About the Creator
Carrie Grimes
Carrie Grimes Bostock graduated from Harvard with an A.B. in Anthropology/Archaeology in 1998, and an interest in quantitative methods for dealing with disparate data. She graduated from Stanford in 2003 with a PhD in Statistics after working with David Donoho on Nonlinear Dimensionality Reduction problems, and has been at Google since mid-2003. Dr. Grimes spent many years leading a research and technical team in Search at Google trying to figure out what criteria make a search engine index "good," "fast," and "comprehensive" - and how to achieve those goals. Currently, she is the Technical Lead for resource planning, pricing, and management data/software in Technical Infrastructure.
Who is this course for
Aspiring data analysts and product managers seeking to understand the fundamentals of A/B testing.
Professionals in tech who want to enhance their ability to make data-driven decisions.
Entrepreneurs and marketers interested in optimizing user experiences and business outcomes through experimentation.
Students and beginners with no prior experience who want to learn about online experimentation techniques.
Anyone curious about how companies like Google, Amazon, and Netflix use A/B testing to improve their products and services.
Overview
This course will cover the design and analysis of A/B tests, which are online experiments used throughout tech industry by companies like Google, Amazon, and Netflix.This course offers a comprehensive introduction to the design and analysis of A/B testing, an essential method for conducting online experiments widely used in the tech industry by companies such as Google, Amazon, and Netflix. Aimed at beginners, this course covers the fundamentals of A/B testing, from understanding what A/B tests are and their applications, to the ethical considerations, metric selection, experiment design, and result analysis. By the end of the course, learners will be equipped with the knowledge to design and analyze their own A/B tests, making data-driven decisions to optimize user experiences and business outcomes.
Course Highlights:
Introduction to A/B Testing: Understand the concept of A/B testing, its significance in the tech industry, and how it can be used to drive decisions and improvements.
Policy and Ethics in Experimentation: Learn the importance of ethical considerations in experiments and how to protect participants while ensuring the integrity of the test.
Selecting and Validating Metrics: Gain insights into choosing the right metrics for your experiment, ensuring they are reliable and valid for measuring success.
Experiment Design: Explore the process of designing an effective A/B test, including the creation of control and variation groups, randomization, and minimizing biases.
Result Analysis: Dive into the methods for analyzing the results of A/B tests, interpreting data correctly, and making informed decisions based on your findings.
Final Project: Apply your knowledge by working on a final project that includes designing an A/B test, analyzing the results, and completing quizzes to verify your understanding of the quantitative aspects of testing.