STAT 301 Study Guide - Midterm Guide: Type I And Type Ii Errors, Statistical Hypothesis Testing, Test Statistic
Document Summary
= p(type i error) (level of significance) After assessing the consequences of type i and type ii errors, we identify the largest that is tolerable for the problem. We then employ a test procedure that uses as the maximum acceptable type i error rate. Generally, with everything else held constant, decreasing one type of error increases the other. The only way to decrease both types of errors is to increase the sample size. No matter what decision is reached through a hypothesis test, there is always the risk of one of these errors. Test statistic a numeric function of sample data on which a conclusion to reject or fail to reject h0 is based. P-value the probability of obtaining a test statistic as extreme or more extreme than the one calculated, assuming h0 is true. A decision to reject h0 is found by comparing the p-value to . If p-value > , h0 is not rejected.
