# Statistics

The Department of Statistics offers courses in the basic principles and techniques of probability and statistics, advanced theory and methods courses, courses in stochastic processes and methods, and courses statistical methods in finance.

For questions about specific courses, contact the department.

For questions about specific courses, contact the department.

### Courses

##### Course Number

STAT1001W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 14:40-15:55We 14:40-15:55

##### Section/Call Number

001/13610##### Enrollment

76 of 86##### Instructor

Ronald Neath##### Course Number

STAT1001W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 10:10-11:25We 10:10-11:25

##### Section/Call Number

002/13674##### Enrollment

33 of 50##### Instructor

Shaw-Hwa LoA 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

STAT1001W003##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

003/13611##### Enrollment

67 of 86##### Instructor

Victor de la PenaThe advent of large scale data collection and the computer power to analyze the data has led to the emergence of a new discipline known as Data Science. Data Scientists in all sectors analyze data to derive business insights, find solutions to societal challenges, and predict outcomes with potentially high impact. The goal of this course is to provide the student with a rigorous understanding of the statistical thinking behind the fundamental techniques of statistical analysis used by data scientists. The student will learn how to apply these techniques to data, understand why they work and how to use the analysis results to make informed decisions. The student will gain this understanding in the classroom and through the analysis of real-world data in the lab using the programming language Python. The student will learn the fundamentals of Python and how to write and run code to apply the statistical concepts taught in the classroom.

##### Course Number

STAT1010W001##### Format

In-Person##### Points

4 pts#### Spring 2024

##### Times/Location

Mo 13:10-14:25We 13:10-14:25

We 14:40-15:55

##### Section/Call Number

001/13612##### Enrollment

27 of 86##### Instructor

Anthony Donoghue##### Course Number

STAT1101W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 08:40-09:55We 08:40-09:55

##### Section/Call Number

001/13613##### Enrollment

76 of 86##### Instructor

Alexander Clark##### Course Number

STAT1101W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 10:10-11:25Th 10:10-11:25

##### Section/Call Number

002/13614##### Enrollment

72 of 86##### Instructor

David Rios##### Course Number

STAT1101W003##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 18:10-19:25We 18:10-19:25

##### Section/Call Number

003/13615##### Enrollment

71 of 86##### Instructor

Banu Baydil##### Course Number

STAT1201W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 10:10-11:25We 10:10-11:25

##### Section/Call Number

001/13616##### Enrollment

80 of 86##### Instructor

Pratyay Datta##### Course Number

STAT1201W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 08:40-09:55We 08:40-09:55

##### Section/Call Number

002/13617##### Enrollment

80 of 85##### Instructor

Joyce Robbins##### Course Number

STAT1201W003##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Th 10:10-11:25Tu 10:10-11:25

##### Section/Call Number

003/13618##### Enrollment

90 of 86##### Instructor

Joyce Robbins##### Course Number

STAT1201W004##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 18:10-19:25We 18:10-19:25

##### Section/Call Number

004/13619##### Enrollment

72 of 86##### Instructor

Sheela Kolluri##### Course Number

STAT2102W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 16:10-17:25Th 16:10-17:25

##### Section/Call Number

001/13620##### Enrollment

80 of 120##### Instructor

Alex PijyanPrerequisites: 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

STAT2103W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 18:10-19:25We 18:10-19:25

##### Section/Call Number

001/13621##### Enrollment

24 of 84##### Instructor

Daniel Rabinowitz##### Course Number

STAT2104W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 08:40-09:55We 08:40-09:55

##### Section/Call Number

001/13622##### Enrollment

40 of 86##### Instructor

Ronald Neath##### Course Number

STAT3106W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 14:40-15:55Th 14:40-15:55

##### Section/Call Number

001/13623##### Enrollment

51 of 50##### Instructor

Alex Pijyan##### Course Number

STAT3107W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

001/13624##### Enrollment

2 of 2##### Instructor

Arian MalekiPrerequisites: 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

STAT3107W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

002/21075##### Enrollment

0 of 2##### Instructor

Anne van DelftTopics in Modern Statistics that provide undergraduate students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field. Courses listed are reviewed and approved by the Undergraduate Advisory Committee of the Department of Statistics.

##### Course Number

STAT3293W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 14:40-15:55Th 14:40-15:55

##### Section/Call Number

002/15045##### Enrollment

1 of 16##### Instructor

Joyce RobbinsPrerequisites: Calculus through multiple integration and infinite sums. 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.

##### Course Number

STAT4001W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 18:10-20:40##### Section/Call Number

001/13625##### Enrollment

79 of 100##### Instructor

Pratyay DattaPrerequisites: Calculus through multiple integration and infinite sums. 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.

##### Course Number

STAT4001W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 13:10-14:25We 13:10-14:25

##### Section/Call Number

002/13626##### Enrollment

72 of 86##### Instructor

Hammou El Barmi##### Course Number

STAT4203W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

001/13627##### Enrollment

56 of 60##### Instructor

David Rios##### Course Number

STAT4203W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

002/13628##### Enrollment

0 of 5##### Instructor

David Rios##### Course Number

STAT4204W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 13:10-14:25Th 13:10-14:25

##### Section/Call Number

001/13629##### Enrollment

14 of 45##### Instructor

Banu Baydil##### Course Number

STAT4204W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

002/13632##### Enrollment

25 of 35##### Instructor

Cristian Pasarica##### Course Number

STAT4204W003##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

003/13675##### Enrollment

37 of 37##### Instructor

Cristian Pasarica##### Course Number

STAT4205W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 19:40-20:55We 19:40-20:55

##### Section/Call Number

001/13676##### Enrollment

22 of 50##### Instructor

Jeonghoe Lee##### Course Number

STAT4206W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 10:10-12:40##### Section/Call Number

001/13630##### Enrollment

19 of 40##### Instructor

Alex Pijyan##### Course Number

STAT4207W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 16:10-17:25Th 16:10-17:25

##### Section/Call Number

001/13677##### Enrollment

17 of 50##### Instructor

Anne van Delft##### Course Number

STAT4207W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 11:40-12:55We 11:40-12:55

##### Section/Call Number

002/13631##### Enrollment

16 of 35##### Instructor

Mark Brown##### Course Number

STAT4221W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Sa 10:10-12:40##### Section/Call Number

001/13633##### Enrollment

7 of 25##### Instructor

Franz RembartPrerequisites: STAT GU4204 or the equivalent. 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

STAT4222W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 10:10-11:25We 10:10-11:25

##### Section/Call Number

001/13678##### Enrollment

0 of 25##### Instructor

Alberto Gonzalez Sanz##### Course Number

STAT4224W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 19:40-20:55Th 19:40-20:55

##### Section/Call Number

001/13634##### Enrollment

17 of 25##### Instructor

Dobrin Marchev##### Course Number

STAT4234W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 14:40-15:55Th 14:40-15:55

##### Section/Call Number

001/13635##### Enrollment

2 of 7##### Instructor

Rongning Wu##### Course Number

STAT4241W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 10:10-11:25We 10:10-11:25

##### Section/Call Number

001/13636##### Enrollment

15 of 50##### Instructor

Samory Kpotufe##### Course Number

STAT4243W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 18:10-20:40##### Section/Call Number

001/13637##### Enrollment

11 of 22##### Instructor

Haiyuan WangPrerequisites: Pre-requisite for this course includes working knowledge in Statistics and Probability, data mining, statistical modeling and machine learning. Prior programming experience in R or Python is required. This course will incorporate knowledge and skills covered in a statistical curriculum with topics and projects in data science. Programming will be 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 of projects, and deeper understanding of several core statistical/machine-learning algorithms. Short project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications.

##### Course Number

STAT4243W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

We 18:10-20:55##### Section/Call Number

002/17757##### Enrollment

7 of 10##### Instructor

Ying Liu##### Course Number

STAT4261W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Sa 10:10-12:40##### Section/Call Number

001/13638##### Enrollment

23 of 25##### Instructor

Zhiliang Ying##### Course Number

STAT4264G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 16:10-17:25We 16:10-17:25

##### Section/Call Number

001/13639##### Enrollment

3 of 25##### Instructor

Steven Campbell##### Course Number

STAT4265G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

001/13679##### Enrollment

4 of 25##### Instructor

Graeme Baker##### Course Number

STAT4291W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 10:10-12:40##### Section/Call Number

001/13640##### Enrollment

5 of 25##### Instructor

Gabriel Young##### Course Number

STAT5203W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

001/13673##### Enrollment

13 of 25##### Instructor

David Rios##### Course Number

STAT5204W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

001/13642##### Enrollment

14 of 25##### Instructor

Cristian Pasarica##### Course Number

STAT5205W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 19:40-20:55We 19:40-20:55

##### Section/Call Number

001/13643##### Enrollment

8 of 50##### Instructor

Jeonghoe Lee##### Course Number

STAT5206W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 10:10-12:40##### Section/Call Number

001/13644##### Enrollment

38 of 50##### Instructor

Alex Pijyan##### Course Number

STAT5207W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 11:40-12:55We 11:40-12:55

##### Section/Call Number

001/13645##### Enrollment

43 of 100##### Instructor

Mark Brown##### Course Number

STAT5221W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Sa 10:10-12:40##### Section/Call Number

001/13646##### Enrollment

23 of 125##### Instructor

Franz RembartPrerequisites: 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

STAT5222W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 10:10-11:25We 10:10-11:25

##### Section/Call Number

001/13647##### Enrollment

7 of 86##### Instructor

Alberto Gonzalez Sanz##### Course Number

STAT5224W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 19:40-20:55Th 19:40-20:55

##### Section/Call Number

001/13648##### Enrollment

32 of 125##### Instructor

Dobrin Marchev##### Course Number

STAT5234W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 14:40-15:55Th 14:40-15:55

##### Section/Call Number

001/13649##### Enrollment

44 of 101##### Instructor

Rongning Wu##### Course Number

STAT5241W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 18:10-20:40##### Section/Call Number

001/13650##### Enrollment

60 of 86##### Instructor

Parijat Dube##### Course Number

STAT5241W002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

002/13651##### Enrollment

39 of 125##### Instructor

Yisha Yao##### Course Number

STAT5241W003##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 14:40-15:55Th 14:40-15:55

##### Section/Call Number

003/13652##### Enrollment

124 of 125##### Instructor

Chenyang ZhongPrerequisites: Pre-requisite for this course includes working knowledge in Statistics and Probability, data mining, statistical modeling and machine learning. Prior programming experience in R or Python is required. 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 of projects, and deeper understanding of several core statistical/machine-learning algorithms. Short project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications.

##### Course Number

STAT5243W001##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 18:10-20:40##### Section/Call Number

001/13653##### Enrollment

75 of 85##### Instructor

Haiyuan WangPrerequisites: Pre-requisite for this course includes working knowledge in Statistics and Probability, data mining, statistical modeling and machine learning. Prior programming experience in R or Python is required. 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 of projects, and deeper understanding of several core statistical/machine-learning algorithms. Short project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications.

##### Course Number

STAT5243W002##### Points

3 pts#### Spring 2024

##### Times/Location

We 18:10-20:55##### Section/Call Number

002/17184##### Enrollment

43 of 65##### Instructor

Ying Liu##### Course Number

STAT5261W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Sa 10:10-12:40##### Section/Call Number

001/13654##### Enrollment

123 of 150##### Instructor

Zhiliang Ying##### Course Number

STAT5264G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 16:10-17:25We 16:10-17:25

##### Section/Call Number

001/13680##### Enrollment

22 of 86##### Instructor

Steven Campbell##### Course Number

STAT5265G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 18:10-19:25Th 18:10-19:25

##### Section/Call Number

001/13655##### Enrollment

118 of 135##### Instructor

Graeme Baker##### Course Number

STAT5291W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 10:10-12:40##### Section/Call Number

001/13656##### Enrollment

142 of 225##### Instructor

Gabriel YoungTopics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

##### Course Number

STAT5293G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 14:40-15:55Th 14:40-15:55

##### Section/Call Number

001/13657##### Enrollment

11 of 70##### Instructor

Joyce RobbinsTopics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

##### Course Number

STAT5293G002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 17:40-18:55We 17:40-18:55

##### Section/Call Number

002/13658##### Enrollment

2 of 28##### Instructor

Musa Elbulok##### Course Number

STAT5293G003##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

We 18:10-20:40##### Section/Call Number

003/13659##### Enrollment

40 of 60##### Instructor

Lei KangTopics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

##### Course Number

STAT5293G004##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 08:30-10:00Th 08:30-10:00

##### Section/Call Number

004/16440##### Enrollment

16 of 35##### Instructor

Andrew Gelman##### Course Number

STAT5293G005##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 18:10-20:40##### Section/Call Number

005/17173##### Enrollment

12 of 30##### Instructor

Baron LawThis 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

STAT5398G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

001/13660##### Enrollment

25 of 35##### Instructor

Demissie Alemayehu##### Course Number

STAT5399G001##### Format

In-Person##### Points

1 pts#### Spring 2024

##### Section/Call Number

001/13661##### Enrollment

1 of 25##### Instructor

Demissie Alemayehu##### Course Number

STAT5703W001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 17:40-18:55Th 17:40-18:55

##### Section/Call Number

001/13662##### Enrollment

160 of 180##### Instructor

Dobrin MarchevThis is only recitation for STAT GR5703. We are requesting 3 sections of recitation to align with the one section of 5703 being offered.

##### Course Number

STAT5704G001##### Format

In-Person##### Points

0 pts#### Spring 2024

##### Times/Location

Tu 14:40-15:55##### Section/Call Number

001/18746##### Enrollment

64 of 60##### Instructor

Alessandro ProsperiThis is only recitation for STAT GR5703. We are requesting 3 sections of recitation to align with the one section of 5703 being offered.

##### Course Number

STAT5704G002##### Format

In-Person##### Points

0 pts#### Spring 2024

##### Times/Location

Mo 14:40-15:55##### Section/Call Number

002/18747##### Enrollment

43 of 60##### Instructor

Haolin ZouThis is only recitation for STAT GR5703. We are requesting 3 sections of recitation to align with the one section of 5703 being offered.

##### Course Number

STAT5704G003##### Format

In-Person##### Points

0 pts#### Spring 2024

##### Times/Location

Th 16:10-17:25##### Section/Call Number

003/18748##### Enrollment

59 of 60##### Instructor

Getoar Sopa##### Course Number

STAT6102G001##### Format

In-Person##### Points

4 pts#### Spring 2024

##### Times/Location

Mo 10:10-11:25We 10:10-11:25

##### Section/Call Number

001/13663##### Enrollment

12 of 24##### Instructor

Yuqi Gu##### Course Number

STAT6104G001##### Format

In-Person##### Points

4 pts#### Spring 2024

##### Times/Location

Tu 14:10-16:00##### Section/Call Number

001/13664##### Enrollment

15 of 25##### Instructor

Liam Paninski##### Course Number

STAT6105G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 08:40-09:55We 08:40-09:55

##### Section/Call Number

001/13665##### Enrollment

15 of 15##### Instructor

Regina Dolgoarshinnykh##### Course Number

STAT6202G001##### Format

In-Person##### Points

4 pts#### Spring 2024

##### Times/Location

Mo 14:40-15:55We 14:40-15:55

##### Section/Call Number

001/13681##### Enrollment

11 of 25##### Instructor

Cynthia Rush##### Course Number

STAT6302G001##### Format

In-Person##### Points

4 pts#### Spring 2024

##### Times/Location

Tu 10:10-11:25Th 10:10-11:25

##### Section/Call Number

001/13666##### Enrollment

12 of 25##### Instructor

Marcel NutzIndependent Study with Faculty Advisor must be registered for every semester after first academic year

##### Course Number

STAT8001R001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

001/13781##### Enrollment

2 of 5##### Instructor

Marco Avella MedinaIndependent Study with Faculty Advisor must be registered for every semester after first academic year

##### Course Number

STAT8001R002##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

002/13788##### Enrollment

4 of 5##### Instructor

David BleiIndependent Study with Faculty Advisor must be registered for every semester after first academic year

##### Course Number

STAT8001R003##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

003/13791##### Enrollment

1 of 5##### Instructor

John Cunningham##### Course Number

STAT8001R004##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

004/13797##### Enrollment

2 of 5##### Instructor

Richard Davis##### Course Number

STAT8001R005##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

005/13802##### Enrollment

1 of 5##### Instructor

Victor de la Pena##### Course Number

STAT8001R006##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

006/13808##### Enrollment

2 of 5##### Instructor

Bianca Dumitrascu##### Course Number

STAT8001R007##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

007/13812##### Enrollment

1 of 5##### Instructor

Andrew Gelman##### Course Number

STAT8001R008##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

008/13816##### Enrollment

0 of 5##### Instructor

Yuqi Gu##### Course Number

STAT8001R009##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

009/13818##### Enrollment

2 of 5##### Instructor

Ioannis Karatzas##### Course Number

STAT8001R010##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

010/13820##### Enrollment

3 of 5##### Instructor

Samory Kpotufe##### Course Number

STAT8001R011##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

011/13822##### Enrollment

1 of 5##### Instructor

Jingchen Liu##### Course Number

STAT8001R012##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

012/13824##### Enrollment

0 of 5##### Instructor

Shaw-Hwa Lo##### Course Number

STAT8001R013##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

013/13827##### Enrollment

2 of 5##### Instructor

Arian Maleki##### Course Number

STAT8001R014##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

014/13831##### Enrollment

3 of 5##### Instructor

Sumit Mukherjee##### Course Number

STAT8001R015##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

015/13833##### Enrollment

2 of 5##### Instructor

Marcel Nutz##### Course Number

STAT8001R016##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

016/13835##### Enrollment

3 of 5##### Instructor

Liam Paninski##### Course Number

STAT8001R017##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

017/13837##### Enrollment

1 of 5##### Instructor

Philip Protter##### Course Number

STAT8001R018##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

018/13839##### Enrollment

0 of 5##### Instructor

Daniel Rabinowitz##### Course Number

STAT8001R019##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

019/13841##### Enrollment

1 of 5##### Instructor

Cynthia Rush##### Course Number

STAT8001R020##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

020/13842##### Enrollment

1 of 5##### Instructor

Bodhisattva Sen##### Course Number

STAT8001R021##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

021/13843##### Enrollment

1 of 5##### Instructor

Michael Sobel##### Course Number

STAT8001R022##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

022/13845##### Enrollment

1 of 5##### Instructor

Simon Tavare##### Course Number

STAT8001R023##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

023/13847##### Enrollment

1 of 5##### Instructor

Anne van Delft##### Course Number

STAT8001R024##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

024/13848##### Enrollment

4 of 5##### Instructor

Zhiliang Ying##### Course Number

STAT8001R025##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

025/13849##### Enrollment

2 of 5##### Instructor

Ming Yuan##### Course Number

STAT8001R026##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Section/Call Number

026/13851##### Enrollment

4 of 5##### Instructor

Tian Zheng.

##### Course Number

STAT8101G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 10:10-12:00##### Section/Call Number

001/13667##### Enrollment

8 of 25##### Instructor

Genevera Allen##### Course Number

STAT8301Q001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 14:10-16:00##### Section/Call Number

001/13682##### Enrollment

5 of 25##### Instructor

Philip ProtterGeneral topics in Machine Learning

##### Course Number

STAT8401G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Tu 16:10-17:25Th 16:10-17:25

##### Section/Call Number

001/15036##### Enrollment

29 of 45##### Instructor

David BleiDonald Green

##### Course Number

STAT9201G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Mo 16:10-17:25##### Section/Call Number

001/13683##### Enrollment

39 of 45##### Instructor

Yuqi GuBianca Dumitrascu

##### Course Number

STAT9301G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Fr 11:40-12:55##### Section/Call Number

001/13669##### Enrollment

1 of 25##### Instructor

Ivan Corwin##### Course Number

STAT9302G001##### Format

In-Person##### Points

1 pts#### Spring 2024

##### Times/Location

Th 13:10-14:25##### Section/Call Number

001/13670##### Enrollment

8 of 25##### Instructor

Chenyang ZhongGraeme Baker

##### Course Number

STAT9303G001##### Format

In-Person##### Points

3 pts#### Spring 2024

##### Times/Location

Th 16:10-17:25##### Section/Call Number

001/13671##### Enrollment

7 of 25##### Instructor

Marcel NutzPhilip Protter