"\\xi\\text{ --- random variable (random value of height)}.\\\\\nP\\{\\xi\\geq 62\\}=1-P\\{\\xi<62\\}=1-F(62)=\\\\=1-\\Phi(\\frac{62-70}{5.3})=\n1-\\Phi(-1.509)=1-0.0656=0.9344.\\\\\nF(x)=\\frac{1}{{(5.3)}\\sqrt{2\\pi}}\\int_{-\\infty}^x e^{-\\frac{(t-70)^2}{2\\cdot({5.3})^2}}dt.\\\\\n\\Phi(x)=\\frac{1}{\\sqrt{2\\pi}}\\int_{-\\infty}^{x} e^{-\\frac{t^2}{2}}dt.\\\\\n\\mu_{\\overline{p}}=P\\text{ (mean of sample proportions equals population proportion)}.\\\\\n\\text{So we have a) }(0.9344)\\cdot 900\\approx 840.\\\\\nb) P\\{68\\leq\\xi\\leq 75\\}=F(75)-F(68)=\\Phi(\\frac{75-70}{5.3})-\\Phi(\\frac{68-70}{5.3})\\approx \\\\ \\approx \\Phi(0.943)-\\Phi(-0.377)\\approx 0.8272-0.3531=0.4741.\\\\\n\\text{So we have } P=(0.4741)\\cdot 900\\approx 426.\\\\\nc) P\\{\\xi<74\\}=F(74)=\\Phi(\\frac{74-70}{5.3})=\\Phi(0.755)=0.7749.\\\\\n\\text{So we have } P=(0.7749)\\cdot 900\\approx 697.\\\\\nd) P\\{\\xi>t\\}=0.35.\\\\\n\\text{We should find }t.\\\\\nP\\{\\xi>t\\}=1-P\\{\\xi\\leq t\\}=0.35.\\\\\nP\\{\\xi\\leq t\\}=0.65.\\\\\n\\Phi(\\frac{t-70}{5.3})=0.65.\\\\\n\\frac{t-70}{5.3}=0.39.\\\\\nt\\approx 72."
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