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.
Length: 5 weeks
Effort: 7 – 10 hours per week
Subject: Data Analysis & Statistics
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
Assistant Professor of Marketing at Columbia Business School Columbia University
Assistant Professor of Psychology Columbia University
Professor of Statistics and Political Science Columbia University
Assistant Professor in the Department of Statistics Columbia University
Executive Vice President and Dean of Faculty of Arts and Sciences Columbia University
Series Creator Columbia University
Course Starts on December 14, 2015
[button link=”https://www.edx.org/course/statistical-thinking-data-science-columbiax-ds101x#!” window=”yes”]Apply Now[/button]