Given "n=400, p=0.25, q=1-p=1-0.25=0.75."
"np=400(0.25)=100\\geq10, nq=400(0.75)=300\\geq10"
Then "\\hat{p}" has approximately a normal distribution with "\\mu_{\\hat{p}}=p=0.25" and "\\sigma_{\\hat{p}}=\\sqrt{\\dfrac{pq}{n}}=\\sqrt{\\dfrac{0.25(0.75)}{400}}=\\dfrac{\\sqrt{3}}{80}."
Then
"\\approx P(Z<-3.23316)\\approx0.000612"
The sample proportion is computed as follows, based on the sample size "N = 400" and the number of favorable cases "X = 152:"
The critical value for "\\alpha = 0.1" is "z_c = z_{1-\\alpha\/2} = 1.6449."
The corresponding confidence interval is computed as shown below:
"\\hat{p}+z_c\\sqrt{\\dfrac{\\hat{p}(1-\\hat{p})}{n}})"
"=(0.38-1.6449\\sqrt{\\dfrac{0.38(1-0.38)}{400}},"
"0.38+1.6449\\sqrt{\\dfrac{0.38(1-0.38)}{400}})"
"=(0.34, 0.42)"
Therefore, based on the data provided, the "90\\%" confidence interval for the population proportion is "0.34 < p < 0.42," which indicates that we are "90\\%" confident that the true population proportion "p" is contained by the interval "(0.34, 0.42)."
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