Trustworthy Online Controlled Experiments

Author: Ron Kohavi
Publisher: Cambridge University Press
ISBN: 1108590098
Category : Computers
Languages : en
Pages : 291

Book Description
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.

Trustworthy Online Controlled Experiments

Author: Ron Kohavi
Publisher: Cambridge University Press
ISBN: 1108724264
Category : Business & Economics
Languages : en
Pages : 291

Book Description
This practical guide for students, researchers and practitioners offers real world guidance for data-driven decision making and innovation.

Experimentation Works

Author: Stefan H. Thomke
Publisher: Harvard Business Press
ISBN: 1633697118
Category : Business & Economics
Languages : en
Pages : 266

Book Description
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.

Experimentation for Engineers

Author: David Sweet
Publisher: Simon and Schuster
ISBN: 1638356904
Category : Computers
Languages : en
Pages : 246

Book Description
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

Testing 1 - 2 - 3

Author: Johannes Ledolter
Publisher: Stanford University Press
ISBN: 9780804756129
Category : Business & Economics
Languages : en
Pages : 326

Book Description
This book gives students, practitioners, and managers a set of practical and valuable tools for designing and analyzing experiments, emphasizing applications in marketing and service operations such as website design, direct mail campaigns, and in-store tests.

Statistical Methods in Online A/B Testing

Author: Georgi Zdravkov Georgiev
Publisher:
ISBN: 9781694079725
Category :
Languages : en
Pages : 302

Book Description
"Statistical Methods in Online A/B Testing" is a comprehensive guide to statistics in online controlled experiments, a.k.a. A/B tests, that tackles the difficult matter of statistical inference in a way accessible to readers with little to no prior experience with it. Each concept is built from the ground up, explained thoroughly, and illustrated with practical examples from website testing. The presentation is straight to the point and practically oriented so you can apply the takeaways in your daily work.It is a must-read for anyone looking for a deep understanding of how to make data-driven business decisions through experimentation: conversion rate optimizers, product managers, growth experts, data analysts, marketing managers, experts in user experience and design. The new research presented and the fresh perspective on how to apply statistics and experimentation to achieve business goals make for an interesting read even for experienced statisticians.The book deals with scientific methods, but their introductions and explanations are grounded in the business goals they help achieve, such as innovating under controlled risk, and estimating the effect of proposed business actions before committing to them. While the book doesn't shy away from math and formulas, it is to the extent to which these are essential for understanding and applying the underlying concepts. The presentation is friendly to readers with little to no prior knowledge in statistics. Artificial and impractical examples like dice rolling and betting are absent, instead statistical concepts are illustrated through scenarios which might well be mistaken with the last couple of A/B tests you managed.This book also doesn't shy away from the fact that much of the current statistical theory and practice in online A/B testing is misguided, misinterpreted, or misapplied. It also addresses the issue of blind copying of scientific applications without due consideration of the unique features of online business, which is widespread. The book will help you avoid these malpractices by explicitly pointing out frequent mistakes, while also helping you align your usage of statistics and experimentation with any business goals you might want to pursue.

A / B Testing

Author: Dan Siroker
Publisher: John Wiley & Sons
ISBN: 1118792416
Category : Business & Economics
Languages : en
Pages : 214

Book Description
How Your Business Can Use the Science That Helped Win the White House The average conversion rate—the rate at which visitors convert into customers—across the web is only 2%. That means it's likely that 98% of visitors to your website won't end up converting into customers. What's the solution? A/B testing. A/B testing is the simple idea of showing several different versions of a web page to live traffic, and then measuring the effect each version has on visitors. Using A/B testing, companies can improve the effectiveness of their marketing and user experience and, in doing so, can sometimes double or triple their conversion rates. Testing has been fundamental in driving the success of Google, Amazon, Netflix, and other top tech companies. Even Barack Obama and Mitt Romney had dedicated teams A/B testing their campaign websites during the 2012 Presidential race. In the past, marketing teams were unable to unleash the power of A/B testing because it required costly engineering and IT resources. Today, a new generation of technology that enables marketers to run A/B tests without depending on engineers is emerging and quickly becoming one of the most powerful tools for making data-driven decisions. Authors Dan Siroker and Pete Koomen are cofounders of Optimizely, the leading A/B testing platform used by more than 5,000 organizations across the world. A/B Testing: The Most Powerful Way to Turn Clicks Into Customers offers best practices and lessons learned from more than 300,000 experiments run by Optimizely customers. You'll learn: What to test How to choose the testing solution that's right for your organization How to assemble an A/B testing dream team How to create personalized experiences for every visitor And much more Marketers and web professionals will become obsolete if they don't embrace a data-driven approach to decision making. This book shows you how, no matter your technical expertise.

Experiment!

Author: Colin McFarland
Publisher: New Riders
ISBN: 0133040089
Category : Computers
Languages : en
Pages : 219

Book Description
Testing is a surefire way to dramatically improve your website’s conversion rate and increase revenue. When you run experiments with changes to design or content, you’ll quickly discover which changes better motivate your users to take action. This book shows how to learn from your customers’ behavior and decisions, and how their responses reveal the strengths and weaknesses of your site. It will show you how to make websites that work harder and convert better. Experiment! will inspire you to challenge assumptions and start experimenting right now. You will: Learn how to approach experiments to improve conversion Understand the various methods of testing including A/B and multivariate Discover experiment ideas, and go beyond optimization to innovation Recognize the UX and design implications of experimenting Learn to analyze data and deliver results Experimenting changes the way you think about design and the way you work. It helps prevent the loudest voice from deciding direction; instead, through an experiment, you’ll ask the most important voices--your customers--“What do you think?”

Randomization, Bootstrap and Monte Carlo Methods in Biology

Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 1000080501
Category : Mathematics
Languages : en
Pages : 338

Book Description
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors, the fourth edition of Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical methods with an emphasis on biological applications. The focus is now on the use of randomization, bootstrapping, and Monte Carlo methods in constructing confidence intervals and doing tests of significance. The text provides comprehensive coverage of computer-intensive applications, with data sets available online. Features Presents an overview of computer-intensive statistical methods and applications in biology Covers a wide range of methods including bootstrap, Monte Carlo, ANOVA, regression, and Bayesian methods Makes it easy for biologists, researchers, and students to understand the methods used Provides information about computer programs and packages to implement calculations, particularly using R code Includes a large number of real examples from a range of biological disciplines Written in an accessible style, with minimal coverage of theoretical details, this book provides an excellent introduction to computer-intensive statistical methods for biological researchers. It can be used as a course text for graduate students, as well as a reference for researchers from a range of disciplines. The detailed, worked examples of real applications will enable practitioners to apply the methods to their own biological data.

The Power of Experiments

Author: Michael Luca
Publisher: MIT Press
ISBN: 0262542277
Category : Business & Economics
Languages : en
Pages : 229

Book Description
How tech companies like Google, Airbnb, StubHub, and Facebook learn from experiments in our data-driven world—an excellent primer on experimental and behavioral economics Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of different online experiences. Once an esoteric tool for academic research, the randomized controlled trial has gone mainstream. No tech company worth its salt (or its share price) would dare make major changes to its platform without first running experiments to understand how they would influence user behavior. In this book, Michael Luca and Max Bazerman explain the importance of experiments for decision making in a data-driven world. Luca and Bazerman describe the central role experiments play in the tech sector, drawing lessons and best practices from the experiences of such companies as StubHub, Alibaba, and Uber. Successful experiments can save companies money—eBay, for example, discovered how to cut $50 million from its yearly advertising budget—or bring to light something previously ignored, as when Airbnb was forced to confront rampant discrimination by its hosts. Moving beyond tech, Luca and Bazerman consider experimenting for the social good—different ways that governments are using experiments to influence or “nudge” behavior ranging from voter apathy to school absenteeism. Experiments, they argue, are part of any leader's toolkit. With this book, readers can become part of “the experimental revolution.”