Courses for Statistics

Unify Course Listings

STAT W 3107x and y Undergraduate Research

This course provides a mechanism for students who undertake research with a faculty member from the Department of Statistics to receive academic credit. Students seeking research opportunities should be proactive and entrepreneurial: identify congenial faculty whose research is appealing, let them know of your interest and your background and skills. - B. Baydil, R. Neath
Prerequisites: the project mentor's permission. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
May be repeated for credit.

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Spring 2016 :: STAT W3107
STAT
3107
22829
001
TuTh 2:40p - 3:55p
602 HAMILTON HALL
S. Mukherjee 73 / 86 [ More Info ]

Introductory Courses

The Department of Statistics offers three first introductory courses, STAT W1001, W1111, and W1211. All three may be taken without preparation in statistics. All three cover roughly the same concepts, but differ substantially in the mathematical maturity that is assumed and in the sophistication of the examples.


STAT W1001 is for students who have no more than the most basic algebra, and may be of interest to students in non-mathematical disciplines seeking to satisfy the Quantitative and Deductive Reasoning requirement. STAT W1111 is for students who have mastered basic algebra; practice is emphasized over mathematical theory. STAT W1211 is for students with competence in differential and integral calculus and emphasizes theory over practice.

STAT W1211 or W1111 may be substituted for ECON BC2411 in satisfaction of the major requirements in Economics. STAT W1211 is required for the major in Mathematics-Statistics, Economics-Statistics, and Statistics, and the for the concentration in Statistics. STAT W1001 and W1111 may be applied to the major requirement in Political Science-Statistics. Students that declared their major in Psychology prior to the 2008-2009 academic year may satisfy their major requirements with STAT W1111 or W1211 in lieu of PSYC BC1101.

STAT W2110 follows on the material of the three introductory courses, and is designed for students interested in developing practical skills. Applications of statistics to current issues in the sciences and social sciences are emphasized.


STAT W 1001x and y Introduction to Statistical Reasoning

A friendly introduction to statistical concepts and reasoning with emphasis on developing statistical intuition rather than on mathematical rigor. Topics include design of experiments, descriptive statistics, correlation and regression, probability, chance variability, sampling, chance models, and tests of significance.
BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Spring 2016 :: STAT W1001
STAT
1001
25430
001
TuTh 6:10p - 7:25p
413 KENT HALL
A. Donoghue 39 / 90 [ More Info ]
STAT
1001
76197
002
MW 10:10a - 11:25a
517 HAMILTON HALL
G. Cohen 79 / 86 [ More Info ]
Autumn 2016 :: STAT W1001
STAT
1001
62634
001
MW 10:10a - 11:25a
517 HAMILTON HALL
Instructor To Be Announced 25 / 85 [ More Info ]
STAT
1001
20936
002
TuTh 10:10a - 11:25a
717 HAMILTON HALL
G. Cohen 49 / 85 [ More Info ]
STAT
1001
63777
003
MW 6:10p - 7:25p
517 HAMILTON HALL
H. Nguyen 37 / 85 [ More Info ]

STAT W 1101x and y Introduction to Statistics

Designed for students in fields that emphasize quantitative methods. Graphical and numerical summaries, probability, theory of sampling distributions, linear regression, analysis of variance, confidence intervals and hypothesis testing. Quantitative reasoning and data analysis. Practical experience with statistical software. Illustrations are taken from a variety of fields. Data-collection/analysis project with emphasis on study designs is part of the coursework requirement.
Prerequisites: intermediate high school algebra. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W1101
STAT
1101
27845
001
MW 11:40a - 12:55p
310 FAYERWEATHER
B. Baydil 87 / 96 [ More Info ]
STAT
1101
14337
002
TuTh 11:40a - 12:55p
310 FAYERWEATHER
S. Davies 56 / 96 [ More Info ]
STAT
1101
16613
003
TuTh 6:10p - 7:25p
310 FAYERWEATHER
S. Davies 22 / 96 [ More Info ]

STAT W 1201x and y Calculus-Based Introduction to Statistics

Designed for students who desire a strong grounding in statistical concepts with a greater degree of mathematical rigor than in STAT W1111. Random variables, probability distributions, pdf, cdf, mean, variance, correlation, conditional distribution, conditional mean and conditional variance, law of iterated expectations, normal, chi-square, F and t distributions, law of large numbers, central limit theorem, parameter estimation, unbiasedness, consistency, efficiency, hypothesis testing, p-value, confidence intervals, maximum likelihood estimation. Serves as the pre-requisite for ECON W3412.
Prerequisites: one semester of calculus. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W1201
STAT
1201
68511
001
MW 8:40a - 9:55a
517 HAMILTON HALL
J. Cunningham 85 / 85 [ More Info ]
STAT
1201
75527
002
TuTh 8:40a - 9:55a
517 HAMILTON HALL
A. Donoghue 53 / 85 [ More Info ]
STAT
1201
70931
003
MW 4:10p - 5:25p
517 HAMILTON HALL
J. Cunningham 85 / 85 [ More Info ]
STAT
1201
10111
004
F 11:40a - 2:25p
517 HAMILTON HALL
S. Kolluri 21 / 85 [ More Info ]

STAT W 1202x Undergraduate Seminar

Prepared with undergraduates majoring in quantitative disciplines in mind, the presentations in this colloquium focus on the interface between data analysis, computation, and theory in interdisciplinary research. Meetings are open to all undergraduates, whether registered or not. Presenters are drawn from the faculty of department in Arts and Sciences, Engineering, Public Health and Medicine. - B. Baydil, R. Neath
Prerequisites: Previous or concurrent enrollment in a course in statistics would make the talks more accessible.
1 point

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W1202
STAT
1202
91046
001
F 10:10a - 11:25a
307 PUPIN LABORATORIES
B. Baydil
R. Neath
9 / 25 [ More Info ]

STAT W 2102y Applied Statistical Computing

This course is an introduction to R programming. After learning basic programming component, such as defining variables and vectors, and learning different data structures in R, students will, via project-based assignments, study more advanced topics, such as recursion, conditionals, modular programming, and data visualization. Students will also learn the fundamental concepts in computational complexity, and will practice writing reports based on their statistical analyses.
Corequisites: An introductory course in statistic (STAT UN1101 is recommended).

STAT W 2103x Applied Linear Regression Analysis

Develops critical thinking and data analysis skills for regression analysis in science and policy settings. Simple and multiple linear regression, non-linear and logistic models, random-effects models. Implementation in a statistical package. Emphasis on real-world examples and on planning, proposing, implementing, and reporting.
Prerequisites: An introductory course in statistics (STAT UN1101 is recommended). Students without programming experience in R might find STAT UN2102 very helpful.
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W2103
STAT
2103
25849
001
MW 2:40p - 3:55p
517 HAMILTON HALL
G. Young 38 / 86 [ More Info ]

STAT W 2104y Applied Categorical Data Analysis

This course covers statistical models amd methods for analyzing and drawing inferences for problems involving categofical data. The goals are familiarity and understanding of a substantial and integrated body of statistical methods that are used for such problems, experience in anlyzing data using these methods, and profficiency in communicating the results of such methods, and the ability to critically evaluate the use of such methods. Topics include binomial proportions, two-way and three-way contingency tables, logistic regression, log-linear models for large multi-way contingency tables, graphical methods. The statistical package R will be used. - J Landwehr
Prerequisites: STAT UN2103 is strongly recommended. Students without programming experience in R might find STAT UN2102 very helpful.
3 points

STAT W 3105x Applied Statistical Methods

This course is intended to give students practical experience with statistical methods beyond linear regression and categorical data analysis. The focus will be on understanding the uses and limitations of models, not the mathematical foundations for the methods. Topics that may be covered include random and mixed-effects models, classical non-parametric techniques, the statistical theory causality, sample survey design, multi-level models, generalized linear regression, generalized estimating equations and over-dispersion, survival analysis including the Kaplan-Meier estimator, log-rank statistics, and the Cox proportional hazards regression model. Power calculations and proposal and report writing will be discussed.
Prerequisites: At least one, and preferably both, of STAT UN2103 and UN2104 are strongly recommended. Students without programming experience in R might find STAT UN2102 very helpful.
3 points

STAT W 3106y Applied Data Mining

Data Mining is a dynamic and fast growing field at the interface of Statistics and Computer Science. The emergence of massive datasets containing millions or even billions of observations provides the primary impetus for the field. Such datasets arise, for instance, in large-scale retailing, telecommunications, astronomy, computational and statistical challenges. This course will provide an overview of current practice in data mining. Specific topics covered with include databases and data warehousing, exploratory data analysis and visualization, descriptive modeling, predictive modeling, pattern and rule discovery, text mining, Bayesian data mining, and causal inference. The use of statistical software will be emphasized. - B. Emir
Prerequisites: STAT UN2103. Students without programming experience in R might find STAT UN2102 very helpful.
3 points

STAT W 4001x and y Introduction to Probability and Statistics

A calculus-based tour of the fundamentals of probability theory and statistical inference. Probability models, random variables, useful distributions, conditioning, expectations, law of large numbers, central limit theorem, point and confidence interval estimation, hypothesis tests, linear regression. This course replaces SIEO 4150. - L. Wright, I. Hueter
Prerequisites: Calculus through multiple integration and infinite sums. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4001
STAT
4001
62983
001
TuTh 8:40a - 9:55a
207 MATHEMATICS BUILDING
L. Wright 35 / 120 [ More Info ]
STAT
4001
23283
002
MW 2:40p - 3:55p
501 NORTHWEST CORNER
M. Brown 91 / 120 [ More Info ]

Foundation Courses

The Department offers STAT W3105, W3107, and W4315 as a sequence. W3105 covers probability theory and is a prerequisite for W3107. W3107 covers statistical theory, and is a prerequisite for STAT W4315. STAT W4315 covers linear regression models, and provides an introduction to practical issues in data analysis. Students who have difficulty scheduling STAT W3105 or W3107 may substitute, respectively, STAT W4105 and W4107, or substitute, for the pair, the combined course STAT W4109. The sequences is a pre-requisite for the advanced undergraduate offerings in the Department (except W4604 and W4835, which have only W3105 as a prerequisite, and W4204, which has only STAT W3105 and W3107 as co-requisites). STAT W4150 is an abridged version of W3105 and W3107 designed especially for SEAS students.

STAT W 4203x Probability Theory

A calculus-based introduction to probability theory. A quick review of multivariate calculus is provided. Topics covered include random variables, conditional probability, expectation, independence, Bayes' rule, important distributions, joint distributions, moment generating functions, central limit theorem, laws of large numbers and Markov's inequality.
Prerequisites: At least one semester, and preferably two, of calculus. An introductory course (STAT UN2101, preferably) is strongly recommended. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4203
STAT
4203
68099
001
TuTh 2:40p - 3:55p
903 SCHOOL OF SOCIAL WORK
S. Lo 26 / 80 [ More Info ]
STAT
4203
75535
003
MW 6:10p - 7:25p
501 NORTHWEST CORNER
M. Sobel 20 / 90 [ More Info ]
STAT
4203
87194
006
MW 6:10p - 8:55p
310 FAYERWEATHER
B. Baydil 6 / 90 [ More Info ]

STAT W 4204y Statistical Inference

Calculus-based introduction to the theory of statistics. Useful distributions, law of large numbers and central limit theorem, point estimation, hypothesis testing, confidence intervals maximum likelihood, likelihood ratio tests, nonparametric procedures, theory of least squares and analysis of variance.
Prerequisites: STAT GU4203. At least one semester of calculus is required; two or three semesters are strongly recommended. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4204
STAT
4204
27746
003
TuTh 4:10p - 5:25p
501 NORTHWEST CORNER
A. Safikhani 22 / 90 [ More Info ]
STAT
4204
19259
D04
MW 8:40a - 11:25a
903 SCHOOL OF SOCIAL WORK
R. Dolgoarshinnykh 7 / 15 [ More Info ]

STAT W 4205x Linear Regression Models

Theory and practice of regression analysis. Simple and multiple regression, testing, estimation, prediction, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Extensive use of the computer to analyse data.
Prerequisites: STAT GU4204 or the equivalent, and a course in linear algebra.
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4205
STAT
4205
65947
001
MW 2:40p - 3:55p
207 MATHEMATICS BUILDING
A. Maleki 25 / 25 [ More Info ]
STAT
4205
77031
002
TuTh 2:40p - 3:55p
501 NORTHWEST CORNER
A. Maleki 25 / 25 [ More Info ]
STAT
4205
25514
003
TuTh 6:10p - 7:25p
501 NORTHWEST CORNER
G. Young 21 / 25 [ More Info ]
STAT
4205
73323
004
MW 1:10p - 2:25p
517 HAMILTON HALL
R. Neath 17 / 65 [ More Info ]

STAT W 4206x Statistical Computing and Introduction to Data Science

Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction. Writing code for numerical and graphical statistical analyses. Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets. Examples from data science will be used for demonstration.
Prerequisites: STAT GU4204 and GU4205 or the equivalent.
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4206
STAT
4206
88014
001
F 1:10p - 2:25p
503 HAMILTON HALL
F 8:40a - 11:25a
903 SCHOOL OF SOCIAL WORK
G. Young 25 / 46 [ More Info ]

STAT W 4207x and y Elementary Stochastic Processes

Review of elements of probability theory. Poisson processes. Renewal theory. Wald's equation. Introduction to discrete and continuous time Markov chains. Applications to queueing theory, inventory models, branching processes. - M. Brown
Prerequisites: STAT GU4203 and two, preferably three, semesters of calculus. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4207
STAT
4207
21098
001
F 2:40p - 5:25p
310 FAYERWEATHER
M. Brown 30 / 30 [ More Info ]

Advanced Courses

STAT W 3201x or y Math Finance in Continuous Time

This follows MATH V3050. Basic concepts in probability theory, and then advanced concepts, including Brownian motion, stochastic calculus, expectation, Radon-Nikodym theorem, Girsanov's theorem, stochastic differential equations (inlcuding Black-Merton-Scholes), options and hedging, stochastic interest rates, forwards and futures. Formal proofs will be eschewed in favor of understanding concepts.
Prerequisites: MATH V3050. Not offered in 2016-2017.
3 points

STAT W 4221x and y Time Series Analysis

Least squares smoothing and prediction, linear systems, Fourier analysis, and spectral estimation. Impulse response and transfer function. Fourier series, the fast Fourier transform, autocorrelation function, and spectral density. Univariate Box-Jenkins modeling and forecasting. Emphasis on applications. Examples from the physical sciences, social sciences, and business. Computing is an integral part of the course.
Prerequisites: STAT GU4205 or the equivalent. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4221
STAT
4221
73322
001
MW 7:40p - 8:55p
417 MATHEMATICS BUILDING
I. Hueter 15 / 15 [ More Info ]

STAT W 4222y Nonparametric Statistics

Statistical inference without parametric model assumption. Hypothesis testing using ranks, permutations, and order statistics. Nonparametric analogs of analysis of variance. Non-parametric regression, smoothing and model selection. - B. Sen
Prerequisites: STAT GU4204 or the equivalent. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

STAT W 4223y Multivariate Statistical Inference

Multivariate normal distribution, multivariate regression and classification; canonical correlation; graphical models and Bayesian networks; principal components and other models for factor analysis; SVD; discriminant analysis; cluster analysis.
Prerequisites: STAT GU4205 or the equivalent.

STAT W 4224y Bayesian Statistics

Bayesian vs frequentist, prior and posterior distributions, conjugate priors, informative and non-informative prior subjective and objective bayes, oneand two sample problems, models for normal data, models for binary data, multivariate normal shrinkage, bayesian linear models, bayesian computation (start early), MCMC algorithms, the Gibbs sampler, hierarchical models, empirical bayes, hypothesis testing, bayes factors, model selection, software: R and WinBUGS
Prerequisites: STAT GU4204 or the equivalent.
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4224
STAT
4224
63446
001
MW 2:40p - 3:55p
417 MATHEMATICS BUILDING
R. Neath 19 / 20 [ More Info ]

STAT W 4231y Survival Analysis

Survival distributions, types of censored data, estimation for various survival models, nonparametric estimation of survival distributions, the proportional hazard and accelerated lifetime models for regression analysis with failure-time data. Extensive use of the computer. - M. Shnaidman
Prerequisites: STAT GU4205 or the equivalent. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..

STAT W 4232y Generalized Linear Models

Statistical methods for rates and proportions, ordered and nominal categorical responses, contingency tables, odds-ratios, exact inference, logistic regression, Poisson regression, generalized linear models. - M. Sobel
Prerequisites: STAT GU4205 or the equivalent. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

STAT W 4233x Multilevel Models

Theory and practice, including model-checking, for random and mixed-effects models (also called hierarchical, multi-level models). Extensive use of the computer to analyse data.
Prerequisites: STAT GU4205 or the equivalent. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA).. Not offered in 2016-2017.

STAT W 4234y Sample Surveys

Introductory course on the design and analysis of sample surveys. How sample surveys are conducted, why the designs are used, how to analyze survey results, and how to derive from first principles the standard results and their generalizations. Examples from public health, social work, opinion polling, and other topics of interest. - M. Sobel
Prerequisites: STAT GU4204 or the equivalent. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4234
STAT
4234
91847
001
TuTh 6:10p - 7:25p
214 PUPIN LABORATORIES
R. Wu 8 / 25 [ More Info ]

STAT W 4241y Statistical Machine Learning

The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to provide students of statistics with detailed knowledge of how Machine Learning methods work and how statistical models can be brought to bear in computer systems - not only to analyze large data sets, but to let computers perform tasks that traditional methods of computer science are unable to address. Examples range from speech recognition and text analysis through bioinformatics and medical diagnosis. This course provides a first introduction to the statistical methods and mathematical concepts which make such technologies possible. - Peter Orbanz
Prerequisites: STAT GU4206.

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4241
STAT
4241
19264
001
MW 2:40p - 3:55p
312 MATHEMATICS BUILDING
L. Liu 23 / 25 [ More Info ]

STAT Q 4242x Advanced Machine Learning

his course covers some advanced topics in machine learning and has an emphasis on applications to real world data. A major part of this course is a course project which consists of an in-class presentation and a written project report.
Prerequisites: STAT GU4241 Not offered in 2016-2017.
3 points

STAT W 4243y Applied Data Science

This course will incorporate knowledge and skills covered in a statistical curriculum with topics and projects in data science. Programming will covered using existing tools in R. Computing best practices will be taught using test-driven development, version control, and collaboration. Students finish the class with a portfolio on GitHub, and deeper understanding of several core statistical/machine-learning algorithms. Bi-weekly project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications. - Tian Zheng
Prerequisites: STAT GU4206 or the equivalent.
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4243
STAT
4243
78248
001
W 2:40p - 5:25p
329 PUPIN LABORATORIES
T. Zheng 27 / 25 [ More Info ]

STAT W 4261x and y Statistical Methods in Finance

A fast-paced introduction to statistical methods used in quantitative finance. Financial applications and statistical methodologies are intertwined in all lectures. Topics include regression analysis and applications to the Capital Asset Pricing Model and multifactor pricing models, principal components and multivariate analysis, smoothing techniques and estimation of yield curves statistical methods for financial time series, value at risk, term structure models and fixed income research, and estimation and modeling of volatilities. Hands-on experience with financial data.
Prerequisites: STAT GU4205 or the equivalent. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4261
STAT
4261
87297
002
F 11:40a - 2:10p
203 MATHEMATICS BUILDING
H. ElBarmi 15 / 20 [ More Info ]

STAT W 4262y Stochastic Processes for Finance

A careful review of the concept of stochastic process as a model of random phenomena evolving through time and of conditional expectation, basic Markov process theory, and the exponential distribution. Marked point processes and their compensators, beginning with Poisson processes, and proceeding through general marked point processes. The use of compensators will be justified by the Doob-Meyer decomposition theorem, and as such it will connect the theory to martingales. Markov processes will enter to provide a description of sufficient conditions for the compensators to have absolutely continuous paths (and as such, have "hazard rates"). Applications to survival analysis and, especially, to mathematical finance, including default and bankruptcy models. Cox process construction. This is a core course in the MS program in mathematical finance.
Prerequisites: STAT GU4203. STAT GU4207 is recommended.
3 points

STAT W 4263y Statistical Inference and Time-Series Modelling

Modeling and inference for random processes, from natural sciences to finance and economics. ARMA, ARCH, GARCH and nonlinear models, parameter estimation, prediction and filtering. This is a core course in the MS program in mathematical finance.
Prerequisites: STAT GU4204 or the equivalent. STAT GU4205 is recommended.
3 points

STAT G 4264x and y Stochastic Processes and Applications

Basics of continuous-time stochastic processes. Wiener processes. Stochastic integrals. Ito's formula, stochastic calculus. Stochastic exponentials and Girsanov's theorem. Gaussian processes. Stochastic differential equations. Additional topics as time permits.
Prerequisites: STAT GU4203. STAT GU4207 is recommended.
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT G4264
STAT
4264
60531
001
MW 6:10p - 7:25p
614 SCHERMERHORN HALL
I. Karatzas 9 / 30 [ More Info ]
STAT
4264
77032
002
TuTh 4:10p - 5:25p
TBA
L. Nielsen 1 / 30 [ More Info ]

STAT W 4265x and y Stochastic Methods in Finance

Mathematical theory and probabilistic tools for modeling and analyzing security markets are developed. Pricing options in complete and incomplete markets, equivalent martingale measures, utility maximization, term structure of interest rates. This is a core course in the MS program in mathematical finance.
Prerequisites: STAT GU4264.
3 points

STAT G 4266 Stochastic Control and Applications in Finance

The course provides an introduction ot th eoptimal control of stochastic systems in continuous time. The topics are centered around controlled diffusions and otpimal stoppping, and illustrated by applications in Finance such as Merton's portfolio allocation problem, quadratic hedging, optimal liquidation, or the pricing of American options. The thoery of dynamic programming is developled together with the associated partial differnetial equations (Hamilton-Jacobi-Bellman equations)and boundary value problems, and complemented by the conved duality method. - M Nutz
Prerequisites: STAT GU4265 Not offered in 2016-2017.

STAT W 4291x and y Advanced Data Analysis

This is a course on getting the most out of data. The emphasis will be on hands-on experience, involving case studies with real data and using common statistical packages. The course covers, at a very high level, exploratory data analysis, model formulation, goodness of fit testing, and other standard and non-standard statistical procedures, including linear regression, analysis of variance, nonlinear regression, generalized linear models, survival analysis, time series analysis, and modern regression methods. Students will be expected to propose a data set of their choice for use as case study material. - Demissie Alemayehu
Prerequisites: STAT GU4205 and at least one statistics course numbered between GU4221 and GU4261. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA)..
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4291
STAT
4291
23324
001
F 6:10p - 8:55p
309 HAVEMEYER HALL
D. Alemayehu 9 / 25 [ More Info ]

STAT W 4702y Exploratory Data Analysis and Visualization

This course is covers the following topics: fundamentals of data visualization, layered grammer of graphics, perception of discrete and continuous variables, intreoduction to Mondran, mosaic pots, parallel coordinate plots, introduction to ggobi, linked pots, brushing, dynamic graphics, model visualization, clustering and classification.
Prerequisites: A course in computer programming.
3 points

Actuarial Science Courses

STAT W 4281x Theory of Interest

Introduction to the mathematical theory of interest as well as the elements of economic and financial theory of interest. Topics include rates of interest and discount; simple, compound, real, nominal, effective, dollar (time)-weighted; present, current, future value; discount function; annuities; stocks and other instruments; definitions of key terms of modern financial analysis; yield curves; spot (forward) rates; duration; immunization; and short sales. The course will cover determining equivalent measures of interest; discounting; accumulating; determining yield rates; and amortization.
Prerequisites: At least one semester of calculus.
3 points

STAT W 4282x Linear Regression and Time Series Methods

A one semester course covering: simple and multiple regression, including testing, estimation, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Linear time series models. Auto-regressive, moving average and ARIMA models. Estimation and forecasting with time series models. Confidence intervals and prediction error. Students may not receive credit for more than two of STAT W4315, W4437, and W4440. Satisfies the SOA VEE requirements in regression and in time-series.
Prerequisites: STAT GU4204 or the equivalent.
3 points

Course
Number
Call Number/
Section
Days & Times/
Location
Instructor Enrollment
Autumn 2016 :: STAT W4282
STAT
4282
88648
001
TuTh 1:10p - 2:25p
413 KENT HALL
F. Bartman 37 / 60 [ More Info ]

There are currently no cross-listed courses for your department.