Check that the sample size is large enough:
"np(1-p)=50\\cdot0.4(1-0.4)=12\\geq10"
Sampling distribution for "\\hat{p}" is approximately normal:
"\\sigma_{\\hat{p}}=\\sqrt{\\dfrac{p(1-p)}{n}}=\\sqrt{\\dfrac{0.4(1-0.4)}{50}}\\approx0.069282"
"{21\\over 50}=0.42"
"P(\\hat{p}>0.42)=1-P(\\hat{p}\\leq0.42)="
"=1-P(Z\\leq\\dfrac{0.42-0.4}{0.069282})\\approx1-P(Z\\leq0.288675)\\approx"
"\\approx0.386415"
The probability that a simple random sample will have x > 21 having that characteristic is approximately "0.3864."
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