list 5 sequences
assignment Level : Introductive
chat_bubble_outline Language : English
card_giftcard 280 points
Users' reviews
4.8
starstarstarstar
Read review

Key information

credit_card Free access
verified_user Fee-based Certificate
timer 35 hours in total

About the content

This statistics and data analysis course will pave the statistical foundation for our discussion on data science.

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.

  • Data collection, analysis and inference
  • Data classification to identify key traits and customers
  • Conditional Probability-How to judge the probability of an event, based on certain conditions
  • How to use Bayesian modeling and inference for forecasting and studying public opinion
  • Basics of Linear Regression
  • Data Visualization: How to create use data to create compelling graphics

more_horiz Read more
more_horiz Read less
report_problem

Prerequisite

High School Math. Some exposure to computer programming.

dns

Syllabus

Week 1 – Introduction to Data Science


Week 2 – Statistical Thinking

  • Examples of Statistical Thinking
  • Numerical Data, Summary Statistics
  • From Population to Sampled Data
  • Different Types of Biases
  • Introduction to Probability
  • Introduction to Statistical Inference 


Week 3 – Statistical Thinking 2

  • Association and Dependence
  • Association and Causation
  • Conditional Probability and Bayes Rule
  • Simpsons Paradox, Confounding
  • Introduction to Linear Regression
  • Special Regression Models


Week 4 – Exploratory Data Analysis and Visualization

  • Goals of statistical graphics and data visualization
  • Graphs of Data
  • Graphs of Fitted Models
  • Graphs to Check Fitted Models
  • What makes a good graph?
  • Principles of graphics


Week 5 – Introduction to Bayesian Modeling

  • Bayesian inference: combining models and data in a forecasting problem
  • Bayesian hierarchical modeling for studying public opinion
  • Bayesian modeling for Big Data
record_voice_over

Instructors

Andrew Gelman
Professor of Statistics and Political Science
Columbia University

David Madigan
Executive Vice President and Dean of Faculty of Arts and Sciences
Columbia University

Lauren Hannah
Assistant Professor in the Department of Statistics
Columbia University

Eva Ascarza
Assistant Professor of Marketing at Columbia Business School
Columbia University

James Curley
Assistant Professor of Psychology
Columbia University

Tian Zheng
Series Creator
Columbia University

store

Content designer

Columbia University
For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries and service to society.
assistant

Platform

Edx

Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with EdX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

Reviews
4.8 /5 Average
starstarstarstarstar
1
starstarstarstarstar
0
starstarstarstarstar
0
starstarstarstarstar
0
starstarstarstarstar
0
Content
5/5
Platform
5/5
Animation
4.5/5
Best review

J'ai beaucoup aimé ce MOOC Il est à la fois accessible et permet d'acquérir des notions assez pointues. Il demande suffisamment de travail pour que l'obtention du certificat soit perçu comme une victoire. Et ça faisait longtemps que j'avais pas éprouvé autant de plaisir à en terminer un ! Sur le contenu, il s'agit surtout de l'exploration de quelques champs d'applications des statistiques modernes. L'analyse de texte, la génomique, le big data évidemment, et d'autres domaines tout aussi passionnants. Compter environ 3 heures par semaine pour des techophiles maîtrisant l'anglais. Le double pour les autres. Mais le jeu en vaut la chandelle !

Published on March 30, 2016
You are the designer of this MOOC?
What is your opinion on this resource ?
Content
0/5
Platform
0/5
Animation
0/5
on the March 30, 2016
starstarstarstar

J'ai beaucoup aimé ce MOOC Il est à la fois accessible et permet d'acquérir des notions assez pointues. Il demande suffisamment de travail pour que l'obtention du certificat soit perçu comme une victoire. Et ça faisait longtemps que j'avais pas éprouvé autant de plaisir à en terminer un ! Sur le contenu, il s'agit surtout de l'exploration de quelques champs d'applications des statistiques modernes. L'analyse de texte, la génomique, le big data évidemment, et d'autres domaines tout aussi passionnants. Compter environ 3 heures par semaine pour des techophiles maîtrisant l'anglais. Le double pour les autres. Mais le jeu en vaut la chandelle !