ºÝºÝߣshows by User: georgf1 / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: georgf1 / Thu, 18 Jun 2015 20:36:53 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: georgf1 Hypothesis Driven Development at Agile Australia 2015 /slideshow/hypothesis-driven-development/49573354 hypothesisdrivendev-150618203653-lva1-app6892
Knowing a little bit about statistics can be a dangerous thing. Most companies doing experimentation don’t even realise the mistakes they’re making, and end up drawing the wrong conclusions from their tests. * When can data be misleading? * When to use A/B testing and when to use other methods. * How to run an A/B experiment and be confident in the result. * Common mistakes most companies make when A/B testing, and how to avoid them.]]>
Knowing a little bit about statistics can be a dangerous thing. Most companies doing experimentation don’t even realise the mistakes they’re making, and end up drawing the wrong conclusions from their tests. * When can data be misleading? * When to use A/B testing and when to use other methods. * How to run an A/B experiment and be confident in the result. * Common mistakes most companies make when A/B testing, and how to avoid them.]]> Thu, 18 Jun 2015 20:36:53 GMT /slideshow/hypothesis-driven-development/49573354 georgf1@slideshare.net(georgf1) Hypothesis Driven Development at Agile Australia 2015 georgf1 Knowing a little bit about statistics can be a dangerous thing. Most companies doing experimentation don’t even realise the mistakes they’re making, and end up drawing the wrong conclusions from their tests. * When can data be misleading? * When to use A/B testing and when to use other methods. * How to run an A/B experiment and be confident in the result. * Common mistakes most companies make when A/B testing, and how to avoid them. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hypothesisdrivendev-150618203653-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Knowing a little bit about statistics can be a dangerous thing. Most companies doing experimentation don’t even realise the mistakes they’re making, and end up drawing the wrong conclusions from their tests. * When can data be misleading? * When to use A/B testing and when to use other methods. * How to run an A/B experiment and be confident in the result. * Common mistakes most companies make when A/B testing, and how to avoid them.
Hypothesis Driven Development at Agile Australia 2015 from Georg Friedrich
]]> 748 2 https://cdn.slidesharecdn.com/ss_thumbnails/hypothesisdrivendev-150618203653-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-georgf1-48x48.jpg?cb=1524448382 Georg Friedrich's experience spans 15 years of software development roles in industries ranging from printing to online fundraising and e-commerce. In 2007 he co-founded betterplace.org which quickly became Germany’s biggest online donation platform. He joined Redbubble in 2009 and helped establish a lean delivery approach. He has continued to play a key role in its implementation as the team has undergone rapid growth.