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.

Learn how two-tailed tests determine statistical significance in hypothesis testing by evaluating if a sample differs from a population mean. Discover real-world applications.

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.

The sample mean amount due was $280, with a sample standard deviation of $120. Taking the statement to be evaluated as “the true mean amount due is at least $300,” you determine (click here to see how ...

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, ...

Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously. This poses new difficulties ...