Google

In the logic of null hypothesis testing, researchers reject the null hypothesis in favor of the alternative hypothesis if they determine that the observed sample relationship would be extremely unlikely to occur if the null hypothesis were actually true. This formal decision indicates that the sample data provides sufficient statistical evidence to conclude that a genuine relationship exists within the broader population.

Rejecting the Null Hypothesis

A Type I error is a false positive in null hypothesis testing. It occurs when a researcher mistakenly concludes that their results are statistically significant—thereby rejecting the null hypothesis—when, in reality, the null hypothesis is true and there is no actual relationship in the population. These errors happen because random sampling error can occasionally produce extreme results even when no true effect exists. The predetermined alpha level dictates the probability of committing this error when the null hypothesis is true.

Type I Error

In the logic of null hypothesis testing, what formal decision indicates that the sample data provides sufficient statistical evidence to conclude that a genuine relationship exists within the broader population?

Learn Before

Related