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 ...

We provide an interactive Excel calculator to compute power, effect size or sample size when comparing study designs or genome platforms involving different numbers of hypothesis tests.

We illustrate our testing procedures using two real data examples and provide recommendations for plant-disease researchers in the field. Published quarterly since 1996, the Journal of Agricultural, ...

A hypothesis test is where we examine the data and decide which of the two alternative hypotheses is more believable given the evidence we have. We begin by assuming the null hypothesis is true.

Most scientists use two closely related statistical approaches to make inferences from their data: significance testing and hypothesis testing.

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.

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 ...

Most statistical analyses use a sampling distribution to make inference , hence to make valid inference we also need to assume that the units of observation in our sample are independent and from a ...