In the early 20 th century, Guinness breweries in Dublin had a policy of hiring the best graduates from Oxford and Cambridge to improve their industrial processes. At the time, it was considered a ...

Basic concepts in hypothesis testing, including effect sizes, type I and type II errors, calculation of statistical power, non-centrality parameter, and applications of these concepts to twin studies.

Christina Majaski writes and edits finance, credit cards, and travel content. She has 14+ years of experience with print and digital publications. Khadija Khartit is a strategy, investment, and ...

During his Ph.D. research, mathematician Tyron Lardy worked on a new approach to hypothesis testing. Instead of the traditional p-value, he uses so-called e-values. These turn out to be more ...

In this module, we will introduce the basic conceptual framework for experimental design and define the models that will allow us to answer meaningful questions about the differences between group ...

Statistical significance is a critical concept in data analysis and research. In essence, it’s a measure that allows researchers to assess whether the results of an experiment or study are due to ...

Distributed hypothesis testing (DHT) and source coding are interrelated domains that address the challenges of reliable communication and decision-making in networked systems. In DHT, multiple nodes ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...