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Oduvanchick [21]
3 years ago
15

In October 1947, the Gallup organization surveyed 1100 adult Americans and asked "Are you a total abstainer from, or do you on o

ccasion consume alcoholic beverages?". Of the 1100 adults surveyed, 407 indicated that they were total abstainers. In a recent survey, the same question was asked of 1100 adult Americans and 333 indicated that they were total abstainers. Has the proportion of adult Americans who totally abstain from alcohol changed? Use the ???? = 0.05 level of significance. (use the traditional method of hypothesis testing)
Mathematics
1 answer:
Rasek [7]3 years ago
6 0

Answer:

z=\frac{0.37-0.303}{\sqrt{0.336(1-0.336)(\frac{1}{1100}+\frac{1}{1100})}}=3.327 .  

p_v =2*P(Z>3.327)= 0.000878    

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

X_{1}=407 represent the number of people who answer abstainers in 1947

X_{2}=333 represent the number of people who answer abstainer recnetly

n_{1}=1100 sample 1 selected  

n_{2}=1100 sample 2 selected  

p_{1}=\frac{407}{1100}=0.37 represent the proportion estimated of people who answer abstainers in 1947

p_{2}=\frac{333}{1100}=0.303 represent the proportion estimated of people who answer abstainers recently

\hat p represent the pooled estimate of p

z would represent the statistic

p_v represent the p value

\alpha=0.05 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:p_{1} = p_{2}    

Alternative hypothesis:p_{1} \neq p_{2}    

The statistic is given by:

z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}   (1)  

Where \hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{407+333}{1100+1100}=0.336  

Replacing the info given we got:    

z=\frac{0.37-0.303}{\sqrt{0.336(1-0.336)(\frac{1}{1100}+\frac{1}{1100})}}=3.327    

p_v =2*P(Z>3.327)= 0.000878    

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.

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