STA 210 Lecture Notes - Lecture 7: Statistical Significance, Null Hypothesis, Statistical Hypothesis Testing

• School: University of Kentucky
• Department: Statistics
• Course: STA 210
• Professor: Jeff Modenbach

Document Summary

The goal of a hypothesis testing is to choose between: To understand how to make an informed choice, it helps to understand how hypothesis testing is similar to a screening test. Think of ho as a negative outcome and ha as a positive outcome . A false positive is when the results from a hypothesis test suggest that ha is true, when in fact ho is true. It is called a type 1 error in statistical science. A false negative is when the results from the hypothesis test suggest that ho is true, when in fact ha is true. It is called type 2 error in statistical science. Hypothesis testing amounts to a screening test that chooses between a null hypothesis and alternative hypothesis based on a rule dictated by the type 1 error rate. Significance in the statistical sense does not mean important. it means not likely to happen by chance .