Chapter 21 Flashcards
Alpha Level
The threshold P-value that determines when we reject a null hypothesis. If we observe a statistic whose P-value based on the null hypothesis is less than alpha , we reject that null hypothesis.
Statistically Significant
When the P-value falls below alpha level, we say that the test is “statistically significant” at that alpha level.
Significance Level
The alpha level is also called the significance level, most often in a phrase such as a conclusion that a particular test is “significant at the 5% significance level.”
Type I Error
The error of rejecting a null hypothesis when it is in fact true (also called a “false positive”). The probability of a Type I Error is alpha.
Type II Error
The error of failing to reject a null hypothesis when in fact it is false (also called a “false negative”). The probability of a Type II Error is commonly denoted as beta and depends on the efect size.
Power
The probability that a hypothesis test will correctly reject a false null hypothesis is the power of the test. To find power, we must specify a particular alternative parameter value as the “true” value. For any specific value in the alternative, the power is 1-beta.
Effect Size
The difference between the null hypothesis value and tru value of a model parameter is called the effect size.