Risk of Errors

Definition

The risk of errors refers to the two types of errors that can occur in statistical hypothesis testing - Type I error and Type II error. Type I error happens when we reject a true null hypothesis, while Type II error happens when we fail to reject a false null hypothesis.

Related terms

Power: Power refers to our ability to correctly reject a false null hypothesis (avoiding a Type II error).

Critical Region: Also known as rejection region, this is the range of values that would lead us to reject the null hypothesis.

Null Hypothesis: This is the assumption we start with, usually stating that there is no significant difference or relationship between variables.