In a study to estimate the proportion of smokers among the residents in a certain city and its suburbs, it is found that 24 of 104 urban residents are smokers, while 34 of 108 suburban residents are smokers.
The value of the pooled proportion is computed as
The following null and alternative hypotheses for the population proportion needs to be tested:
"H_0:p_1=p_2"
"H_a:p_1\\not=p_2"
This corresponds to a two-tailed test, and a z-test for two population proportions will be used.
Based on the information provided, the significance level is "\\alpha = 0.05," and the critical value for a two-tailed test is"z_c = 1.96."
The rejection region for this two-tailed test is "R = \\{z: |z| > 1.96\\}."
The z-statistic is computed as follows:
"=\\dfrac{\\dfrac{24}{104}-\\dfrac{34}{108}}{\\sqrt{\\dfrac{29}{106}(1-\\dfrac{29}{106})(1\/104+1\/108)}}"
"=-1.380342"
Since it is observed that "|z| = 1.380342 \\le 1.96=z_c ," it is then concluded that the null hypothesis is not rejected.
Using the P-value approach:
The p-value is "p=2P(Z<-1.380342)=0.167481," and since "p=0.167481>0.05=\\alpha," it is concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population proportion "p_1" is different than "p_2," at the "\\alpha = 0.05" significance level.
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