Respuesta :
Answer: The test statistic needed to test this claim= 10.92
Step-by-step explanation:
We know that the probability of giving birth to a boy : p= 0.5
i..e The population proportion of giving birth to a boy = 0.5
As per given , we have
Null hypothesis : [tex]H_0: p\leq0.5[/tex]
Alternative hypothesis : [tex]H_a: p>0.5[/tex]
Since [tex]H_a[/tex] is right-tailed , so the hypothesis test is a right-tailed z-test.
Also, it is given that , the sample size : n= 291
Sample proportion: [tex]\hat{p}=\dfrac{239}{291}\approx0.82[/tex]
Test statistic : [tex]z=\dfrac{\hat{p}-p}{\sqrt{\dfrac{p(1-p)}{n}}}[/tex] , where n is sample size , [tex]\hat{p}[/tex] is sample proportion and p is the population proportion.
[tex]\Rightarrow\ z=\dfrac{0.82-0.5}{\sqrt{\dfrac{0.5(1-0.5)}{291}}}\approx10.92[/tex]
i.e. the test statistic needed to test this claim= 10.92
Critical value ( one-tailed) for 0.01 significance level = [tex]z_{0.01}=2.326[/tex]
Decision : Since Test statistic value (10.92)> Critical value (2.326), so we reject the null hypothesis .
[When test statistic value is greater than the critical value , then we reject the null hypothesis.]
Thus , we concluded that we have enough evidence at 0.01 significance level to support the claim that the YSORT method is effective in increasing the likelihood that a baby will be a boy.