Learn how statistics plays a central role in the data science approach from Columbia University USA.
This statistics and data analysis course will pave the statistical foundation for our discussion on data science.
User Review
( votes)You will learn how data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, obtain supporting evidence for data-based decisions and construct models for predicting future trends from data.
This is the first course in the three-part Data Science and Analytics XSeries.
Brief Details
Length: 5 weeks
Effort: 7 – 10 hours per week
Price: Free
Institution: ColumbiaX
Subject: Data Analysis & Statistics
Level: Introductory
Languages: English
Video Transcripts: English
What you’ll learn
- Data collection, analysis and inference
- Relationship between variables
- Types of association
- Conditional probability
- Bayes’ Rule
- Goals of data visualization
- Statistical comparisons that underlie data graphics
- How Bayesian inference is used to combine sources of information
- Identify situations where Bayesian modeling can be useful
Instructors
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Eva Ascarza
Assistant Professor of Marketing at Columbia Business School Columbia University -
James Curley
Assistant Professor of Psychology Columbia University -
Andrew Gelman
Professor of Statistics and Political Science Columbia University -
Lauren Hannah
Assistant Professor in the Department of Statistics Columbia University -
David Madigan
Executive Vice President and Dean of Faculty of Arts and Sciences Columbia University -
Tian Zheng
Series Creator Columbia University
Course Starts on December 14, 2015
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