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. The most desired skill in data science
  2. The Third Wave Data Scientist
  3. The 3 Biggest Mistakes on Learning Data Science
  4. Data Visualization in Python: Matplotlib vs Seaborn
  5. Data Scientist — Best Job of the Year in USA
  6. How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists with Serious Guides
  7. 9 Must-have skills you need to become a Data Scientist, updated
Most Shared
  1. Top Data Science and Machine Learning Methods Used in 2018, 2019
  2. The most desired skill in data science
  3. The Third Wave Data Scientist
  4. The 3 Biggest Mistakes on Learning Data Science
  5. 7 Steps to Mastering SQL for Data Science — 2019 Edition
  6. How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists with Serious Guides
  7. Normalization vs Standardization — Quantitative analysis

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

By subscribing you accept KDnuggets Privacy Policy