Today our goal is to cover hypothesis testing and the basic z-test, as these are fundamental to understanding how the t-test works. We’ll return to the t-test soon — with real data.

A Tutorial In T-Tests and ANOVA using JMP A Tutorial In T-Tests and ANOVA using JMP Course Topics This short course provides an overview of statistical analyses useful for comparing the means for one ...

Hypothesis testing is a procedure for evaluating the strength of a hypothesis. The methodology depends on the data and the reason for the analysis.

Specialization: Data Science Foundations: Statistical InferenceInstructor: Dr. Jem Corcoran, Associate Professor in Applied MathematicsPrior knowledge ...

Statistical hypothesis testing is used to determine whether the result of a data set is statistically significant. A p-value of 5% or lower is generally considered statistically significant.

This article explores the concept of statistical hypothesis testing, its process, and how organizations can leverage it to make better business decisions. We’ll also examine real-world examples ...

Despite their wide use in scientific journals such as The Journal of Wildlife Management, statistical hypothesis tests add very little value to the products of research. Indeed, they frequently ...

This paper presents a review and critique of statistical null hypothesis testing in ecological studies in general, and wildlife studies in particular, and describes an alternative. Our review of ...