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Applied Econometrics: Mostly Harmless Big Data
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This course covers empirical strategies for applied micro research questions. Our agenda includes regression and matching, instrumental variables, differences-in-differences, regression discontinuity designs, standard errors, and a module consisting of 8–9 lectures on the analysis of high-dimensional data sets a.k.a. "Big Data".

Subject:
Applied Science
Computer Science
Economics
Engineering
Mathematics
Social Science
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Angrist, Joshua
Chernozhukov, Victor
Date Added:
09/01/2014
Data Analysis for Social Scientists
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This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. We will start with essential notions of probability and statistics. We will proceed to cover techniques in modern data analysis: regression and econometrics, design of experiments, randomized control trials (and A/B testing), machine learning, and data visualization.
We will illustrate these concepts with applications drawn from real-world examples and frontier research. Finally, we will provide instruction on the use of the statistical package R, and opportunities for students to perform self-directed empirical analyses.
MITx Online
This course draws materials from 14.310x Data Analysis for Social Scientists, which is part of the MicroMasters Program in Data, Economics, and Design of Policy offered by MITx Online. The MITx Online course is entirely free to audit, though learners have the option to pay a fee, which is based on the learner’s ability to pay, to take the proctored exam and earn a course certificate. To access that course, create an MITx Online account and enroll in the course 14.310x Data Analysis for Social Scientists.

Subject:
Economics
Mathematics
Social Science
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Duflo, Esther
Ellison, Sara
Date Added:
02/01/2023
Econometrics
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Introduction to econometric models and techniques, simultaneous equations, program evaluation, emphasizing regression. Advanced topics include instrumental variables, panel data methods, measurement error, and limited dependent variable models. May not count toward HASS requirement.

Subject:
Economics
Mathematics
Social Science
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Angrist, Joshua
Date Added:
02/01/2007
Econometrics
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CC BY-NC-SA
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The course will cover several key models as well as identification and estimation methods used in modern econometrics. We shall being with exploring some leading models of econometrics, then seeing structures, then providing methods of identification, estimation, and inference. You will get lots of hands-on experience with using the methods on real data sets.

Subject:
Economics
Social Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Chernozhukov, Victor
Date Added:
02/01/2017
Econometrics Textbook
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Educational Use
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Econometrics is the study of estimation and inference for economic models using economic data. Econometric theory concerns the study and development of tools and methods for applied econometric applications. Applied econometrics concerns the application of these tools to economic data.

Subject:
Business and Communication
Economics
Social Science
Material Type:
Textbook
Provider:
University of Wisconsin
Author:
Bruce Hansen
Date Added:
01/01/2016
Statistical Method in Economics
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CC BY-NC-SA
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This course is divided into two sections, Part I and Part II. Part I, found here, provides an introduction to statistical theory. Topics include normal distribution, limit theorems, Bayesian concepts, and testing, among others.

Subject:
Economics
Mathematics
Social Science
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Mikusheva, Anna
Date Added:
09/01/2018
Understanding Data
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Data is all around us. Everything from the fitness tracker on your wrist to researchers at your local university are creating mountains of data — big data. What does all this data mean? And how can it help us answer important questions such as: What are the leading causes of heart disease? Or what patterns are related to higher pay at your job? Looking at data can help us answer fun questions too — who’s likely to win the next Super Bowl? Leave the boring lectures behind and intuitively learn data analysis through interactive exercises that allow you to play with fascinating real-world datasets. By the end of this course, you’ll be comfortable applying the basics of statistical analysis and econometrics. There are no prerequisites and we encourage you to repeat the interactive lessons as often as you need.

Subject:
Economics
Social Science
Material Type:
Full Course
Provider:
Marginal Revolution University
Author:
Thomas Stratmann
Date Added:
05/18/2017