MBA统计学第7章解析全文阅读.pptx

This is another issue of statistical inference, f on getting the conclusion of “Yes ” or “No ”. Background： • After improving technology, does the average product size change significantly? • After improving technology, whether the product is stable or not? • Is the qualified rate up to the standard? • Does the life of the product follow the normal distribution? Etc. 1 Chapter 7 Hypothesis Tests (p156) ➢ Its theoretical base is the principle of small probability : In one experiment, the event with small probability hardly happens. Example ： H0 ： = 0=200mm, H1 : 0=200mm It is known that the population X follows N（ , 。2) ， if H0 is tenable ， then we get The Idea of Hypothesis Tests i . e . it appears with a large probability . The opposite event appears with a small probability . After sampling , compute : 2 If ， then there is no contradiction. If the opposite appears ， then it is proved tha the event with small probability happens in one experiment, which contradicts with the princip of small probability and proves that H0 is wrong za/2 Critical value 3 Hypothesis Tests Steps for Hypothesis Tests Select the test statistic 4 ➢ If the statistic is larger than the critical reject H0. ➢ If the statistic is smaller than the critical accept H0. ➢ If the statistic equals to the critical value enlarge the sample size, and make a retesting. Hypothesis Tests 5 When H0 is true, H0 may be rejected (caused by stochastic factors),we call this k of error Rejecting Truth Error. From the prior formula we can know, this kind of probability is“, it is also called Type 1 Error or Supplie Risk. When H0is false, H0 may be accepted (caused by stochastic factors),we call this k of error Accepting Falseness Error. Its , it is also called Type 2 Err 6 Two Types of Errors (P159) probability is or User Risk. In general, we control“ in most time， our lecture does not cover the computing value of . (If the sample s