Date
Wednesday, 25 Nov 2015 10:00 AM
You must officially register in the course page to attend. Secure your spot HERE.
Melbourne Silicon Beach in association with Collective Campus presents Introduction to Causality.
This is a paid workshop for anyone who works with Data (Analysts, Digital Marketer, and Statisticians), R Users, Data Scientists and The curious at heart.
All Silicon Beachers receive a 20% discount if you pay for the workshop using the discount code ‘siliconbeach’.
This 1-day intensive currently has an early-bird price of $399 (RRP $499) with more discounts provided if you sign up in groups. Sign up to the course here.
===
In this one-day course, participants will be introduced to causal thinking. We’ll start with the experimental idea: how do we work out causation when we get to apply A-B tests everywhere. Unfortunately, experiments are not always practical or ethical. In these cases, we need to use different methods: regression with controls, panel data methods, instrumental variables, regression discontinuity design, and matching estimators.
At the end of the day, participants should feel equipped to structure analysis into causal problems (like policy effectiveness, demand elasticities and marketing campaign effectiveness) in such a way as to get the best estimate of the underlying causal relationships. The course will contain worked examples using R, though participants who are comfortable using some other statistical package can use those. As a pre-requisite, participants should feel comfortable running and interpreting a linear regression; they may have recently completed the Introduction to Data Science course.
What You Will Learn
• Introduction to Causal Thinking
• Regression with Controls
• Panel Data Methods
• Instrumental Variables
• Matching Estimators
Regression Discontinuity Design
About The Instructor
Jim Savage is an experienced data scientist and educator. He is currently the Lead Data Scientist at US startup Lendable, and a lecturer at La Trobe University. Before that, he was a Senior Associate at the Grattan Institute, a Data Science Fellow at the University of Chicago, and an Analyst at the Australian Treasury.
