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

Key Points Hypothesis testing provides organizations with a structured approach to evaluate assumptions using data, reducing ...

We will learn to identify when hypothesis tests based on these distributions are appropriate. We will review the concept of sample variance and derive the “t-test”. Additionally, we will derive our ...

Standard 21.4: Understands and applies basic principles of hypothesis testing and scientific inquiry Presents alternative explanations and conclusions to one's own experiments and those of others.

A one-tailed hypothesis test, on the other hand, is set up to show only one test; that the sample mean would be higher than the population mean, or, in a separate test, that the sample mean would ...

For multiple hypothesis testing in genomics and other large-scale data analyses, the independent hypothesis weighting (IHW) approach uses data-driven P-value weight assignment to improve power ...

Standard 21.4: Understands and applies basic principles of hypothesis testing and scientific inquiry Presents alternative explanations and conclusions to one's own experiments and those of others.