Statistical testing in Python offers a way to make sure your data is meaningful. It only takes a second to validate your data ...

This article reviews important concepts and methods that are useful for hypothesis testing. First, we discuss the Neyman-Pearson framework. Various approaches to optimality are presented, including ...

In the realm of technical product development, hypothesis testing acts as a bridge between design, data and decision-making. It enables teams to move beyond assumptions and validate their ideas ...

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 ...

Rob Herbert does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...

Consider the problem of testing k hypotheses simultaneously. In this article we discuss finite- and large-sample theory of stepdown methods that provide control of ...

In applied research, an effect size is specified in advance and defines a threshold for decision-making. Power analyses of a specific desired effect size may then be carried out before an experiment ...

Students will conduct an experiment in order to determine the origin of a family artifact. Students will determine whether the results from an experiment successfully determined the origin of a family ...