Summer Sessions | Courses | Statistics

Course information is posted for 2021. Please check back at a later time for updated 2022 course offerings.

Statistics

The Statistics Department offers a range of courses that build on a foundation in probability and statistical theory to provide practical training in statistical methods, study design, and data analysis.

Check the Directory of Classes for the most up-to-date course information.

Summer 2021 Session Information

  • SESSION A courses are May 3–June 18, 2021
  • SESSION B courses are June 28–August 16, 2021

Visit our calendar for a complete list of Summer dates.

Courses
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INTRO TO STATISTICAL REASONING
STAT1001W001 3 points.

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.

Course Number Section/Call Number Session Times/Location
STAT1001W001 001/11205 Summer A Subterm We 10:45 AM–12:20 PM
Mo 10:45 AM–12:20 PM
Th 10:45 AM–12:20 PM
Tu 10:45 AM–12:20 PM

Instructor Points Enrollment Method of Instruction
Victor de la Pena
3 Closed for Online Registration On-Line Only
INTRODUCTION TO STATISTICS
STAT1101S001 3 points.
Prerequisites: some high school algebra. Designed for students in fields that emphasize quantitative methods. This course satisfies the statistics requirements of all majors except statistics, economics, and engineering. Graphical and numerical summaries, probability, theory of sampling distributions, linear regression, confidence intervals, and hypothesis testing are taught as aids to quantitative reasoning and data analysis. Use of statistical software required. Illustrations are taken from a variety of fields. Data-collection/analysis project with emphasis on study designs is part of the coursework requirement.
Course Number Section/Call Number Session Times/Location
STAT1101S001 001/11074 Summer A Subterm Th 10:45 AM–12:20 PM
We 10:45 AM–12:20 PM
Mo 10:45 AM–12:20 PM
Tu 10:45 AM–12:20 PM

Instructor Points Enrollment Method of Instruction
Anthony Donoghue
3 Closed for Online Registration On-Line Only
INTRODUCTION TO STATISTICS
STAT1101S002 3 points.
Prerequisites: some high school algebra. Designed for students in fields that emphasize quantitative methods. This course satisfies the statistics requirements of all majors except statistics, economics, and engineering. Graphical and numerical summaries, probability, theory of sampling distributions, linear regression, confidence intervals, and hypothesis testing are taught as aids to quantitative reasoning and data analysis. Use of statistical software required. Illustrations are taken from a variety of fields. Data-collection/analysis project with emphasis on study designs is part of the coursework requirement.
Course Number Section/Call Number Session Times/Location
STAT1101S002 002/11076 Summer B Subterm Tu 06:15 PM–07:50 PM
Mo 06:15 PM–07:50 PM
Th 06:15 PM–07:50 PM
We 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
Chengliang Tang
3 Open for Enrollment
(auto-fill waitlist)
On-Line Only
CALC-BASED INTRO TO STATISTICS
STAT1201S001 3 points.
Prerequisites: working knowledge of calculus (differentiation and integration). 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. Satisfies the pre-requisites for ECON W3412.
Course Number Section/Call Number Session Times/Location
STAT1201S001 001/11078 Summer A Subterm Mo 10:45 AM–12:20 PM
Tu 10:45 AM–12:20 PM
We 10:45 AM–12:20 PM
Th 10:45 AM–12:20 PM

Instructor Points Enrollment Method of Instruction
Owen Ward
3 Closed for Online Registration On-Line Only
CALC-BASED INTRO TO STATISTICS
STAT1201S002 3 points.
Prerequisites: working knowledge of calculus (differentiation and integration). 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. Satisfies the pre-requisites for ECON W3412.
Course Number Section/Call Number Session Times/Location
STAT1201S002 002/11082 Summer B Subterm Mo 06:15 PM–07:50 PM
Tu 06:15 PM–07:50 PM
We 06:15 PM–07:50 PM
Th 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
David Rios
3 Open for Enrollment
(auto-fill waitlist)
On-Line Only
CALC-BASED INTRO TO STATISTICS
STAT1201S003 3 points.
Prerequisites: working knowledge of calculus (differentiation and integration). 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. Satisfies the pre-requisites for ECON W3412.
Course Number Section/Call Number Session Times/Location
STAT1201S003 003/12248 Summer A Subterm Tu 06:15 PM–07:50 PM
Mo 06:15 PM–07:50 PM
We 06:15 PM–07:50 PM
Th 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
Daniel Rabinowitz
3 Closed for Online Registration On-Line Only
APPLIED LINEAR REG ANALYSIS
STAT2103W001 3 points.

Prerequisites: An introductory course in statistics (STAT UN1101 is recommended). Students without programming experience in R might find STAT UN2102 very helpful. 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.

Course Number Section/Call Number Session Times/Location
STAT2103W001 001/11206 Summer A Subterm Mo 06:15 PM–07:50 PM
We 06:15 PM–07:50 PM
Tu 06:15 PM–07:50 PM
Th 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
Rongning Wu
3 Closed for Online Registration On-Line Only
Undergraduate Mentored Research
STAT3107W001 3 points.

Prerequisites: the project mentors permission. 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.

Course Number Section/Call Number Session Times/Location
STAT3107W001 001/10897 Full Trm Crs
Instructor Points Enrollment Method of Instruction
Ronald Neath
3 Registration Block
(w/ Self-Managed Wait List)
On-Line Only
Undergraduate Mentored Research
STAT3107W002 3 points.

Prerequisites: the project mentors permission. 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.

Course Number Section/Call Number Session Times/Location
STAT3107W002 002/13088 Full Trm Crs
Instructor Points Enrollment Method of Instruction
Carsten Chong
3 Registration Block
(w/ Self-Managed Wait List)
On-Line Only
Undergraduate Mentored Research
STAT3107W003 3 points.

Prerequisites: the project mentors permission. 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.

Course Number Section/Call Number Session Times/Location
STAT3107W003 003/13436 Full Trm Crs
Instructor Points Enrollment Method of Instruction
Tian Zheng
3 Registration Block
(w/ Self-Managed Wait List)
On-Line Only
INTRODUCTION TO PROBABILITY AND STATISTICS
STAT4001S001 3 points.

Prerequisites: A good working knowledge of calculus, including derivatives, single and double, limits, sums and series. Life is a gamble and with some knowledge of probability / statistics is easier evaluate the risks and rewards involved. Probability theory allows us take a known underlying model and estimate how likely will we be able to see future events. Statistical Inference allows us to take data we have seen and estimate the missing parts of an unknown model. The first part of the course focus on the former and the second part the latter.

Course Number Section/Call Number Session Times/Location
STAT4001S001 001/11103 Summer A Subterm Mo 06:05 PM–07:30 PM
Tu 06:05 PM–07:30 PM
We 06:05 PM–07:30 PM
Th 06:05 PM–07:30 PM

Instructor Points Enrollment Method of Instruction
Tat Sang Fung
3 Closed for Online Registration On-Line Only
PROBABILITY THEORY
STAT4203S001 3 points.
Prerequisites: MATH V1101 Calculus I and MATH V1102 Calculus II, or the equivalent, and STAT W1111 or STAT W1211 (Introduction to Statistics). Corequisites: MATH V1201 Calculus III, or the equivalent, or the instructor's permission. This course can be taken as a single course for students requiring knowledge of probability or as a foundation for more advanced courses. It is open to both undergraduate and master students. This course satisfies the prerequisite for STAT W3107 and W4107. Topics covered include combinatorics, conditional probability, random variables and common distributions, expectation, independence, Bayes' rule, joint distributions, conditional expectations, moment generating functions, central limit theorem, laws of large numbers, characteristic functions.
Course Number Section/Call Number Session Times/Location
STAT4203S001 001/11083 Summer A Subterm Mo 04:30 PM–06:05 PM
Th 04:30 PM–06:05 PM
We 04:30 PM–06:05 PM
Tu 04:30 PM–06:05 PM

Instructor Points Enrollment Method of Instruction
Young Kim
3 Closed for Online Registration On-Line Only
PROBABILITY THEORY
STAT4203S002 3 points.
Prerequisites: MATH V1101 Calculus I and MATH V1102 Calculus II, or the equivalent, and STAT W1111 or STAT W1211 (Introduction to Statistics). Corequisites: MATH V1201 Calculus III, or the equivalent, or the instructor's permission. This course can be taken as a single course for students requiring knowledge of probability or as a foundation for more advanced courses. It is open to both undergraduate and master students. This course satisfies the prerequisite for STAT W3107 and W4107. Topics covered include combinatorics, conditional probability, random variables and common distributions, expectation, independence, Bayes' rule, joint distributions, conditional expectations, moment generating functions, central limit theorem, laws of large numbers, characteristic functions.
Course Number Section/Call Number Session Times/Location
STAT4203S002 002/11084 Summer A Subterm We 10:45 AM–12:20 PM
Th 10:45 AM–12:20 PM
Tu 10:45 AM–12:20 PM
Mo 10:45 AM–12:20 PM

Instructor Points Enrollment Method of Instruction
Shaw-Hwa Lo
3 Closed for Online Registration On-Line Only
PROBABILITY THEORY
STAT4203S003 3 points.
Prerequisites: MATH V1101 Calculus I and MATH V1102 Calculus II, or the equivalent, and STAT W1111 or STAT W1211 (Introduction to Statistics). Corequisites: MATH V1201 Calculus III, or the equivalent, or the instructor's permission. This course can be taken as a single course for students requiring knowledge of probability or as a foundation for more advanced courses. It is open to both undergraduate and master students. This course satisfies the prerequisite for STAT W3107 and W4107. Topics covered include combinatorics, conditional probability, random variables and common distributions, expectation, independence, Bayes' rule, joint distributions, conditional expectations, moment generating functions, central limit theorem, laws of large numbers, characteristic functions.
Course Number Section/Call Number Session Times/Location
STAT4203S003 003/14281 Summer B Subterm Mo 07:00 PM–09:30 PM
We 07:00 PM–09:30 PM

Instructor Points Enrollment Method of Instruction
Michael Sobel
3 Open for Enrollment
(auto-fill waitlist)
On-Line Only
STATISTICAL INFERENCE
STAT4204S001 3 points.
Prerequisites: STAT W3105 Intro. to Probability or STAT W4105 Probability, or the equivalent. 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.
Course Number Section/Call Number Session Times/Location
STAT4204S001 001/11085 Summer A Subterm Th 06:15 PM–07:50 PM
We 06:15 PM–07:50 PM
Mo 06:15 PM–07:50 PM
Tu 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
Ji Meng Loh
3 Closed for Online Registration On-Line Only
Linear Regression Models
STAT4205S001 3 points.

Prerequisites: STAT GU4204 or the equivalent, and a course in linear algebra. 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.

Course Number Section/Call Number Session Times/Location
STAT4205S001 001/14372 Summer B Subterm Tu 07:30 PM–10:00 PM
Th 07:30 PM–10:00 PM

Instructor Points Enrollment Method of Instruction
Haiyuan Wang
3 Open for Enrollment
(auto-fill waitlist)
On-Line Only
STAT COMP & INTRO DATA SCIENCE
STAT4206S001 3 points.
Prerequisites: STAT GU4204 and GU4205 or the equivalent. 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.
Course Number Section/Call Number Session Times/Location
STAT4206S001 001/11086 Summer A Subterm Mo 04:30 PM–06:15 PM
We 04:30 PM–06:15 PM
Tu 04:30 PM–06:15 PM
Th 04:30 PM–06:15 PM

Instructor Points Enrollment Method of Instruction
Gabriel Young
3 Closed for Online Registration On-Line Only
Time Series Analysis
STAT4221S001 3 points.
Prerequisites: STAT GU4205 or the equivalent. Prerequisites: STAT GU4205 or the equivalent. 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.
Course Number Section/Call Number Session Times/Location
STAT4221S001 001/11089 Summer A Subterm Tu 01:00 PM–04:10 PM
Th 01:00 PM–04:10 PM

Instructor Points Enrollment Method of Instruction
Li Haoran
3 Closed for Online Registration On-Line Only
BAYESIAN STATISTICS
STAT4224W001 3 points.

Prerequisites: STAT GU4204 or the equivalent. Bayesian data analysis: building, fitting, evaluating and improving probability models. Prior information, hierachical models and combining information. Linear and nonlinear models. Simulation of fake data and evaluation of methods. Computing using R and Stan.

Course Number Section/Call Number Session Times/Location
STAT4224W001 001/11092 Summer A Subterm Mo 09:00 AM–10:35 AM
Tu 09:00 AM–10:35 AM
We 09:00 AM–10:35 AM
Th 09:00 AM–10:35 AM

Instructor Points Enrollment Method of Instruction
Ronald Neath
3 Closed for Online Registration On-Line Only
STATISTICAL MACHINE LEARNING
STAT4241S001 3 points.
Prerequisites: STAT GU4206 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.
Course Number Section/Call Number Session Times/Location
STAT4241S001 001/11097 Summer A Subterm Th 02:45 PM–04:20 PM
Tu 02:45 PM–04:20 PM
Mo 02:45 PM–04:20 PM
We 02:45 PM–04:20 PM

Instructor Points Enrollment Method of Instruction
Banu Baydil
3 Closed for Online Registration On-Line Only
STATISTICAL METHODS FOR FINANCE
STAT4261S002 3 points.
Prerequisites: STAT GU4204 and STAT GU4205 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.
Course Number Section/Call Number Session Times/Location
STAT4261S002 002/11100 Summer A Subterm Th 06:15 PM–07:50 PM
Mo 06:15 PM–07:50 PM
We 06:15 PM–07:50 PM
Tu 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
Hammou El Barmi
3 Closed for Online Registration On-Line Only
PROBABILITY
STAT5203W001 3 points.

Prerequisites: At least one semester of calculus. A calculus-based introduction to probability theory. 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 Markovs inequality.

Course Number Section/Call Number Session Times/Location
STAT5203W001 001/11209 Summer A Subterm Mo 04:30 PM–06:05 PM
We 04:30 PM–06:05 PM
Tu 04:30 PM–06:05 PM
Th 04:30 PM–06:05 PM

Instructor Points Enrollment Method of Instruction
Young Kim
3 Closed for Online Registration On-Line Only
PROBABILITY
STAT5203W002 3 points.

Prerequisites: At least one semester of calculus. A calculus-based introduction to probability theory. 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 Markovs inequality.

Course Number Section/Call Number Session Times/Location
STAT5203W002 002/14282 Summer B Subterm We 07:00 PM–09:30 PM
Mo 07:00 PM–09:30 PM

Instructor Points Enrollment Method of Instruction
Michael Sobel
3 Open for Enrollment
(auto-fill waitlist)
On-Line Only
STATISTICAL INFERENCE
STAT5204W001 3 points.

Prerequisites: STAT GR5203 or the equivalent, and two semesters of calculus. 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.

Course Number Section/Call Number Session Times/Location
STAT5204W001 001/11210 Summer A Subterm We 06:15 PM–07:50 PM
Tu 06:15 PM–07:50 PM
Th 06:15 PM–07:50 PM
Mo 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
Ji Meng Loh
3 Closed for Online Registration On-Line Only
STAT COMP & INTRO DATA SCIENCE
STAT5206S001 3 points.
Prerequisites: STAT GU5204 and STAT GU5205 Open to MA students in Statistics only 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.
Course Number Section/Call Number Session Times/Location
STAT5206S001 001/11087 Summer A Subterm Mo 04:30 PM–06:15 PM
We 04:30 PM–06:15 PM
Tu 04:30 PM–06:15 PM
Th 04:30 PM–06:15 PM

Instructor Points Enrollment Method of Instruction
Gabriel Young
3 Closed for Online Registration On-Line Only
Time Series Analysis
STAT5221S001 3 points.
Open to MA students in Statistics only Prerequisites: STAT GU4205 or the equivalent. 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.
Course Number Section/Call Number Session Times/Location
STAT5221S001 001/11090 Summer A Subterm Tu 01:00 PM–04:10 PM
Th 01:00 PM–04:10 PM

Instructor Points Enrollment Method of Instruction
Li Haoran
3 Closed for Online Registration On-Line Only
NONPARAMETRIC STATISTICS
STAT5222W001 3 points.

Prerequisites: STAT GR5205 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.

Course Number Section/Call Number Session Times/Location
STAT5222W001 001/11208 Summer A Subterm Mo 01:00 PM–04:10 PM
We 01:00 PM–04:10 PM

Instructor Points Enrollment Method of Instruction
Marco Avella Medina
3 Closed for Online Registration On-Line Only
BAYESIAN STATISTICS
STAT5224W001 3 points.

This course introduces the Bayesian paradigm for statistical inference.  Topics covered include prior and posterior distributions: conjugate priors, informative and non-informative priors; one- and two-sample problems; models for normal data, models for binary data, Bayesian linear models, Bayesian computation: MCMC algorithms, the Gibbs sampler; hierarchical models; hypothesis testing, Bayes factors, model selection; use of statistical software.

 

Prerequisites: A course in the theory of statistical inference, such as STAT GU4204/GR5204 a  course in statistical modeling and data analysis such as STAT GU4205/GR5205.

Course Number Section/Call Number Session Times/Location
STAT5224W001 001/11094 Summer A Subterm We 09:00 AM–10:35 AM
Mo 09:00 AM–10:35 AM
Tu 09:00 AM–10:35 AM
Th 09:00 AM–10:35 AM

Instructor Points Enrollment Method of Instruction
Ronald Neath
3 Closed for Online Registration On-Line Only
STATISTICAL MACHINE LEARNING
STAT5241S001 3 points.
Prerequisites: STAT GR5206 or the equivalent. Open to MA students in Statistics only 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.
Course Number Section/Call Number Session Times/Location
STAT5241S001 001/11096 Summer A Subterm Th 02:45 PM–04:20 PM
We 02:45 PM–04:20 PM
Mo 02:45 PM–04:20 PM
Tu 02:45 PM–04:20 PM

Instructor Points Enrollment Method of Instruction
Banu Baydil
3 Closed for Online Registration On-Line Only
STATISTICAL METHODS FOR FINANCE
STAT5261S001 3 points.
Prerequisites: STAT GR5204 or the equivalent. STAT GR5205 is recommended. Open to MA students in Statistics only 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.
Course Number Section/Call Number Session Times/Location
STAT5261S001 001/11101 Summer A Subterm Mo 06:15 PM–07:50 PM
Th 06:15 PM–07:50 PM
Tu 06:15 PM–07:50 PM
We 06:15 PM–07:50 PM

Instructor Points Enrollment Method of Instruction
Hammou El Barmi
3 Closed for Online Registration On-Line Only
PROFESSIONAL DEVELOPMENT
STAT5391G001 0 points.

The course aims to teach MA in Statistics students how to manage their careers and develop professionally. Topics include resume and cover-letter writing, negotiation, mentoring, interviewing skills and communication across global teams. Top professionals from across the globe speak to students and help improve leadership skills. 

Course Number Section/Call Number Session Times/Location
STAT5391G001 001/ Summer A Subterm
Instructor Points Enrollment Method of Instruction
Tian Zheng
0 Open for Enrollment
(auto-fill waitlist)
On-Line Only
MA Mentored Research
STAT5398G001 1 points.

This course is intended to provide a mechanism to MA students in Statistics who undertake on-campus project work or research. The course may be signed up with a faculty member from the Department of Statistics for academic credit. Students seeking to enroll in the course should identify an on-campus project and a congenial faculty member whose research is appealing to them, and who are able to serve as their mentor. Students should then submit an application to enroll in this course, which will be reviewed and approved by the Faculty Director of the MA in Statistics program.

Course Number Section/Call Number Session Times/Location
STAT5398G001 001/10898 Full Trm Crs
Instructor Points Enrollment Method of Instruction
Wayne Lee
1 Registration Block
(w/ Self-Managed Wait List)
On-Line Only
MA Mentored Research
STAT5398G002 1 points.

This course is intended to provide a mechanism to MA students in Statistics who undertake on-campus project work or research. The course may be signed up with a faculty member from the Department of Statistics for academic credit. Students seeking to enroll in the course should identify an on-campus project and a congenial faculty member whose research is appealing to them, and who are able to serve as their mentor. Students should then submit an application to enroll in this course, which will be reviewed and approved by the Faculty Director of the MA in Statistics program.

Course Number Section/Call Number Session Times/Location
STAT5398G002 002/13375 Full Trm Crs
Instructor Points Enrollment Method of Instruction
Demissie Alemayehu
1 Registration Block
(w/ Self-Managed Wait List)
On-Line Only
MA Mentored Research
STAT5398G003 1 points.

This course is intended to provide a mechanism to MA students in Statistics who undertake on-campus project work or research. The course may be signed up with a faculty member from the Department of Statistics for academic credit. Students seeking to enroll in the course should identify an on-campus project and a congenial faculty member whose research is appealing to them, and who are able to serve as their mentor. Students should then submit an application to enroll in this course, which will be reviewed and approved by the Faculty Director of the MA in Statistics program.

Course Number Section/Call Number Session Times/Location
STAT5398G003 003/13425 Summer A Subterm
Instructor Points Enrollment Method of Instruction
Tian Zheng
1 Registration Block
(w/ Self-Managed Wait List)
On-Line Only
Statistical Fieldwork
STAT5399G001 1 points.
Prerequisites: GR5203; GR5204 &GR5205 and at least 4 approved electives This course is an elective course for students in the M.A. in Statistics program that counts towards the degree requirements. To receive a grade and academic credits for this course, students are expected to engage in approved off-campus internships that can be counted as an elective. Statistical Fieldwork should provide students an opportunity to apply their statistical skills and gain practical knowledge on how statistics can be applied to solve real-world challenges.
Course Number Section/Call Number Session Times/Location
STAT5399G001 001/10899 Summer A Subterm
Instructor Points Enrollment Method of Instruction
Demissie Alemayehu
1 Registration Block
(w/ Self-Managed Wait List)
On-Line Only
Theoretical Statistics
STAT8201G001 3 points.
.
Course Number Section/Call Number Session Times/Location
STAT8201G001 001/10900 Summer A Subterm We 01:30 PM–04:30 PM
Mo 01:30 PM–04:30 PM
Fr 01:30 PM–04:30 PM

Instructor Points Enrollment Method of Instruction
Bodhisattva Sen
3 Open for Enrollment
(auto-fill waitlist)
On-Line Only
STATISTICS INTERNSHIP ELECTIVE
STAT8292G001 3 points.
n/a
Course Number Section/Call Number Session Times/Location
STAT8292G001 001/10901 Full Trm Crs
Instructor Points Enrollment Method of Instruction
Tian Zheng
3 Open for Enrollment
(auto-fill waitlist)
On-Line Only