Follow Gregory Piatetsky, No. 1 on LinkedIn Top Voices in Data Science & Analytics

KDnuggets Home » News » 2017 » Apr » Webcasts & Webinars » Stanford Webinar: Pitfalls of A/B Testing ( 17:n16 )

Stanford Webinar: Pitfalls of A/B Testing


 
 
Tags: , ,

Join Ramesh Johari, Associate Professor, Stanford Department of Management Science & Engineering, as he discusses some common practices and pitfalls in A/B testing, Apr 26, 2017.


 
 
 
 
You're Invited!
Free Stanford Webinar
Common Pitfalls of A/B Testing and How to Avoid Them
 
A/B testing is the process of using randomized controlled experiments on a web page or technology platform to determine which has a higher conversion rate. While this method of testing has become ubiquitous, there remain some common traps to which even the most sophisticated data scientists fall prey.

Join Ramesh Johari, Associate Professor, Stanford Department of Management Science & Engineering, as he discusses some common practices and pitfalls in A/B testing.

You will learn:
bullet To analyze the output of A/B tests
 
bullet To balance quick results with statistical significance during continuous monitoring
 
bullet To maintain data integrity when running simultaneous experiments

Presented by the Management Science & Engineering  and Decision Analysis Graduate Certificates
Questions? Contact 650 204-3984 or scpd-customerservice@stanford.edu.
 
Date: April 26, 2017
Day: Wednesday
Time: 10am-11am PDT
 
 
Venue:
Online via Webex
 
 
events  Upcoming Events
April 9-June 18, 2017
 
Graduate Education. Professional Certification.
online | at Stanford | at work
facebook Twitter LinkedIn YouTube google+



Top Stories Past 30 Days

Most Popular
  1. Why You Shouldn't be a Data Science Generalist
  2. 9 Must-have skills you need to become a Data Scientist, updated
  3. The cold start problem: how to build your machine learning portfolio
  4. Introduction to Statistics for Data Science
  5. The Essence of Machine Learning
  6. The Five Best Data Visualization Libraries
  7. 10 More Must-See Free Courses for Machine Learning and Data Science
Most Shared
  1. 10 More Must-See Free Courses for Machine Learning and Data Science
  2. The Essence of Machine Learning
  3. Introduction to Statistics for Data Science
  4. Papers with Code: A Fantastic GitHub Resource for Machine Learning
  5. A Guide to Decision Trees for Machine Learning and Data Science
  6. Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning
  7. The cold start problem: how to build your machine learning portfolio

KDnuggets Home » News » 2017 » Apr » Webcasts & Webinars » Stanford Webinar: Pitfalls of A/B Testing ( 17:n16 )

Get KDnuggets, a leading newsletter on AI, Data Science, and Machine Learning
Sign Up