## ECON 102A: Introduction to Statistical Methods (Postcalculus) for Social Scientists

Probabilistic modeling and statistical techniques relevant for economics. Concepts include: probability trees, conditional probability, random variables, discrete and continuous distributions, correlation, central limit theorems, point estimation, hypothesis testing and confidence intervals for both one and two populations. Prerequisite:
MATH 20 or equivalent.

Terms: Aut, Win, Sum
| Units: 5
| UG Reqs: GER:DB-Math, WAY-AQR, WAY-SI

Instructors:
McKeon, S. (PI)
;
Hong, H. (SI)
;
Imbens, G. (SI)
;
Romano, J. (SI)
;
Cao, Y. (TA)
;
Caratelli, D. (TA)
;
Qiu, X. (TA)
;
Yany Anich, A. (TA)
;
Zempleni, R. (TA)

## ECON 102D: Econometric Methods for Public Policy Analysis and Business Decision-Making

This course focuses on the use of econometric methods in public policy analysis and business decision-making. Building on methods taught in Economics 102A and 102B, additional descriptive, predictive and causal econometric modeling methods will be introduced along with the assumptions required for the validity of each methodology. Methods for designing randomized controlled trials (RCT) and analyzing the resulting data will be discussed. The methods for recovering economically meaningful magnitudes such as price elasticities of demand and other behavioral responses from observational data will be discussed. Both classical econometric methods and modern techniques in machine learning will be employed. The class will be taught using the R programming language. Students will perform both in-class and out-of-class assignments working with actual datasets to address policy-relevant decisions and simulation exercises designed to deepen their knowledge of these methods. Prerequisites:
Econ102A,
Econ102B

Terms: Aut
| Units: 5
| UG Reqs: WAY-AQR

Instructors:
Wolak, F. (PI)
;
Naumann, R. (TA)

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