Economics and Statistics

https://economics.barnard.edu/

The Economics-Statistics major provides the student with a grounding in economic theory comparable to that provided by the general economics major; and also exposes the student to rigorous and extensive training in Statistics. Students choose between two tracks of the major. The Computational Track consists of coursework in applied statistical methods.  It is recommended for students preparing to apply statistical methods in the social sciences. The Theoretical Track consists of calculus-based probability, and the theory of statistical inference. It also provides some practical training in data analysis.

Available to students of the Class of 2021 and later. 

Department Administrator: Robert O'Connor

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

A major in Economics-Statistics, Computational Track must complete the following 16 courses or their equivalents:

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 Data Mining
One Upper-level Elective in Statistics (STAT UN3106, GU4203, GU4204, GU4205, GU4206, or a Computer Science Elective)

Theoretical Track

A major in Economics-Statistics, Theoretical Track must complete the following 16 courses or their equivalents:

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.

Spring 2018: ECON BC1003
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 1003 001/04582 T Th 10:10am - 11:25am
302 Barnard Hall
Belinda Archibong 3 46/50
ECON 1003 002/06347 T Th 11:40am - 12:55pm
328 Milbank Hall
Sonia Pereira 3 39/50
Fall 2018: ECON BC1003
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 1003 001/04582 M W 1:10pm - 2:25pm
Room TBA
Sharon Harrison 3 18/25
ECON 1003 002/03020 T Th 10:10am - 11:25am
Room TBA
Homa Zarghamee 3 22/25
ECON 1003 003/02004 T Th 11:40am - 12:55pm
Room TBA
Sonia Pereira 3 27/25

MATH UN1102 Calculus II. 3 points.

Prerequisites: MATH UN1101 or the equivalent.

Methods of integration, applications of the integral, Taylor's theorem, infinite series. (SC) 

Spring 2018: MATH UN1102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1102 001/18873 M W 11:40am - 12:55pm
407 Mathematics Building
Elena Giorgi 3 27/35
MATH 1102 002/19504 M W 6:10pm - 7:25pm
203 Mathematics Building
Vivek Pal 3 76/100
MATH 1102 003/21419 T Th 2:40pm - 3:55pm
407 Mathematics Building
Ivan Danilenko 3 26/35
MATH 1102 004/62347 T Th 1:10pm - 2:25pm
503 Hamilton Hall
Xuan Wu 3 13/35
MATH 1102 005/88001 T Th 11:40am - 12:55pm
407 Mathematics Building
Pak Hin Lee 3 6/35
Fall 2018: MATH UN1102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1102 001/21348 M W 10:10am - 11:25am
209 Havemeyer Hall
Evgeni Dimitrov 3 12/100
MATH 1102 002/68227 M W 2:40pm - 3:55pm
203 Mathematics Building
Sylvain Carpentier 3 10/100
MATH 1102 003/73735 M W 4:10pm - 5:25pm
407 Mathematics Building
Donghan Kim 3 9/30
MATH 1102 004/77440 T Th 10:10am - 11:25am
203 Mathematics Building
Peter Woit 3 4/100
MATH 1102 005/75792 T Th 6:10pm - 7:25pm
337 Seeley W. Mudd Building
Elliott Stein 3 28/35
MATH 1102 006/86786 M W 8:40am - 9:55am
312 Mathematics Building
Aliakbar Daemi 3 2/100

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) 

Spring 2018: MATH UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1201 001/05518 M W 8:40am - 9:55am
504 Diana Center
Ilya Kofman 3 38/100
MATH 1201 002/76403 M W 10:10am - 11:25am
312 Mathematics Building
Igor Krichever 3 93/116
MATH 1201 003/67090 M W 11:40am - 12:55pm
203 Mathematics Building
Shrenik Shah 3 84/110
MATH 1201 004/29982 M W 1:10pm - 2:25pm
203 Mathematics Building
Shrenik Shah 3 91/110
MATH 1201 005/14673 T Th 6:10pm - 7:25pm
407 Mathematics Building
Elliott Stein 3 29/35
Fall 2018: MATH UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 1201 001/06129 M W 10:10am - 11:25am
Room TBA
Daniela De Silva 3 100/100
MATH 1201 002/15181 M W 4:10pm - 5:25pm
312 Mathematics Building
Akram Alishahi 3 44/100
MATH 1201 003/70393 M W 5:40pm - 6:55pm
312 Mathematics Building
Akram Alishahi 3 14/100
MATH 1201 004/28840 T Th 8:40am - 9:55am
312 Mathematics Building
Teng Fei 3 13/100
MATH 1201 005/29694 T Th 10:10am - 11:25am
312 Mathematics Building
Teng Fei 3 16/110
MATH 1201 006/26829 T Th 1:10pm - 2:25pm
203 Mathematics Building
Michael Harris 3 36/100
MATH 1201 007/66587 T Th 2:40pm - 3:55pm
312 Mathematics Building
Michael Harris 3 16/100
MATH 1201 008/73001 T Th 6:10pm - 7:25pm
207 Mathematics Building
Guillaume Remy 3 9/100

MATH UN2010 Linear Algebra. 3 points.

Prerequisites: MATH UN1201 or the equivalent.

Matrices, vector spaces, linear transformations, eigenvalues and eigenvectors, canonical forms, applications. (SC)

Spring 2018: MATH UN2010
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 2010 001/14202 M W 8:40am - 9:55am
312 Mathematics Building
Gus Schrader 3 77/100
MATH 2010 002/20875 M W 10:10am - 11:25am
203 Mathematics Building
Guillaume Barraquand 3 81/100
MATH 2010 003/27803 M W 1:10pm - 2:25pm
207 Mathematics Building
Guillaume Barraquand 3 83/100
MATH 2010 004/20676 T Th 8:40am - 9:55am
413 International Affairs Bldg
Teng Fei 3 28/70
MATH 2010 005/71356 T Th 10:10am - 11:25am
413 International Affairs Bldg
Teng Fei 3 51/70
Fall 2018: MATH UN2010
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MATH 2010 001/17348 M W 11:40am - 12:55pm
203 Mathematics Building
Gus Schrader 3 100/100
MATH 2010 002/12215 M W 1:10pm - 2:25pm
203 Mathematics Building
Gus Schrader 3 100/100
MATH 2010 003/03818 T Th 8:40am - 9:55am
Room TBA
David Bayer 3 37/100
MATH 2010 004/02940 T Th 10:10am - 11:25am
Room TBA
David Bayer 3 78/100
MATH 2010 005/70756 T Th 6:10pm - 7:25pm
312 Mathematics Building
Michael Thaddeus 3 55/100
MATH 2010 006/10282 M W 4:10pm - 5:25pm
203 Mathematics Building
3 3/100

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.

Spring 2018: ECON BC3033
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3033 001/06157 M W 1:10pm - 2:25pm
Ll104 Diana Center
Luis Silva-Yanez 4 38/50
Fall 2018: ECON BC3033
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3033 001/06157 M W 8:40am - 9:55am
Room TBA
0. FACULTY 4 46/50

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.

Spring 2018: ECON BC3035
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3035 001/04588 T Th 6:10pm - 7:25pm
323 Milbank Hall
Lalith Munasinghe 4 31/50
Fall 2018: ECON BC3035
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3035 001/04588 T Th 11:40am - 12:55pm
Room TBA
John Park 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.

Spring 2018: ECON BC3041
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3041 001/07742 M W 4:10pm - 5:25pm
323 Milbank Hall
Sonia Pereira 3 47/48
Fall 2018: ECON BC3041
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3041 001/07742 M W 4:10pm - 5:25pm
Room TBA
Sonia Pereira 3 76/75

ECON BC3063 Senior Seminar. 4 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 instructor’s choice. See department for current topics and for senior requirement preference forms.

Spring 2018: ECON BC3063
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3063 001/02840 Th 11:00am - 12:50pm
406 Barnard Hall
Homa Zarghamee 4 15
ECON 3063 002/05970 T 4:10pm - 6:00pm
406 Barnard Hall
Lalith Munasinghe 4 13
ECON 3063 003/02843 M 2:10pm - 4:00pm
903 Altschul Hall
Anja Tolonen 4 15
Fall 2018: ECON BC3063
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3063 001/03378 T 4:10pm - 6:00pm
Room TBA
Rajiv Sethi 4 11/16
ECON 3063 002/06514 M 10:10am - 12:00pm
Room TBA
0. FACULTY 4 6

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.

Spring 2018: STAT UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 1201 001/63271 T Th 10:10am - 11:25am
601 Fairchild Life Sciences Bldg
David Rios 3 46/54
STAT 1201 002/70918 M W 8:40am - 9:55am
602 Hamilton Hall
Joyce Robbins 3 78/86
STAT 1201 003/29709 T Th 8:40am - 9:55am
207 Mathematics Building
Joyce Robbins 3 83/86
STAT 1201 004/11251 T Th 6:10pm - 7:25pm
312 Mathematics Building
Sheela Kolluri 3 53/86
Fall 2018: STAT UN1201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 1201 001/28764 M W 8:40am - 9:55am
Room TBA
Joyce Robbins 3 86/86
STAT 1201 002/75041 T Th 8:40am - 9:55am
Room TBA
Joyce Robbins 3 86/86
STAT 1201 003/12543 M W 11:40am - 12:55pm
Room TBA
Banu Baydil 3 86/86
STAT 1201 004/10709 T Th 6:10pm - 7:25pm
Room TBA
Banu Baydil 3 51/86

ECON BC3018 Econometrics. 4 points.

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.

Spring 2018: ECON BC3018
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3018 001/04759 M 10:00am - 10:50am
222 Milbank Hall
Homa Zarghamee 4 35/45
ECON 3018 001/04759 M 9:00am - 9:50am
222 Milbank Hall
Homa Zarghamee 4 35/45
Fall 2018: ECON BC3018
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ECON 3018 001/01690 T Th 1:10pm - 2:25pm
Room TBA
Daniel Hamermesh 4 40/50

STAT UN2102 Applied Statistical Computing. 3 points.

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 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.

Spring 2018: STAT UN2102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 2102 001/69000 T Th 4:10pm - 5:25pm
312 Mathematics Building
Gabriel Young 3 68/86

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 2018: STAT UN2104
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 2104 001/26887 M W 2:40pm - 3:55pm
214 Pupin Laboratories
James Landwehr 3 33/56

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 2018: STAT UN3105
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 3105 001/15398 T Th 11:40am - 12:55pm
903 School Of Social Work
David Rios 3 18/50

STAT UN3106 Applied Data Mining. 3 points.

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

This course will be taught as a machine learning class. 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; students without programming experience in R might find STAT UN2102 helpful.

Spring 2018: STAT UN3106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 3106 001/64011 T Th 2:40pm - 3:55pm
627 Seeley W. Mudd Building
Peter Orbanz 3 41/50

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.

Spring 2018: STAT GU4203
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4203 001/25545 T Th 10:10am - 11:25am
310 Fayerweather
Daniel Rabinowitz 3 89/93
Fall 2018: STAT GU4203
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4203 001/24276 M W 10:10am - 11:25am
903 School Of Social Work
Shaw-Hwa Lo 3 33/60
STAT 4203 003/74226 M W 6:10pm - 7:25pm
Room TBA
Larry Wright 3 30/55

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.

Spring 2018: STAT GU4204
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4204 001/65537 M W 1:10pm - 2:25pm
413 Kent Hall
Gabriel Young 3 60/71
STAT 4204 002/16672 Sa 1:10pm - 3:55pm
207 Mathematics Building
Dan Wang 3 16/50
Fall 2018: STAT GU4204
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4204 003/24240 T Th 6:10pm - 7:25pm
Room TBA
Thibault Vatter 3 54/55

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.

Spring 2018: STAT GU4205
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4205 001/24588 Sa 10:10am - 12:40pm
203 Mathematics Building
Jingchen Liu 3 32/60
Fall 2018: STAT GU4205
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4205 001/25430 M W 2:40pm - 3:55pm
501 Northwest Corner
Yang Feng 3 25/35
STAT 4205 002/76197 F 10:10am - 12:40pm
501 Northwest Corner
Jingchen Liu 3 26/35
STAT 4205 003/63988 M W 6:10pm - 7:25pm
501 Northwest Corner
Ronald Neath 3 35/35
STAT 4205 004/16318 M W 1:10pm - 2:25pm
Room TBA
Gabriel Young 3 27/65

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.

Spring 2018: STAT GU4206
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4206 001/26627 F 10:10am - 12:40pm
203 Mathematics Building
Gabriel Young 3 76/80
Fall 2018: STAT GU4206
Course Number Section/Call Number Times/Location Instructor Points Enrollment
STAT 4206 001/27544 F 8:40am - 11:25am
903 School Of Social Work
Gabriel Young 3 26/46

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.

Spring 2018: COMS W1004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 1004 001/12368 T Th 2:40pm - 3:55pm
309 Havemeyer Hall
Adam Cannon 3 224/300
COMS 1004 002/64704 T Th 4:10pm - 5:25pm
309 Havemeyer Hall
Adam Cannon 3 174/300
Fall 2018: COMS W1004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 1004 001/69061 T Th 4:10pm - 5:25pm
Room TBA
Adam Cannon 3 241/275

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.

Spring 2018: COMS W1005
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 1005 001/76034 M W 7:10pm - 8:25pm
501 Schermerhorn Hall
Timothy Paine 3 20/120

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. 

Fall 2018: COMS W1007
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 1007 001/72894 T Th 1:10pm - 2:25pm
Room TBA
John Kender 3 15/70