Data Scientist's Toolbox: Difference between revisions
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=== Week 3 === | === Week 3 === | ||
==== Types of Questions ==== | ==== Types of Questions ==== | ||
Types of analysis | |||
* descriptive: describe the data, like census | |||
* exploratory: find relationships (not causation) | |||
* inferential: use a small sample to say something about a bigger population | |||
* predictive: use data on some object to predict values for another object (still not causation) | |||
* causal: find out what happens t one variable when you change another variable (very difficult) | |||
* mechanistic: understand the exact changes in variables that lead to changes in other variables (very difficult, next to impossible unless system is nearly deterministic) | |||
==== What is data ==== | ==== What is data ==== | ||
==== What about Big Data ==== | ==== What about Big Data ==== | ||
Revision as of 15:31, 19 January 2015
Video Lectures
Week 1
Series Motivation
The Data Scientist's Toolbox
Getting Help
Finding Answers
Week 3
Types of Questions
Types of analysis
- descriptive: describe the data, like census
- exploratory: find relationships (not causation)
- inferential: use a small sample to say something about a bigger population
- predictive: use data on some object to predict values for another object (still not causation)
- causal: find out what happens t one variable when you change another variable (very difficult)
- mechanistic: understand the exact changes in variables that lead to changes in other variables (very difficult, next to impossible unless system is nearly deterministic)