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ECON-4280: Econometric Methods for Big Data
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< meta property = "og:description" content = "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." >
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Econometric Methods for Big Data
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ECON-4280
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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.
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4 credits
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Prereqs:
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one of:
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< a class = "course-pill" href = "ECON-1200" > ECON-1200 Introductory Economics< / a >
2023-07-27 23:36:01 +00:00
< a class = "course-pill" href = "INQR-1200" > INQR-1200 Principles of Economics< / a >
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one of:
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< a class = "course-pill" href = "MATH-1010" > MATH-1010 Calculus I< / a >
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< a class = "course-pill" href = "MATH-1500" > MATH-1500 Calculus for Architecture, Management, and HASS< / a >
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one of:
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< a class = "course-pill" href = "ENGR-2600" > ENGR-2600 Modeling and Analysis of Uncertainty< / a >
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< a class = "course-pill" href = "MGMT-2100" > MGMT-2100 Statistical Methods< / a >
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< a class = "course-pill" href = "MATP-4600" > MATP-4600 Probability Theory and Applications< / a >
< a class = "course-pill" href = "PSYC-2310" > PSYC-2310 Research Methods and Statistics I< / a >
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Past Term Data
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< th class = "spring season-label" > Spring< / th >
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< th class = "fall season-label" > Fall< / th >
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< th class = "year" > 2023< / th >
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2023-04-05 18:33:00 +00:00
< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=202301&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
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< / span >
< ul class = "prof-list" >
< li > Huaming Peng< / li >
< / ul >
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2023-03-03 04:25:41 +00:00
Seats Taken: 6/19
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2023-04-05 18:33:00 +00:00
< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=202309&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
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< / span >
< ul class = "prof-list" >
< li > Huaming Peng< / li >
< / ul >
< span class = "course-capacity" >
2023-08-08 19:17:11 +00:00
Seats Taken: 8/19
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< th class = "year" > 2022< / th >
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< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=202201&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
2023-02-10 04:02:50 +00:00
< / span >
< ul class = "prof-list" >
< li > Jason Ung Huh< / li >
< / ul >
< span class = "course-capacity" >
Seats Taken: 9/19
< / span >
< / div >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall offered" >
< div class = "view-container detail-view-container" >
< span class = "term-course-info" >
2023-04-05 18:33:00 +00:00
< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=202209&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
2023-02-10 04:02:50 +00:00
< / span >
< ul class = "prof-list" >
< li > Huaming Peng< / li >
< / ul >
< span class = "course-capacity" >
Seats Taken: 12/19
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< th class = "year" > 2021< / th >
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2023-04-05 18:33:00 +00:00
< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=202101&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
2023-02-10 04:02:50 +00:00
< / span >
< ul class = "prof-list" >
< li > Jason Ung Huh< / li >
< / ul >
< span class = "course-capacity" >
Seats Taken: 11/19
< / span >
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< td colspan = "2" class = "term summer not-offered" >
< / td >
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2023-04-05 18:33:00 +00:00
< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=202109&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
2023-02-10 04:02:50 +00:00
< / span >
< ul class = "prof-list" >
< li > Huaming Peng< / li >
< / ul >
< span class = "course-capacity" >
Seats Taken: 11/19
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< th class = "year" > 2020< / th >
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< / td >
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2023-04-05 18:33:00 +00:00
< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=202009&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
2023-02-10 04:02:50 +00:00
< / span >
< ul class = "prof-list" >
< li > Huaming Peng< / li >
< / ul >
< span class = "course-capacity" >
Seats Taken: 10/19
< / span >
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< th class = "year" > 2019< / th >
< td class = "term spring not-offered" >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall offered" >
< div class = "view-container detail-view-container" >
< span class = "term-course-info" >
2023-04-05 18:33:00 +00:00
< a href = "https://sis.rpi.edu/rss/bwckctlg.p_disp_listcrse?term_in=201909&subj_in=ECON&crse_in=4280&schd_in=" > Econometric Methods-big Data (4c)< / a >
2023-02-10 04:02:50 +00:00
< / span >
< ul class = "prof-list" >
< li > Huaming Peng< / li >
< / ul >
< span class = "course-capacity" >
Seats Taken: 6/19
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< th class = "year" > 2018< / th >
< td class = "term spring not-offered" >
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< td class = "term fall not-offered" >
< / td >
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< tr >
< th class = "year" > 2017< / th >
< td class = "term spring not-offered" >
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< td colspan = "2" class = "term summer not-offered" >
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< td class = "term fall not-offered" >
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< td class = "term fall not-offered" >
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< td class = "term spring not-offered" >
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< / td >
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< / td >
< td class = "term fall not-offered" >
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< td class = "term spring not-offered" >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall not-offered" >
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< / tr >
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< td class = "term spring not-offered" >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall not-offered" >
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< th class = "year" > 2011< / th >
< td class = "term spring not-offered" >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall not-offered" >
< / td >
< / tr >
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< th class = "year" > 2010< / th >
< td class = "term spring not-offered" >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall not-offered" >
< / td >
< / tr >
< tr >
< th class = "year" > 2009< / th >
< td class = "term spring not-offered" >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall not-offered" >
< / td >
< / tr >
< tr >
< th class = "year" > 2008< / th >
< td class = "term spring not-offered" >
< / td >
< td colspan = "2" class = "term summer not-offered" >
< / td >
< td class = "term fall not-offered" >
< / td >
< / tr >
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< th class = "year" > 2007< / th >
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< / td >
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< / td >
< td class = "term fall not-offered" >
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< td class = "term spring not-offered" >
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< / td >
< td class = "term fall not-offered" >
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< / td >
< td class = "term fall not-offered" >
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< / tr >
< tr >
< th class = "year" > 2002< / th >
< td class = "term spring not-offered" >
< / td >
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< / td >
< td class = "term fall not-offered" >
< / td >
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< td class = "term spring not-offered" >
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< / td >
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< / td >
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< / td >
< td class = "term fall not-offered" >
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< th class = "year" > 1999< / th >
< td class = "term spring not-offered" >
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< td class = "term fall not-offered" >
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2023-02-10 04:02:50 +00:00
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2023-02-22 04:39:06 +00:00
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