Chair: Rajiv Sethi (Ann Whitney Olin Professor)
Professors: Elizabeth Ananat, André Burgstaller, Alan Dye, Daniel Hamermesh (Distinguished Scholar), Sharon Harrison, Shaw-Hwa Lo (Statistics), Lalith Munasinghe, David Weiman (Alena Wels Hirschorn '58 Professor)
Associate Professors: Yang Feng (Statistics), Jingchen Liu (Statistics), Randall Reback, Ashley Timmer (Adjunct)
Assistant Professors: Belinda Archibong, Biwei Chen (Term), Martina Jasova, Elizabeth Kopko (Adjunct), Peter Orbanz (Statistics), Sonia Pereira (Term), Anja Tolonen, Homa Zarghamee
Associates: John Park

Lecturers in Statistics: Banu Baydil, Ronald Neath, David Rios, Joyce Robbins, Gabriel Young

Computational Track

The Economics-Statistics, Computational Track requires a minimum of 16 courses (52 minimum credits).

10 courses in Economics, Mathematics

ECON BC1003Introduction to Economic Reasoning
MATH UN1102CALCULUS II
MATH UN1201Calculus III
MATH UN2010LINEAR ALGEBRA
ECON BC3033Intermediate Macroeconomic Theory
ECON BC3035Intermediate Microeconomic Theory
ECON BC3041Theoretical Foundations of Political Economy
Two Upper-level Electives in Economics
ECON BC3063SENIOR SEMINAR

6 courses in Statistics

STAT UN1201Calculus-Based Introduction to Statistics
ECON BC3018ECONOMETRICS
STAT UN2102Applied Statistical Computing
STAT UN2104Applied Categorical Data Analysis
One of the following two courses:
Applied Statistical Methods
APPLIED MACHINE LEARNING
One Upper-level Elective in Statistics (STAT UN3106, GU4203, GU4204, GU4205, GU4206, or a Computer Science Elective)

Theoretical Track

The Economics-Statistics, Theoretical Track requires a minimum of 16 courses (52 minimum credits).

10 courses in Economics, Mathematics which are the same as in the Computational Track above, plus

6 courses in Statistics which differs from the Computational Track somewhat:

STAT UN1201Calculus-Based Introduction to Statistics
ECON BC3018ECONOMETRICS
STAT GU4203PROBABILITY THEORY
STAT GU4204Statistical Inference
STAT GU4205Linear Regression Models
One Elective in Statistics at the 3000+ level (or a Computer Science Elective such as COMS W1004, W1005, W1007, or STAT UN2102)

Economics, Mathematics

ECON BC1003 Introduction to Economic Reasoning. 3 points.

BC: Fulfillment of General Education Requirement: Social Analysis (SOC I)., BC: Fulfillment of General Education Requirement: Social Analysis (SOC II).

Covers basic elements of microeconomic and marcoeconomic reasoning at an introductory level. Topics include Individual Constraints and Preferences, Production by Firms, Market Transactions, Competition, The Distribution of Income, Technological Progress and Growth, Unemployment and Inflation, the Role of Government in the Economy.  Note: Students cannot get credit for ECON BC1003 if they have taken the Columbia introductory course ECON W1105 Principles of Economics.

Fall 2022: ECON BC1003
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 1003 001/00380 T Th 10:10am - 11:25am
Ll103 Diana Center
Rajiv Sethi 3 59/60
ECON 1003 002/00381 T Th 4:10pm - 5:25pm
405 Milbank Hall
Camilo Rubbini 3 61/70
Spring 2023: ECON BC1003
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 1003 001/00294 M W 8:40am - 9:55am
504 Diana Center
Camilo Rubbini 3 60/60
ECON 1003 002/00295 T Th 10:10am - 11:25am
Ll103 Diana Center
Rajiv Sethi 3 60/60

MATH UN1102 CALCULUS II. 3.00 points.

Prerequisites: MATH UN1101 or the equivalent.
Prerequisites: MATH UN1101 or the equivalent. Methods of integration, applications of the integral, Taylors theorem, infinite series. (SC)

Fall 2022: MATH UN1102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1102 001/12761 M W 1:10pm - 2:25pm
203 Mathematics Building
Rostislav Akhmechet 3.00 69/110
MATH 1102 002/12763 M W 2:40pm - 3:55pm
203 Mathematics Building
Rostislav Akhmechet 3.00 68/110
MATH 1102 003/12765 M W 4:10pm - 5:25pm
407 Mathematics Building
Hindy Drillick 3.00 34/35
MATH 1102 004/12767 T Th 10:10am - 11:25am
312 Mathematics Building
Andres Fernandez Herrero 3.00 37/110
MATH 1102 005/12768 T Th 11:40am - 12:55pm
203 Mathematics Building
Andres Fernandez Herrero 3.00 65/110
MATH 1102 006/12771 T Th 6:10pm - 7:25pm
407 Mathematics Building
Haodong Yao 3.00 16/30
Spring 2023: MATH UN1102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1102 001/00021 T Th 2:40pm - 3:55pm
304 Barnard Hall
Lindsay Piechnik 3.00 100/100
MATH 1102 002/12024 M W 1:10pm - 2:25pm
407 Mathematics Building
Ryuichi Haney 3.00 17/30
MATH 1102 003/12025 M W 2:40pm - 3:55pm
417 Mathematics Building
Richard Hamilton 3.00 37/64
MATH 1102 004/12026 M W 6:10pm - 7:25pm
417 Mathematics Building
Elliott Stein 3.00 42/64
MATH 1102 005/12027 T Th 10:10am - 11:25am
203 Mathematics Building
Allen Yuan 3.00 38/100
MATH 1102 006/12028 T Th 11:40am - 12:55pm
203 Mathematics Building
Andres Fernandez Herrero 3.00 21/100
MATH 1102 007/12029 T Th 6:10pm - 7:25pm
417 Mathematics Building
Patrick Lei 3.00 9/30

MATH UN1201 Calculus III. 3 points.

Prerequisites: MATH UN1101 or the equivalent

Vectors in dimensions 2 and 3, complex numbers and the complex exponential function with applications to differential equations, Cramer's rule, vector-valued functions of one variable, scalar-valued functions of several variables, partial derivatives, gradients, surfaces, optimization, the method of Lagrange multipliers. (SC) 

Fall 2022: MATH UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1201 001/12774 M W 10:10am - 11:25am
207 Mathematics Building
Tudor Padurariu 3 106/110
MATH 1201 002/12776 M W 11:40am - 12:55pm
207 Mathematics Building
Tudor Padurariu 3 106/110
MATH 1201 003/12778 M W 1:10pm - 2:25pm
312 Mathematics Building
Sam Collingbourne 3 18/110
MATH 1201 004/12779 M W 2:40pm - 3:55pm
312 Mathematics Building
Sam Collingbourne 3 34/110
MATH 1201 005/12781 T Th 11:40am - 12:55pm
142 Uris Hall
Ilya Kofman 3 28/100
MATH 1201 006/12783 T Th 1:10pm - 2:25pm
203 Mathematics Building
Gyujin Oh 3 58/100
MATH 1201 007/12784 T Th 2:40pm - 3:55pm
207 Mathematics Building
Gyujin Oh 3 63/100
MATH 1201 008/12785 T Th 4:10pm - 5:25pm
312 Mathematics Building
George Dragomir 3 109/116
Spring 2023: MATH UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1201 001/12030 M W 10:10am - 11:25am
207 Mathematics Building
Xi Shen 3 57/100
MATH 1201 002/12031 M W 11:40am - 12:55pm
312 Mathematics Building
Chen-Chih Lai 3 61/100
MATH 1201 003/12032 M W 1:10pm - 2:25pm
203 Mathematics Building
Xi Shen 3 100/100
MATH 1201 004/12033 T Th 1:10pm - 2:25pm
207 Mathematics Building
Inbar Klang 3 100/100
MATH 1201 005/12034 T Th 2:40pm - 3:55pm
207 Mathematics Building
Inbar Klang 3 100/100
MATH 1201 006/19536 M W 6:10pm - 7:25pm
203 Mathematics Building
Tomasz Owsiak 3 9/100

MATH UN2010 LINEAR ALGEBRA. 3.00 points.

Prerequisites: MATH UN1201 or the equivalent.
Matrices, vector spaces, linear transformations, eigenvalues and eigenvectors, canonical forms, applications. (SC)

Fall 2022: MATH UN2010
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 2010 001/00061 T Th 8:40am - 9:55am
328 Milbank Hall
David Bayer 3.00 41/56
MATH 2010 002/00062 T Th 10:10am - 11:25am
328 Milbank Hall
David Bayer 3.00 55/56
MATH 2010 003/12793 M W 10:10am - 11:25am
312 Mathematics Building
Marco Castronovo 3.00 47/100
MATH 2010 004/12794 M W 11:40am - 12:55pm
312 Mathematics Building
Marco Castronovo 3.00 63/100
MATH 2010 005/12796 T Th 4:10pm - 5:25pm
417 Mathematics Building
Elliott Stein 3.00 52/64
Spring 2023: MATH UN2010
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 2010 001/12504 M W 10:10am - 11:25am
203 Mathematics Building
Amadou Bah 3.00 80/100
MATH 2010 002/12541 M W 11:40am - 12:55pm
203 Mathematics Building
Amadou Bah 3.00 99/100
MATH 2010 003/12543 T Th 1:10pm - 2:25pm
312 Mathematics Building
Jie Jun Morris Ang 3.00 100/100
MATH 2010 004/12546 T Th 4:10pm - 5:25pm
203 Mathematics Building
Konstantin Aleshkin 3.00 93/100
MATH 2010 005/12563 T Th 6:10pm - 7:25pm
203 Mathematics Building
Konstantin Aleshkin 3.00 40/100
MATH 2010 006/15466 M W 6:10pm - 7:25pm
Room TBA
Tomasz Owsiak 3.00 17/100

ECON BC3033 Intermediate Macroeconomic Theory. 4 points.

Prerequisites: An introductory course in economics and a functioning knowledge of high school algebra and analytical geometry or permission of the instructor.

Systematic exposition of current macroeconomic theories of unemployment, inflation, and international financial adjustments.

Fall 2022: ECON BC3033
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3033 001/00388 T Th 6:10pm - 7:25pm
304 Barnard Hall
Elham Saeidinezhad 4 30/50
Spring 2023: ECON BC3033
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3033 001/00375 T Th 11:40am - 12:55pm
323 Milbank Hall
Miguel Casares 4 60/60

ECON BC3035 Intermediate Microeconomic Theory. 4 points.

Prerequisites: An introductory course in microeconomics or a combined macro/micro principles course (ECON BC1003 or ECON W1105, or the equivalent) and one semester of calculus or ECON BC1007, or permission of the instructor.

Preferences and demand; production, cost, and supply; behavior of markets in partial equilibrium; resource allocation in general equilibrium; pricing of goods and services under alternative market structures; implications of individual decision-making for labor supply; income distribution, welfare, and public policy. Emphasis on problem solving.

Fall 2022: ECON BC3035
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3035 001/00400 T Th 4:10pm - 5:25pm
Ll103 Diana Center
Lalith Munasinghe 4 37/50
Spring 2023: ECON BC3035
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3035 001/00407 T Th 1:10pm - 2:25pm
Ll104 Diana Center
Lalith Munasinghe 4 50/50

ECON BC3041 Theoretical Foundations of Political Economy. 3 points.

BC: Fulfillment of General Education Requirement: Reason and Value (REA)., BC: Fulfillment of General Education Requirement: Ethics and Values.

Prerequisites: An introductory course in economics or permission of the instructor.

Intellectual origins of the main schools of thought in political economy. Study of the founding texts in classical political economy, Marxian economics, neoclassicism, and Keynesianism.

Fall 2022: ECON BC3041
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3041 002/00390 M W 2:40pm - 3:55pm
328 Milbank Hall
David Weiman 3 42/45
ECON 3041 003/00391 M W 10:10am - 11:25am
302 Barnard Hall
David Weiman 3 43/45
Spring 2023: ECON BC3041
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3041 001/00409 T Th 2:40pm - 3:55pm
323 Milbank Hall
Belinda Archibong 3 44/40

ECON BC3063 SENIOR SEMINAR. 4.00 points.

Prerequisites: Permission of the instructor and the completion of all courses (except for the senior requirement) required for the economics track, political economy track, or economics and mathematics majors. Exceptions to these prerequisites may be granted by the chair of the department only. Seminar sections are limited to 15 students. A topic in economic theory or policy of the instructors choice. See department for current topics and for senior requirement preference forms

Fall 2022: ECON BC3063
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3063 001/00396 T 10:10am - 12:00pm
407 Barnard Hall
Morgan Williams 4.00 16/16
ECON 3063 002/00397 T 4:10pm - 6:00pm
407 Barnard Hall
Rajiv Sethi 4.00 16/16
ECON 3063 003/00630 W 11:00am - 12:50pm
404 Barnard Hall
Elham Saeidinezhad 4.00 16/16
Spring 2023: ECON BC3063
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3063 001/00451 T 2:10pm - 4:00pm
805 Altschul Hall
Anja Tolonen 4.00 12/16
ECON 3063 002/00452 W 2:10pm - 4:00pm
502 Diana Center
Homa Zarghamee 4.00 11/16
ECON 3063 003/00453 Th 4:10pm - 6:00pm
227 Milbank Hall
Lalith Munasinghe 4.00 17/16
ECON 3063 004/00454 M 2:10pm - 4:00pm
501 Diana Center
Mulu Gebreyohannes 4.00 10/16

Statistics, Computer Science

STAT UN1201 Calculus-Based Introduction to Statistics. 3 points.

CC/GS: Partial Fulfillment of Science Requirement, BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA).

Prerequisites: one semester of calculus.

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.

Fall 2022: STAT UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 1201 001/13781 T Th 10:10am - 11:25am
602 Hamilton Hall
Joyce Robbins 3 84/86
STAT 1201 002/13782 M W 6:10pm - 7:25pm
517 Hamilton Hall
Johannes Wiesel 3 67/86
STAT 1201 003/13783 M W 10:10am - 11:25am
517 Hamilton Hall
Dobrin Marchev 3 74/86
STAT 1201 004/13784 T Th 2:40pm - 3:55pm
517 Hamilton Hall
Chenyang Zhong 3 64/86
Spring 2023: STAT UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 1201 001/14233 M W 10:10am - 11:25am
602 Hamilton Hall
Philip Protter 3 86/86
STAT 1201 002/14234 M W 8:40am - 9:55am
602 Hamilton Hall
Banu Baydil 3 69/86
STAT 1201 003/14235 T Th 10:10am - 11:25am
602 Hamilton Hall
Joyce Robbins 3 86/86
STAT 1201 004/14236 M W 6:10pm - 7:25pm
702 Hamilton Hall
Alex Pijyan 3 86/86

ECON BC3018 ECONOMETRICS. 4.00 points.

Prerequisites: ECON BC3033 or ECON BC3035, and ECON BC2411 or STAT W1111 or STAT W1211, or permission of the instructor.
Prerequisites: ECON BC3033 or ECON BC3035, and ECON BC2411 or STAT W1111 or STAT W1211, or permission of the instructor. Specification, estimation and evaluation of economic relationships using economic theory, data, and statistical inference; testable implications of economic theories; econometric analysis of topics such as consumption, investment, wages and unemployment, and financial markets

Fall 2022: ECON BC3018
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3018 001/00386 T Th 1:10pm - 2:25pm
Ll103 Diana Center
Morgan Williams 4.00 36/60
Spring 2023: ECON BC3018
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3018 001/00391 M W 1:10pm - 2:25pm
Ll002 Milstein Center
Camilo Rubbini 4.00 60/60

STAT UN2102 Applied Statistical Computing. 3.00 points.

Corequisites: An introductory course in statistic (STAT UN1101 is recommended).
Corequisites: An introductory course in statistic (STAT UN1101 is recommended). 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 conditionals, modular programming, and data visualization. Students will also learn the fundamental concepts in computational complexity, and will practice writing reports based on their data analyses

Fall 2022: STAT UN2102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 2102 001/13786 T Th 4:10pm - 5:25pm
614 Schermerhorn Hall
Anthony Donoghue 3.00 66/120
Spring 2023: STAT UN2102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 2102 001/14237 T Th 4:10pm - 5:25pm
402 Chandler
Alex Pijyan 3.00 77/125

STAT UN2104 Applied Categorical Data Analysis. 3 points.

Prerequisites: STAT UN2103 is strongly recommended. Students without programming experience in R might find STAT UN2102 very helpful.

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.

Spring 2023: STAT UN2104
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 2104 001/14239 M W 8:40am - 9:55am
413 Kent Hall
Ronald Neath 3 51/60

STAT UN3105 Applied Statistical Methods. 3 points.

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.

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.

Fall 2022: STAT UN3105
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 3105 001/13788 T Th 11:40am - 12:55pm
702 Hamilton Hall
David Rios 3 37/86

STAT UN3106 APPLIED MACHINE LEARNING. 3.00 points.

Prerequisites: STAT UN2103. Students without programming experience in R might find STAT UN2102 very helpful.
Prerequisites: STAT UN2103. Students without programming experience in R might find STAT UN2102 very helpful. This course is a machine learning class from an application perspective. We will cover topics including data-based prediction, classification, specific classification methods (such as logistic regression and random forests), and basics of neural networks. Programming in homeworks will require R

Spring 2023: STAT UN3106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 3106 001/14240 T Th 2:40pm - 3:55pm
703 Hamilton Hall
Gabriel Young 3.00 45/45

STAT GU4203 PROBABILITY THEORY. 3 points.

Prerequisites: At least one semester, and preferably two, of calculus. An introductory course (STAT UN1201, preferably) is strongly recommended.

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.

Fall 2022: STAT GU4203
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4203 001/13792 M W 10:10am - 11:25am
602 Hamilton Hall
Carsten Chong 3 48/86
STAT 4203 002/13793 M W 6:10pm - 7:25pm
301 Pupin Laboratories
Cristian Pasarica 3 37/86
STAT 4203 003/13794 M W 6:10pm - 7:25pm
301 Pupin Laboratories
Cristian Pasarica 3 18/35
Spring 2023: STAT GU4203
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4203 001/14244 M W 6:10pm - 7:25pm
614 Schermerhorn Hall
David Rios 3 61/61

STAT GU4204 Statistical Inference. 3 points.

CC/GS: Partial Fulfillment of Science Requirement, BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA).

Prerequisites: STAT GU4203. At least one semester of calculus is required; two or three semesters are strongly recommended.

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.

Fall 2022: STAT GU4204
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4204 001/13795 T Th 6:10pm - 7:25pm
501 Schermerhorn Hall
Hammou El Barmi 3 31/86
STAT 4204 002/13796 T Th 6:10pm - 7:25pm
501 Schermerhorn Hall
Hammou El Barmi 3 5/15
Spring 2023: STAT GU4204
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4204 001/14246 T Th 2:40pm - 3:55pm
702 Hamilton Hall
Johannes Wiesel 3 48/86
STAT 4204 002/14247 T Th 6:10pm - 7:25pm
142 Uris Hall
Cristian Pasarica 3 26/45
STAT 4204 003/14248 T Th 6:10pm - 7:25pm
142 Uris Hall
Cristian Pasarica 3 19/24

STAT GU4205 Linear Regression Models. 3 points.

CC/GS: Partial Fulfillment of Science Requirement

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.

Fall 2022: STAT GU4205
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4205 001/13797 M W 8:40am - 9:55am
602 Hamilton Hall
Ronald Neath 3 25/86
STAT 4205 002/13798 T Th 2:40pm - 3:55pm
301 Pupin Laboratories
Philip Protter 3 10/15
STAT 4205 003/13799 M W 1:10pm - 2:25pm
428 Pupin Laboratories
Banu Baydil 3 11/11
STAT 4205 004/13800 T Th 6:10pm - 7:25pm
428 Pupin Laboratories
Alex Pijyan 3 4/25
STAT 4205 005/13801 M W 8:40am - 9:55am
312 Mathematics Building
Yuqi Gu 3 8/25
Spring 2023: STAT GU4205
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4205 001/14249 M W 7:40pm - 8:55pm
428 Pupin Laboratories
Jeonghoe Lee 3 25/35

STAT GU4206 Statistical Computing and Introduction to Data Science. 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.

Fall 2022: STAT GU4206
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4206 001/14194 F 10:10am - 12:40pm
301 Pupin Laboratories
Wayne Lee 3 6/10
Spring 2023: STAT GU4206
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4206 001/14250 M W 6:10pm - 7:25pm
301 Pupin Laboratories
Yongchan Kwon 3 18/40

COMS W1004 Introduction to Computer Science and Programming in Java. 3 points.

Lect: 3.

A general introduction to computer science for science and engineering students interested in majoring in computer science or engineering. Covers fundamental concepts of computer science, algorithmic problem-solving capabilities, and introductory Java programming skills. Assumes no prior programming background. Columbia University students may receive credit for only one of the following two courses: 1004 or 1005.

Fall 2022: COMS W1004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 1004 001/10985 M W 2:40pm - 3:55pm
417 International Affairs Bldg
Paul Blaer 3 392/398
COMS 1004 002/10986 M W 5:40pm - 6:55pm
501 Northwest Corner
Paul Blaer 3 171/164
COMS 1004 H01/20439 M W 2:40pm - 3:55pm
Online Only
Paul Blaer 3 4/40
COMS 1004 H02/20440 M W 5:40pm - 6:55pm
Online Only
Paul Blaer 3 3/40
Spring 2023: COMS W1004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 1004 001/12396 T Th 11:40am - 12:55pm
417 International Affairs Bldg
Adam Cannon 3 285/350
COMS 1004 002/12398 T Th 1:10pm - 2:25pm
417 International Affairs Bldg
Adam Cannon 3 186/350

COMS W1005 Introduction to Computer Science and Programming in MATLAB. 3 points.

CC/GS: Partial Fulfillment of Science Requirement

A general introduction to computer science concepts, algorithmic problem-solving capabilities, and programming skills in MATLAB. Assumes no prior programming background. Columbia University students may receive credit for only one of the following two courses: W1004 or W1005.

COMS W1007 Honors Introduction to Computer Science. 3 points.

Lect: 3.

Prerequisites: AP Computer Science with a grade of 4 or 5 or similar experience.

An honors-level introduction to computer science, intended primarily for students considering a major in computer science. Computer science as a science of abstraction. Creating models for reasoning about and solving problems. The basic elements of computers and computer programs. Implementing abstractions using data structures and algorithms. Taught in Java.