EC255 Chapter Notes - Chapter 9: Type I And Type Ii Errors, Null Hypothesis, Statistical Hypothesis Testing
Document Summary
Learning objectives: understand logic of hypothesis testing, establish null and alternative hypotheses, understand type 1 and 2 errors, know and implement methods for testing hypotheses. Test for hypotheses when deviation and variance is known and unknown. Estimation: hypothesis testing, test the validity of statements about an unknown population parameter based on a random sample. Type one error: rejecting a true null hypothesis, considered a serious type error. The probability of committing a type i error is , the level of significance. The probability of committing a type ii error is : is a calculated value. There are two hypotheses: null (h0) and alternative (ha) The procedure begins by assuming h0 is true. The goal is to determine whether there is enough evidence to infer that ha is true. There are two possible decisions: conclude there is enough evidence to support ha, conclude there is not enough evidence to support ha. Type ii error: do not reject a false h0.
