Elective Courses in Advanced Quantitative Methods

Elective Courses in Advanced Quantitative Methods

2018-2024

(Note: This list needs to be updated annually.)

BUSN 36906     Stochastic Processes

BUSN 36912     Stochastic Optimization

BUSN 37904     Advanced Quantitative Marketing

BUSN 37906     Applied Bayesian Econometrics

BUSN 37907     Behavioral Science Research Methods in Marketing

BUSN 40206     Healthcare Business Analytics

BUSN 41917     Causal Machine Learning

BUSN 41918     Data, Learning, and Algorithms

BUSN 41100     Applied Regression Analysis

BUSN 41201     Big Data

BUSN 41202     Analysis of Financial Time Series

BUSN 41203     Financial Econometrics

BUSN 41204     Machine Learning

BUSN 41207     Causal Inference for Business Applications

BUSN 41210     Financial Analytics [open only to Booth Students]

BUSN 41305     Statistical Insight into Entrepreneurial Quantitative Consulting with Wide Business Applications

BUSN 41600/ECPN 51400    Econometrics and Statistics Colloquium

BUSN 41903     Applied Econometrics

BUSN 41910/STAT 33500    Time Series Analysis for Forecasting and Model Building

BUSN 41912     Applied Multivariate Analysis

BUSN 41913     Bayesian Inference

BUSN 41914     Multivariate Time Series Analysis

BUSN 41916     Bayes, AI and Deep Learning

BUSN 41918     Data, Learning, and Algorithms

 

 

CHDV 30102/MACS 50100/PBHS 43201/SOCI 30315/STAT 31900         Introduction to Causal Inference

CHDV 32411/CCTS 32411/PBPL 29411/PSYC 32411/SOCI 30318/STAT 33211             Mediation, Moderation, and Spillover Effects

 

 

ECMA 33220     Introduction to Advanced Macroeconomic Analysis

ECMA 33221     Intro to Advanced Macroeconomic Analysis II

ECON 31000     Empirical Analysis I

ECON 31100     Empirical Analysis II: Stochastic Processes and Time-Series Econometrics

ECON 31200     Empirical Analysis III

ECON 31703     Topics in Econometrics

ECON 31715     Econometrics with Partial Identification

ECON 31720     Applied Microeconometrics

ECON 31740/PPHA 48403    Optimization-Conscious Econometrics

ECON 31750     Topics on the Analysis of Randomized Experiments

ECON 31760     Topics in Modern Econometrics

ECON 31761     Frontiers of Causal Inference [intended for Econ PhD students]

ECON 31800     Advanced Econometrics

ECON 35003     Human Capital, Markets, and the Family

ECON 33550     Spatial Economics  

ECON 35550/PPHA 35561/ECMA 35550    The Practicalities of Running Randomized Control Trials

 

MACS 33002     Introduction to Machine Learning

MACS 40200     Structural Estimation

MACS 40101/SOCI 40248     Social Network Analysis

MACS 40800     Unsupervised Machine Learning

MACS 60000/SOCI 40133/CHDV 30510     Computational Content Analysis

 

MDEC/ISTP 42000 Topics in Data Analysis in Biomedical Research: Big Data

 

PBHS 30910      Epidemiology and Population Health

PBHS 31001/STAT 35700     Epidemiologic Methods

PBHS 33300/STAT 36900     Applied Longitudinal Data Analysis

PBHS 33400/CHDV 32401    Multilevel Modeling

PBHS 33500/STAT 35800/CHDV 32702      Statistical Applications

PBHS 34500      Machine Learning

PBHS 40500      Advanced Epidemiologic Methods

PBHS 43010/STAT 35920     Applied Bayesian Modeling and Inference

 

PLSC 30600       Causal Inference

PLSC 40502       Data Analysis with Statistical Models

PLSC 40601       Advanced Topics in Causal Inference

PLSC 43100       Maximum Likelihood

PLSC 43200       Maximum Likelihood II

PLSC 57200       Network Analysis and Social Structure

 

PPHA 31300      Regression Analysis for Public Policy II

PPHA 34600      Program Evaluation

PPHA 41103      Political Economy III

PPHA 41300      Cost Benefit Analysis

PPHA 41400      Applied Regression Analysis

PPHA 41420      Multilevel Regression Modeling for Public Policy

PPHA 41600      Survey Research Methodology

PPHA 41800/PSYC 47500     Survey Questionnaire Design

PPHA 42000      Applied Econometrics I

PPHA 42100      Applied Econometrics II

PPHA 42200      Applied Econometrics III

PPHA 42600      Survey Research Methods and Analysis

 

PSYC 31300      Experimental Design

PSYC 34410      Computational Approaches for Cognitive Neuroscience

PSYC 36210/CPNS 31000     Mathematical Methods for Biological Sciences I

PSYC 36211/CPNS 31100     Mathematical Methods for Biological Sciences II

PSYC 37900      Experimental Design and Statistical Modeling II

PSYC 43360      Computational Models of Cognition and Development

 

SOCI 30005       Statistical Methods of Research 2

SOCI 30111       Survey Analysis 1

SOCI 30112       Applications of Hierarchical Linear Models

SOCI 30118       Survey Research Overview

SOCI 30157       Mathematical Models

SOCI 30253/MACS 54000     Introduction to Spatial Data Science

SOCI 40103       Event History Analysis

SOCI 40202       Advanced Topics in Causal Inference

SOCI 40204       Categorical Data Analysis

SOCI 40212       Demographic Technique

SOCI 40217/GEOG 40217/MACS 55000     Spatial Regression Analysis

SOCI 40236/MACS 40236     Panel Data Spatial Econometrics

SOCI 40242       Parametric and Semi-parametric Methods of Categorical Data Analysis

SOCI 40258       Causal Mediation Analysis

SOCI 50123       Seminar: Elegant Models for Social Structure, Probability and Non-Probability Applications

SOCI 50132       Seminar: Causal Inference in Studies of Educational Interventions

SOSC 36008/CHDV 36008/EDSO 36008/PSYC 28926       Principles and Methods of Measurement

SOSC 36011      Fundamentals of Item Response Theory

 

STAT 22200      Linear Models and Experimental Design

STAT 22400/PBHS 32400     Applied Regression Analysis

STAT 22600/PBHS 32600     Analysis of Categorical Data

STAT 22700/PBHS 32700     Biostatistical Methods

STAT 24300/30750    Numerical Linear Algebra

STAT 24620/32950    Multivariate Statistical Analysis: Applications and Techniques

STAT 24630      Causal Inference Methods and Case Studies

STAT 25300/31700    Introduction to Probability Models

STAT 26100/33600    Time Dependent Data

STAT 26300/35490    Introduction to Statistical Genetics

STAT 27400/37400    Nonparametric Inference

STAT 27410      Introduction to Bayesian Data analysis

STAT 27420      Introduction to Causality with Machine Learning

STAT 27725      Machine Learning

STAT 27850/30850    Multiple Testing, Modern Inference, and Replicability

STAT 27855      Hypothesis Testing with Empirical Bayes Methodology

STAT 30100      Mathematical Statistics-1

STAT 30200      Mathematical Statistics-2

STAT 30400      Distribution Theory

STAT 30600      Advanced Statistical Inference 1

STAT 30800      Advanced Statistical Inference II

STAT 30810      High Dimensional Time Series Analysis

STAT 31140/CMSC 31140/CAAM 31140    Computational Imaging: Theory and Methods

STAT 31150/CAAM 31150   Inverse Problems and Data Assimilation

STAT 31200      Introduction to Stochastic Processes I

STAT 31511      Monte Carlo Simulation

STAT 31550      Uncertainty Quantification 

STAT 32940/FINM 33180/CAAM 32940     Multivariate Data Analysis via Matrix Decompositions

STAT 33100      Sample Surveys

STAT 33910/FINM 33170     Financial Statistics: Time Series, Forecasting, Mean Reversion, and High Frequency Data

STAT 34300      Applied Linear Stat Methods

STAT 34500      Design and Analysis of Experiments

STAT 34700      Generalized Linear Models

STAT 34800      Modern Methods in Applied Statistics

STAT 35450/HGEN 48600    Fundamentals of Computational Biology: Models and Inference

STAT 35460/HGEN 48800    Fundamentals of Computational Biology: Algorithms and Applications

STAT 35920      Applied Bayesian Modeling and Inference

STAT 36900/PBHS 33300     Applied Longitudinal Data Analysis

STAT 37601/CMSC 25025    Machine Learning and Large-Scale Data Analysis

STAT 37710      Machine Learning

STAT 37790/CMSC 35425    Topics in Statistical Machine Learning

STAT 37791   Topics in Machine Learning
STAT 37792   Topics in Deep Learning: Generative Models

Note: This list of courses is updated regularly. Courses that are not included in this list generally do not count toward the Certificate requirement. For such a course to be considered, the instructor must file a petition, which will be reviewed and decided upon by the curriculum subcommittee of the Quantitative Methods Committee on a quarterly basis.