Development of mathematics from ancient times to the birth of calculus in the seventeenth century.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :D- and MAT 2600 :D-

### MAT 4110 : Combinatorics

Induction, permutations and combinations, general counting methods, generating functions, recurrence relations, principle of inclusion-exclusion, graph theory, trees, planarity, crossing numbers, Hamiltonian cycles, Eulerian tours.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :D-

### MAT 4210 : Bayesian Statistical Analysis

Application of Bayesian statistical procedures. Implementation using the programming language R. Bayes's Theorem. Bayesian statistical inference. Various types of prior distributions. Computer-intensive methods. Assessing the prior. Robustness analysis. Writing Bayesian statistical reports.

#### Credits

Credits 3#### Prerequisites

MAT 4310

### MAT 4270 : Numerical Analysis

Numerical and computational aspects of root-finding methods, interpolation and polynomial approximation, numerical differentiation and integration, approximation theory.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :D-

### MAT 4310 : Stat Methods

Data displays and summarization, probability distributions, point and interval estimation, hypothesis testing, categorical data analysis, regression and correlation.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :Y :D-

### MAT 4315 : Applied Statistical Models

Simple and multiple linear regression, including prediction, correlation, model building, multicollinearity, influential observations, and model fit; ANOVA for designed experiments, including completely randomized, randomized block and factorial designs; Time Series including linear time series models, moving averages, autoregressive and ARIMA models, estimation and forecasting.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :D- and (MAT 4310 :B- or MAT 1430 :B-)

### MAT 4380 : Data Science

Combining and summarizing real-world data to inform decision-making and predictions; data wrangling, visualization, text mining, ethics; uses R programming language. Some programming experience recommended.

#### Credits

Credits 3#### Prerequisites

MAT 1230 or MAT 1250 or MAT 1313 or MAT 1430 or MAT 4310

### MAT 4500 : Mathematics of Games

Study of popular games, toys, and puzzles using recursions, counting techniques, graph theory, group theory, probability, Markov chains, and other mathematical tools.

#### Credits

Credits 3#### Prerequisites

MAT 2600 and (STAT 1230 or STAT 1250 or STAT 1313 or STAT 1430 or STAT 4310)

### MAT 4550 : Math of Financial Derivatives

Basic tools of financial markets; options; asset price random walks; estimation of parameters; arbitrage put-call parity; Black-Scholes Model; implied volatility; portfolio-optimization; hedging.

#### Credits

Credits 3#### Prerequisites

MAT 2705 :D-

### MAT 4600 : Deterministic Oper Res

Deterministic methods: mathematical optimization, linear programming, formulation and solution techniques, duality, integer linear programming, transportation problem, assignment problem, network flows, dynamic programming.

#### Credits

Credits 3#### Prerequisites

MAT 2500 :D- and (MAT 2705 or MAT 3100 or MAT 3400)

### MAT 5110 : Topics in Geometry

Topics selected from affine, hyperbolic, spherical, elliptic, Euclidean or projective geometry.

#### Credits

Credits 3#### Prerequisites

MAT 2600 :D-

### MAT 5200 : Theory of Numbers

Congruences, quadratic reciprocity, Diophantine equations; applications.

#### Credits

Credits 3#### Prerequisites

MAT 2600 :D-

### MAT 5400 : Complex Analysis

Algebra of complex numbers, analytic functions, Cauchy- Riemann equation, Laplace equations, conformal mapping, integrals of complex functions, Cauchy's theorem, power series, Taylor's theorem, Laurent's theorem, residues, entire functions.

#### Credits

Credits 3#### Prerequisites

(MAT 2500 :D- and MAT 2600 :D-)

#### Corequisites

### MAT 5500 : Topology

Topological equivalence, connectedness, compactness, topology of subsets of Rn, manifolds, topological embeddings, topological spaces.

#### Credits

Credits 3#### Prerequisites

MAT 3300 :Y

### MAT 5600 : Differential Geometry

Geometry of curves and surfaces, curvature, first and second fundamental forms, minimal surfaces, use of MAPLE.

#### Credits

Credits 3#### Prerequisites

MAT 2500 :D-

### MAT 5700 : Math Statistics I

Probability, random variables, joint distributions, expected values, limit theorems, distributions derived from the normal distribution.

#### Credits

Credits 3#### Prerequisites

MAT 2500 :D-

### MAT 5705 : Math Statistics II

Survey sampling, parameter estimation, hypothesis testing, two sample tests, analysis of variance, analysis of categorical data, linear least squares.

#### Credits

Credits 3#### Prerequisites

MAT 5700 :D- and MAT 2500 :D-

### MAT 5900 : Seminar in Mathematics

Supervised study of selected topics or problems in mathematics, student presentations. May be repeated for credit if content is different.

#### Credits

Credits 3#### Prerequisites

MAT 3300 :D- or MAT 3500 :D-

### MAT 5905 : Seminar in Statistics

Supervised study of selected topics or problems in statistics, with student presentations and papers. May be repeated for credit if content is different.

#### Credits

Credits 3#### Prerequisites

MAT 4315 and MAT 5700

### MAT 5910 : Topics in Statistics

Lecture course in an area of statistics. May be repeated for credit if topics are different. Prerequisites: Dependent on Topic.

#### Credits

Credits 3### MAT 5920 : Topics in Applied Mathematics

Lecture course in an area of applied mathematics. May be repeated for credit if topics are different.

#### Credits

Credits 3### MAT 5930 : Topics in Pure Mathematics

Lecture course in an area of pure mathematics. May be repeated for credit if topics are different.

#### Credits

Credits 3### MAT 5991 : Independent Study

Reading in a selected branch of mathematics under the direction of a member of the staff. May be repeated for credit.

#### Credits

Credits 1#### Prerequisites

MAT 1505 :D-

### MAT 5992 : Independent Study

Reading in a selected branch of mathematics under the direction of a member of the staff. May be repeated for credit.

#### Credits

Credits 2#### Prerequisites

MAT 1505 :D-

### MAT 5993 : Independent Study

Reading in a selected branch of mathematics under the direction of a member of the staff. May be repeated for credit.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :D-

### MAT 7111 : Adv. Placement Stat. Workshop

Workshop for teachers of the Advanced Placement (AP) Statistics course. Inference, design of experiments, exploratory data analysis, simulation, probability, investigative tasks, and AP Statistics exam overview.

#### Credits

Credits 3### MAT 7120 : Intro to Stats for HS Teachers

A brief overview of statistical reasoning using both descriptive and inferential statistical methods. Special focus on the Advanced Placement statistics course.

#### Credits

Credits 1### MAT 7125 : Intermed Stats for HS Teachers

Workshop for teachers of introductory statistics. Overview of material just beyond the AP/introductory statistics curriculum, including simulation-based inference, multiple regression, ANOVA, statistical programming, and selected topics.

#### Credits

Credits 1### MAT 7130 : Teaching Intro. Statistics

For current or future teachers of statistics. Combines theoretical framework and hands-on experience in understanding and developing statistical reasoning and thinking necessary for teaching an introductory statistics course. Ideas for addressing common student misconceptions will be addressed. Prerequisites: MAT 1230 or MAT 4310 equivalent.

#### Credits

Credits 3### MAT 7404 : Statistical Methods

Data summarization and display, distributions; binomial, Poisson, normal, t, chi-square and F, estimation, hypothesis testing, linear regression, correlation, statistical software packages.

#### Credits

Credits 3### MAT 7405 : Statistical Methods II

ANOVA: multiple comparison procedures, contrasts, random and fixed effect models, transformations, experimental design, nested designs, randomized blocks, factorials, latin squares, analysis of covariance, multiple regression, correlation, statistical software packages.

#### Credits

Credits 3#### Prerequisites

MAT 7404 :C

### MAT 7500 : Statistical Programming

Use SAS and R for data manipulation, presentation, and summarization. Topics include inputting/importing/exporting data cleaning and manipulation, and numerical and graphical summaries/analyses. Students will be introduced to simulations, SAS macro programming, and R functions.

#### Credits

Credits 3#### Prerequisites

MAT 4310 :Y or STAT 4310 :Y or MAT 7404 :Y or STAT 7404 :Y

### MAT 8400 : Statistical Theory I

Probability, random variables, univariate and multivariate distributions, mathematical expectation, Central Limit Theorem, Law of Large Numbers.

#### Credits

Credits 3### MAT 8401 : Statistical Theory II

Sampling, estimation, hypothesis testing, decision theory, least squares, regression, analysis of variance, Bayesian statistics.

#### Credits

Credits 3#### Prerequisites

MAT 5700 or MAT 8400

### MAT 8406 : Regression Methods

Linear regression, correlation, multiple regression, weighted least squares, residuals and influence diagnostics, model building, variable selection, nonlinear regression.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404

### MAT 8408 : Multivariate Methods

Multivariate normal distribution, principal component analysis, Hotelling T2 test, discriminant function analysis, multivariate analysis of variance, covariance and repeated measurements, canonical correlation analysis, factor analysis, claffication and cluster analysis.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404

### MAT 8410 : Bayesian Statistics

Prior distributions, Posterior distributions, Conjugate priors, the Metropolis-Hastings algorithm, the Gibbs sampler, Markov chain Monte Carlo, Convergence diagnostics, Credible Intervals Hierarchical modeling, Differences between Bayesian and frequentist inference.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404 and MAT 5700 or MAT 8400

### MAT 8412 : Linear Models

Analysis of general linear models, fixed and random effects, variance components, unbalanced data.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404

### MAT 8414 : Categorical Data Anal

Estimation, maximum likelihood, weighted least squares, log- linear models, logistic regression.

#### Credits

Credits 3#### Prerequisites

MAT 8406 :Y

### MAT 8416 : Design of Experiments

Completely randomized, randomized block, latin square, nested, split plot, balanced incomplete block and crossover designs, factorials, systems of confounding, fractional factorials and response surface designs.

#### Credits

Credits 3#### Prerequisites

MAT 8412

### MAT 8424 : Statistics Practicum

Applications of regression analysis, analysis of variance, multivariate data analysis, presentation of results, statistical graphics, interpretation of results, issues relevant to the practice of statistical consulting. Analysis of a selected dataset, with written report and accompanying presentation required. Must have completed 24 credits in the Applied Statistics Program.

#### Credits

Credits 3### MAT 8440 : Statistics Quality Control

Industrial applications of statistical techniques, Deming's 14 points, Ishikawa's charting techniques, control charts for attributes and variables, acceptance sampling, military standards, process capability studies, introduction to Taguchi designs.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404

### MAT 8444 : Time Series and Forecasting

Frequency domain approaches to the analysis of time series, autoregressive models, forecasting.

#### Credits

Credits 3#### Prerequisites

MAT 8406

### MAT 8446 : Survival Data Analysis

Analysis of survival of lifetime data; life tables and Kaplan-Meier estimation, survival analysis with covariates, Cox proportional hazard models.

#### Credits

Credits 3#### Prerequisites

MAT 5700 or MAT 8400 and MAT 8406

### MAT 8448 : Clinical Trials

Basic principles of clinical trials, rationale, history, organization and planning, randomization and ethical issues, sample size determination, study designs: parallel, crossover, repeated measurements, statistical analysis of clinical trials data, interim analyses.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404

### MAT 8450 : Longitudinal Data Analysis

Longitudinal data plots, univariate and multivariate repeated measures ANOVA, generalized linear models, response profile models, linear mixed models, generalized linear mixed models, residual diagnostics, missing data, clinical trials applications, analysis in SAS.

#### Credits

Credits 3#### Prerequisites

MAT 8406 and MAT 5700 or MAT 8400

#### Corequisites

### MAT 8452 : Nonparametric Statistics

One sample rank tests, estimates and confidence intervals, paired replicates, two sample rank tests, nonparametric correlation and regression techniques.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404

### MAT 8454 : Sampling Methods

Sampling and survey methodology, basic sampling theory, random and stratified sampling, systematic sampling errors, estimation procedures.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or MAT 7404

### MAT 8462 : Stochastic Modeling

Monte Carlo Simulation, Markov chains, generating functions, random walk models, gambler's ruin problem, queuing processes, Poisson processes, Gaussian processes.

#### Credits

Credits 3#### Prerequisites

MAT 5700 or MAT 8400

### MAT 8480 : Data Mining & Predictive Analy

Data preparation, Predictive modeling via decision trees, regression models and neural network, Model assessment and implementation, Pattern discovery, Association rule discovery, Text mining.

#### Credits

Credits 3#### Prerequisites

MAT 8406

### STAT 1230 : Intro Statistics I

Displaying and summarizing data, basic probability concepts, normal distributions, sampling distributions, estimation for a single population parameter, regression and correlation. Not open to students who have completed MAT 1505.

#### Credits

Credits 3### STAT 1235 : Intro Statistics II

Probability concepts, hypothesis testing, inferences about means, variances and proportions, contingency tables, analysis of variance. Not open to students who have completed MAT 1505.

#### Credits

Credits 3#### Prerequisites

MAT 1230 or STAT 1230

### STAT 1250 : Stats in Health Care Research

Descriptive and inferential statistics: graphical displays, estimation, & hypothesis testing. Restricted to nursing students; others by special permission only.

#### Credits

Credits 3### STAT 1260 : Elementary Statistics

Introduction to statistics including topics such as study design, graphical and numerical descriptive statistics, bivariate data analysis, probability, sampling distributions, confidence intervals, hypothesis testing, goodness of fit tests, analysis of variance; resampling and simulation using statistical software; interpreting output from and understanding selected algorithms used in statistical packages.

#### Credits

Credits 3### STAT 1313 : Statistics for Life Sciences

Statistical concepts and methods with applications in biological and life sciences; data visualization, descriptive statistics, probability distributions, interval estimation and hypothesis testing for one and two variables, statistical software.

#### Credits

Credits 3### STAT 1430 : Business Statistics

Statistical concepts and methods useful in analyzing problems in all areas of business. Descriptive statistics, probability, sampling distributions, confidence intervals, hypothesis testing, regression analysis, and time series. Applications in various areas of business and economics.

#### Credits

Credits 4### STAT 2310 : Stat for Experimenters

The design and analysis of experiments, probability distributions, basic statistical inference, analysis of variance, block designs and factorial designs. For social and natural science majors.

#### Credits

Credits 3#### Prerequisites

MAT 1315 or MAT 1325 or MAT 1505

### STAT 3021 : Topics in Statistics

Lecture course on a topic from Statistics. May be repeated for credit if topics are different.

#### Credits

Credits 1### STAT 4210 : Bayesian Statistical Analysis

Application of Bayesian statistical procedures. Implementation using the programming language R. Bayes's Theorem. Bayesian statistical inference. Various types of prior distributions. Computer-intensive methods. Assessing the prior. Robustness analysis. Writing Bayesian statistical reports.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or STAT 4310

### STAT 4310 : Stat Methods

Data displays and summarization, probability distributions, point and interval estimation, hypothesis testing, categorical data analysis, regression and correlation.

#### Credits

Credits 3#### Prerequisites

MAT 1505 :Y

### STAT 4315 : Applied Statistical Models

Simple and multiple linear regression, including prediction, correlation, model building, multicollinearity, influential observations, and model fit; ANOVA for designed experiments, including completely randomized, randomized block and factorial designs; Time Series including linear time series models, moving averages, autoregressive and ARIMA models, estimation and forecasting.

#### Credits

Credits 3#### Prerequisites

MAT 1505 and (MAT 1430 or STAT 1430 or MAT 4310 or STAT 4310)

### STAT 4380 : Data Science

Combining and summarizing real-world data to inform decision-making and predictions; data wrangling, visualization, text mining, ethics; uses R programming language. Some programming experience recommended.

#### Credits

Credits 3#### Prerequisites

MAT 1230 or STAT 1230 or MAT 1250 or STAT 1250 or MAT 1313 or STAT 1313 or MAT 1430 or STAT 1430 or MAT 4310 or STAT 4310 or CSC 2300

### STAT 4414 : Categorical Data Analysis

Analysis of categorical response data, including contingency tables, logistic regression, multinomial logistic regression, and generalized linear models.

#### Credits

Credits 3#### Prerequisites

STAT 4315

### STAT 4416 : Design of Experiments

Completely randomized, randomized block, and Latin square designs; full and fractional factorial designs; nested and split plot designs; response surface methology.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or STAT 4310

### STAT 4444 : Applied Time Series Analysis

Time series modeling, forecasting, and diagnostics, with an emphasis on applications from business and the sciences.

#### Credits

Credits 3#### Prerequisites

STAT 4315

### STAT 4450 : Regression for Biostatistics

Regression methods for analyzing medical and biological data, including multiple regression, logistic regression, survival modeling, and longitudinal mixed modeling.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or STAT 4310

### STAT 4452 : Nonparametric Statistics

One-sample, two-sample, and multi-sample rank tests; nonparametric confidence intervals; permutation tests; nonparametric regression and correlation; the bootstrap.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or STAT 4310

### STAT 4480 : Data Mining

Supervised and unsupervised data mining techniques, including clustering, classification, and association rule learning.

#### Credits

Credits 3#### Prerequisites

MAT 4310 or STAT 4310

### STAT 5700 : Probability

Probability, random variables, joint distributions, expected values, limit theorems, distributions derived from the normal distribution.

#### Credits

Credits 3#### Prerequisites

MAT 2500

### STAT 5705 : Theory of Stat Inference

Transformation of random variables, Distributions related to the normal, Central Limit Theorem, Law of Large Numbers, Point estimation, Maximum likelihood estimation, Bias, Consistency, Sufficiency, Confidence intervals, Hypothesis testing, Likelihood ratio tests.

#### Credits

Credits 3#### Prerequisites

MAT 2500 and (MAT 5700 or STAT 5700)

### STAT 5905 : Seminar in Statistics

Supervised study of selected topics or problems in statistics, with student presentations and papers. May be repeated for credit if content is different.

#### Credits

Credits 3#### Prerequisites

(MAT 4315 or STAT 4315) and (MAT 5700 or STAT 5700)

### STAT 5910 : Topics in Statistics

Lecture course in an area of statistics. May be repeated for credit if topics are different. Prerequisites: Dependent on Topic.

#### Credits

Credits 3### STAT 7405 : Statistical Methods II

ANOVA: multiple comparison procedures, contrasts, random and fixed effect models, transformations, experimental design, nested designs, randomized blocks, factorials, latin squares, analysis of covariance, multiple regression, correlation, statistical software packages.

#### Credits

Credits 3#### Prerequisites

MAT 7404 or STAT 7404

### STAT 8470 : Statistical Genetics

Methodologies for analyzing genetic data, including genome-wide association studies, population genetics, and phylogenetics; emphasis on discussing recent research literature in these areas.

#### Credits

Credits 3#### Prerequisites

STAT 5700 or STAT 8400

### STAT 8490 : Deep Learning

Artificial neural networks, convolutional neural networks, recurrent neural networks, self-organizing maps, autoencoders.

#### Credits

Credits 3#### Prerequisites

STAT 8406