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2023-02-10 21:00:10 +00:00

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ECON-6280 - 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 &quot;Big Data.&quot; In this setting, detailed information for each unit of observation informs machine learning techniques such as classification and regression trees; rECandom 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. Â">
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Econometric Methods for Big Data
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ECON-6280
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<p>
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; rECandom 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. Â
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3 credits
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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="summer2 midsum-label">(Session 1)</th>
<th class="summer3 midsum-label">(Session 2)</th>
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<th class="year">2023</th>
<td class="term spring offered">
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Econometric Methods-big Data (3c)
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<ul class="prof-list">
<li>Huaming Peng</li>
</ul>
<span class="course-capacity">
Seats Taken: 0/5
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</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">
Econometric Methods-big Data (3c)
</span>
<ul class="prof-list">
<li>Huaming Peng</li>
</ul>
<span class="course-capacity">
Seats Taken: 0/19
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</td>
</tr>
<tr>
<th class="year">2022</th>
<td class="term spring offered">
<div class="view-container detail-view-container">
<span class="term-course-info">
Econometric Methods-big Data (3c)
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<ul class="prof-list">
<li>Jason Ung Huh</li>
</ul>
<span class="course-capacity">
Seats Taken: 0/19
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<td colspan="2" class="term summer not-offered">
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<td class="term fall offered">
<div class="view-container detail-view-container">
<span class="term-course-info">
Econometric Methods-big Data (3c)
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<ul class="prof-list">
<li>Huaming Peng</li>
</ul>
<span class="course-capacity">
Seats Taken: 4/19
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<th class="year">2021</th>
<td class="term spring offered">
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<span class="term-course-info">
Econometric Methods-big Data (3c)
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<ul class="prof-list">
<li>Jason Ung Huh</li>
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<span class="course-capacity">
Seats Taken: 1/10
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<td colspan="2" class="term summer not-offered">
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<td class="term fall offered">
<div class="view-container detail-view-container">
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Econometric Methods-big Data (3c)
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<ul class="prof-list">
<li>Huaming Peng</li>
</ul>
<span class="course-capacity">
Seats Taken: 2/9
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<th class="year">2020</th>
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<td colspan="2" class="term summer not-offered">
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<td class="term fall offered">
<div class="view-container detail-view-container">
<span class="term-course-info">
Econometric Methods-big Data (3c)
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<ul class="prof-list">
<li>Huaming Peng</li>
</ul>
<span class="course-capacity">
Seats Taken: 0/9
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<td colspan="2" class="term summer not-offered">
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<td class="term fall offered">
<div class="view-container detail-view-container">
<span class="term-course-info">
Econometric Methods-big Data (3c)
</span>
<ul class="prof-list">
<li>Huaming Peng</li>
</ul>
<span class="course-capacity">
Seats Taken: 5/9
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