A/B Testing, A Data Science Perspective Training Video Год выпуска: 2015 Производитель: O'Reilly Media / Infinite Skills Сайт производителя: oreilly.com, infiniteskills.com Автор: Lisa Qian Продолжительность: 1:17 Тип раздаваемого материала: Видеоклипы Язык: Английский Описание: Deciding whether or not to launch a new product or feature is a resource management bet for any Internet business. Conducting rigorous online A/B tests flattens the risk. Drawing on her experience at Airbnb, data scientist Lisa Qian offers a practical ten-step guide to designing and executing statistically sound A/B tests. - Discover best practices for defining test goals and hypotheses - Learn to identify controls, treatments, key metrics, and data collection needs - Understand the role of appropriate logging in data collection - Determine how to frame your tests (size of difference detection, visitor sample size, etc.) - Master the importance of testing for systematic biases - Run power tests to determine how much data to collect - Learn how experimenting on logged out users can introduce bias - Understand when cannibalization is an issue and how to deal with it - Review accepted A/B testing tools (Google Analytics, Vanity, Unbounce, among others) Lisa Qian focuses on search and discovery at Airbnb. She has a PhD in Applied Physics from Stanford University. Принятия решения о целесообразности запуска нового продукта или функция управления ресурсами ставку для любого интернет-бизнеса. Проведение скрупулезного онлайн А/Б тесты сглаживает риск. Опираясь на ее опыт с Airbnb, данных ученый Лиза Цянь предлагает практические десяти шагом руководство для проектирования и выполнения статистически звука a/b тесты.
Содержание
01. A/B Testing, A Data Science Perspective 0101 Overview of the Course 0102 Why Should You Run A/B Tests? 0103 The 10 Steps and An Overview of Case Studies 0104 Case Study 1: Red vs. Green Button 0105 Case Study 2: Testing a New Landing Page 0106 Case Study 3: Price Recommendations on an Online Marketpl 0107 Summary: Setting Up an A/B Test 0108 Some of Your Options 0109 Scaling A/B Testing and Developing a Culture of Experimentation
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