Respuesta :
Answer:
[tex]z=\frac{0.37-0.303}{\sqrt{0.336(1-0.336)(\frac{1}{1100}+\frac{1}{1100})}}=3.327[/tex] .
[tex]p_v =2*P(Z>3.327)= 0.000878[/tex]
Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true proportions for this case are different so then there is enough evidence to conlcude that the real proportion change.
Step-by-step explanation:
Information provided
[tex]X_{1}=407[/tex] represent the number of people who answer abstainers in 1947
[tex]X_{2}=333[/tex] represent the number of people who answer abstainer recnetly
[tex]n_{1}=1100[/tex] sample 1 selected
[tex]n_{2}=1100[/tex] sample 2 selected
[tex]p_{1}=\frac{407}{1100}=0.37[/tex] represent the proportion estimated of people who answer abstainers in 1947
[tex]p_{2}=\frac{333}{1100}=0.303[/tex] represent the proportion estimated of people who answer abstainers recently
[tex]\hat p[/tex] represent the pooled estimate of p
z would represent the statistic
[tex]p_v[/tex] represent the p value
[tex]\alpha=0.05[/tex] significance level given
Hypothesis to test
We want to verify if the proportion of adult Americans who totally abstain from alcohol changed , the system of hypothesis would be:
Null hypothesis:[tex]p_{1} = p_{2}[/tex]
Alternative hypothesis:[tex]p_{1} \neq p_{2}[/tex]
The statistic is given by:
[tex]z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}[/tex] (1)
Where [tex]\hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{407+333}{1100+1100}=0.336[/tex]
Replacing the info given we got:
[tex]z=\frac{0.37-0.303}{\sqrt{0.336(1-0.336)(\frac{1}{1100}+\frac{1}{1100})}}=3.327[/tex]
[tex]p_v =2*P(Z>3.327)= 0.000878[/tex]
Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true proportions for this case are different so then there is enough evidence to conlcude that the real proportion change.