Final conclusion would be: for couples using the XSORT the likelihood of having a baby girl is indeed equal to 0.5 Final conclusion would be: for couples using the XSORT, the likelihood of having a baby girl is not 0.5 If we fail to reject the null hypothesis, then the original clam is accepted.
11 Example 2 (continued) If we reject the null hypothesis, then the original clam is rejected. 10 Example 2 Claim: for couples using the XSORT method the likelihood of having a baby girl is 50% Express this claim in symbolic form: p=0.5 (again p denotes the proportion of baby girls) Null hypothesis must say equal to, so H 0 : p=0.5 Alternative hypothesis must express difference: H 1 : p 0.5 Original claim is now the null hypothesis. Final conclusion would be: XSORT method does not increase the likelihood of having a baby girl. If we fail to reject the null hypothesis, then the original clam is rejected. Final conclusion would be: XSORT method increases the likelihood of having a baby girl. If we reject the null hypothesis, then the original clam is accepted. 
9 Example 1 (continued) We always test the null hypothesis. 
We express this claim in symbolic form: p>0.5 (here p denotes the proportion of baby girls) Null hypothesis must say equal to, so H 0 : p=0.5 Alternative hypothesis must express difference: H 1 : p>0.5 Original claim is now the alternative hypothesis
8 Example 1 Claim: the XSORT method of gender selection increases the likelihood of having a baby girl. The symbolic form of the alternative hypothesis must use one of these symbols. 7 Alternative Hypothesis: H 1 The alternative hypothesis (denoted by H 1 ) is the statement that the parameter has a value that somehow differs from the null hypothesis. Either reject H 0 or fail to reject H 0 (in other words, accept H 0 ). 6 Null Hypothesis: H 0 The null hypothesis (denoted by H 0 ) is a statement that the value of a population parameter (such as proportion, mean, or standard deviation) is equal to some claimed value. 5 Components of a Formal Hypothesis Test. 4 Rare Event Rule for Inferential Statistics If, under a given assumption, the probability of a particular observed event is exceptionally small, we conclude that the assumption is probably not correct. 
If 13 or 14 couples have girls, the method is probably increases the likelihood of a girl. If 6 or 7 or 8 have girls, the method probably does not increase the likelihood of a girl. This is a claim about proportion (of girls) To test this claim 14 couples (volunteers) were subject to XSORT treatment. 3 Example Claim: the XSORT method of gender selection increases the likelihood of having a baby girl.2 Main Objectives We will study hypothesis testing for 1.A hypothesis test is a standard procedure for testing a claim about a property of a population. 1 Definitions In statistics, a hypothesis is a claim or statement about a property of a population.
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