Trustworthy Online Controlled Experiments - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Trustworthy Online Controlled Experiments write by Ron Kohavi. This book was released on 2020-04-02. Trustworthy Online Controlled Experiments available in PDF, EPUB and Kindle. Getting numbers is easy; getting numbers you can trust is hard. This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to • Use the scientific method to evaluate hypotheses using controlled experiments • Define key metrics and ideally an Overall Evaluation Criterion • Test for trustworthiness of the results and alert experimenters to violated assumptions • Build a scalable platform that lowers the marginal cost of experiments close to zero • Avoid pitfalls like carryover effects and Twyman's law • Understand how statistical issues play out in practice.
Experimentation Works
Experimentation Works - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Experimentation Works write by Stefan H. Thomke. This book was released on 2020-02-18. Experimentation Works available in PDF, EPUB and Kindle. Don't fly blind. See how the power of experiments works for you. When it comes to improving customer experiences, trying out new business models, or developing new products, even the most experienced managers often get it wrong. They discover that intuition, experience, and big data alone don't work. What does? Running disciplined business experiments. And what if companies roll out new products or introduce new customer experiences without running these experiments? They fly blind. That's what Harvard Business School professor Stefan Thomke shows in this rigorously researched and eye-opening book. It guides you through best practices in business experimentation, illustrates how these practices work at leading companies, and answers some fundamental questions: What makes a good experiment? How do you test in online and brick-and-mortar businesses? In B2B and B2C? How do you build an experimentation culture? Also, best practice means running many experiments. Indeed, some hugely successful companies, such as Amazon, Booking.com, and Microsoft, run tens of thousands of controlled experiments annually, engaging millions of users. Thomke shows us how these and many other organizations prove that experimentation provides significant competitive advantage. How can managers create this capability at their own companies? Essential is developing an experimentation organization that prizes the science of testing and puts the discipline of experimentation at the center of its innovation process. While it once took companies years to develop the tools for such large-scale experiments, advances in technology have put these tools at the fingertips of almost any business professional. By combining the power of software and the rigor of controlled experiments, today's managers can make better decisions, create magical customer experiences, and generate big financial returns. Experimentation Works is your guidebook to a truly new way of thinking and innovating.
Trustworthy Online Controlled Experiments
Trustworthy Online Controlled Experiments - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Trustworthy Online Controlled Experiments write by Ron Kohavi. This book was released on 2020-02-14. Trustworthy Online Controlled Experiments available in PDF, EPUB and Kindle. This practical guide for students, researchers and practitioners offers real world guidance for data-driven decision making and innovation.
You Should Test That
You Should Test That - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook You Should Test That write by Chris Goward. This book was released on 2012-12-21. You Should Test That available in PDF, EPUB and Kindle. Learn how to convert website visitors into customers Part science and part art, conversion optimization is designed to turn visitors into customers. Carefully developed testing procedures are necessary to help you fine-tune images, headlines, navigation, colors, buttons, and every other element, creating a website that encourages visitors to take the action you seek. This book guides you through creating an optimization strategy that supports your business goals, using appropriate analytics tools, generating quality testing ideas, running online experiments, and making the adjustments that work. Conversion optimization is part science and part art; this guide provides step-by-step guidance to help you optimize your website for maximum conversion rates Explains how to analyze data, prioritize experiment opportunities, and choose the right testing methods Helps you learn what to adjust, how to do it, and how to analyze the results Features hands-on exercises, case studies, and a full-color insert reinforcing key tactics Author has used these techniques to assist Fortune 500 clients You Should Test That explains both the "why" and the "how" of conversion optimization, helping you maximize the value of your website.
Experimentation for Engineers
Experimentation for Engineers - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Experimentation for Engineers write by David Sweet. This book was released on 2023-03-21. Experimentation for Engineers available in PDF, EPUB and Kindle. Optimize the performance of your systems with practical experiments used by engineers in the world’s most competitive industries. In Experimentation for Engineers: From A/B testing to Bayesian optimization you will learn how to: Design, run, and analyze an A/B test Break the "feedback loops" caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization Clearly define business metrics used for decision-making Identify and avoid the common pitfalls of experimentation Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of techniques for evaluating new features and fine-tuning parameters. You’ll start with a deep dive into methods like A/B testing, and then graduate to advanced techniques used to measure performance in industries such as finance and social media. Learn how to evaluate the changes you make to your system and ensure that your testing doesn’t undermine revenue or other business metrics. By the time you’re done, you’ll be able to seamlessly deploy experiments in production while avoiding common pitfalls. About the technology Does my software really work? Did my changes make things better or worse? Should I trade features for performance? Experimentation is the only way to answer questions like these. This unique book reveals sophisticated experimentation practices developed and proven in the world’s most competitive industries that will help you enhance machine learning systems, software applications, and quantitative trading solutions. About the book Experimentation for Engineers: From A/B testing to Bayesian optimization delivers a toolbox of processes for optimizing software systems. You’ll start by learning the limits of A/B testing, and then graduate to advanced experimentation strategies that take advantage of machine learning and probabilistic methods. The skills you’ll master in this practical guide will help you minimize the costs of experimentation and quickly reveal which approaches and features deliver the best business results. What's inside Design, run, and analyze an A/B test Break the “feedback loops” caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization About the reader For ML and software engineers looking to extract the most value from their systems. Examples in Python and NumPy. About the author David Sweet has worked as a quantitative trader at GETCO and a machine learning engineer at Instagram. He teaches in the AI and Data Science master's programs at Yeshiva University. Table of Contents 1 Optimizing systems by experiment 2 A/B testing: Evaluating a modification to your system 3 Multi-armed bandits: Maximizing business metrics while experimenting 4 Response surface methodology: Optimizing continuous parameters 5 Contextual bandits: Making targeted decisions 6 Bayesian optimization: Automating experimental optimization 7 Managing business metrics 8 Practical considerations
