Massachusetts Institute of Technology is offering free online course on Data Analysis for Social Scientists. This course is designed for anyone who wants to learn how to work with data and communicate data-driven findings effectively, but it is challenging.
In this twelve week course, applicants will learn methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest. This course will start on June 5, 2018.
Course At A Glance
Length: 12 weeks
Effort: 12 hours pw
Subject: Social Sciences
Institution: Massachusetts Institute of Technology and edx
Session: Course Starts on June 5, 2018
Massachusetts Institute of Technology a coeducational, privately endowed research university founded in 1861 is dedicated to advancing knowledge and educating students in science, technology, and other areas of scholarship that will best serve the nation and the world in the 21st century.
About This Course
This statistics and data analysis course will introduce you to the essential notions of probability and statistics. We will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization.
Why Take This Course?
This course is designed for anyone who wants to learn how to work with data and communicate data-driven findings effectively, but it is challenging. Students who are uncomfortable with basic calculus and algebra might struggle with the pace of the class.
- Intuition behind probability and statistical analysis.
- How to summarize and describe data.
- A basic understanding of various methods of evaluating social programs.
- How to present results in a compelling and truthful way.
- Skills and tools for using R for data analysis.
Esther Duflo is the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at MIT.
Sara Fisher Ellison
Sara Fisher Ellison is a Senior Lecturer in the MIT Economics Department. She was an undergraduate at Purdue University and received graduate degrees from both Cambridge University and MIT.
No prior preparation in probability and statistics is required, but familiarity with algebra and calculus is assumed.
How To Join This Course
- Go to the course website link
- Create an edX account to SignUp
- Choose “Register Now” to get started.
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