Because this sample meets the "np=400(0.08)=32>10" and "n(1-p)=400(1-0.08)" "=368>10" conditions, we can assume it is approximately normal.
The following null and alternative hypotheses for the population proportion needs to be tested:
"H_0: p=0.8"
"H_1: p\\not=0.8"
This corresponds to a two-tailed test, for which a z-test for one population proportion will be used.
Based on the information provided, the significance level is "\\alpha=0.15," and the critical value for a two-tailed test is "z_c=1.4395."
The rejection region for this two-tailed test is "R=\\{z:|z|>1.4395\\}."
The z-statistic is computed as follows:
"\\approx1.1058"
Since it is observed that "|z|=1.1058<1.4395=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>1.1058)=0.2688," and since "p=0.2688>0.15=\\alpha," it is concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population proportion "p" is different than "0.08," at the "\\alpha=0.15" significance level.
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Nice answer
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