Data Science: Inference and Modeling

MOOC
Data Science: Inference and Modeling
Language
English
Duration
5 months
Certificate
Certification paid
Course by EdX
Data Science: Inference and Modeling
What will you learn?
The concepts necessary to define estimates and margins of errors of populations, parameters, estimates and standard errors in order to make predictions about data
How to use models to aggregatedata from different sources
The very basics of Bayesian statistics and predictive modeling
About the course

Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting.

This course will show you how inference and modeling can be applied to develop the statistical approaches that make polls an effective tool and we'll show you how to do this using R. You will learn concepts necessary to define estimates and margins of errors and learn how you can use these to make predictions relatively well and also provide an estimate of the precision of your forecast.

Once you learn this you will be able to understand two concepts that are ubiquitous in data science: confidence intervals, and p-values. Then, to understand statements about the probability of a candidate winning, you will learn about Bayesian modeling. Finally, at the end of the course, we will put it all together to recreate a simplified version of an election forecast model and apply it to the 2016 election.

Program
Data Science: Inference and Modeling
Learn inference and modeling, two of the most widely used statistical tools in data analysis.
Lecturers
Rafael Irizarry
Rafael Irizarry
Professor of Biostatistics Harvard University
Platform
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All the courses on this platform are free of charge. The authors are top universities and corporations that seek to maintain high quality standards. If you do not meet a deadline for assignments, you lose points. Like on other platforms, the videos in which the theory is explained are followed by practical assignments. Courses are available in English, Chinese, Spanish, French and Hindi.
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