# Econometric Methods for Big Data

## ECON-4280

Examine advanced econometric and statistical methods for the analysis of high-dimensional data, otherwise known as "Big Data." In this setting, detailed information for each unit of observation informs machine learning techniques such as classification and regression trees; random forests; penalized regressions; and boosted estimation. These prediction methods are then utilized to improve causal modeling, with applications in the study of healthcare demand and supply modeling, and behavior of consumers and businesses.

4 credits
Prereqs:
one of:
ECON-1200 Introductory Economics IHSS-1200 Principles of Economics
and
one of:
MATH-1010 Calculus I MATH-1500 Calculus for Architecture, Management, and HASS
and
one of:
ENGR-2600 Modeling and Analysis of Uncertainty MGMT-2100 Statistical Methods MATP-4600 Probability Theory and Applications PSYC-2310 Research Methods and Statistics I

# Past Term Data
Offered
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No Term Data
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| Spring | Summer | Fall
--- | --- | --- | ---
| (Session 1) | (Session 2) |
2023 | Econometric Methods-big Data (4c) Huaming Peng Seats Taken: 7/19 |  | Econometric Methods-big Data (4c) Huaming Peng Seats Taken: 0/19
2022 | Econometric Methods-big Data (4c) Jason Ung Huh Seats Taken: 9/19 |  | Econometric Methods-big Data (4c) Huaming Peng Seats Taken: 12/19
2021 | Econometric Methods-big Data (4c) Jason Ung Huh Seats Taken: 11/19 |  | Econometric Methods-big Data (4c) Huaming Peng Seats Taken: 11/19
2020 |  |  | Econometric Methods-big Data (4c) Huaming Peng Seats Taken: 10/19
2019 |  |  | Econometric Methods-big Data (4c) Huaming Peng Seats Taken: 6/19
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