"\\xi\\text{ --- "number of consecutive days of snow beginning on April 1"}\\\\\n\\xi\\in \\text{Poisson }(\\lambda), M_{\\xi}=\\lambda=0.6\\\\\nP\\{\\xi=0\\}=\\frac{(0.6)^0}{0!}e^{-0.6}\\approx 0.5488.\\\\\nP\\{\\xi=1\\}=\\frac{(0.6)^1}{1!}e^{-0.6}\\approx 0.3293.\\\\\n\\eta\\text{ --- "the amount that the insurance company will have to pay"}\\\\\nP\\{\\eta=0\\}=P\\{\\xi=0\\}\\approx 0.5488\\\\\nP\\{\\eta=1000\\}=P\\{\\xi=1\\}\\approx 0.3293\\\\\nP\\{\\eta=2000\\}=1-(P\\{\\eta=0\\}+P\\{\\eta=1000\\})\\approx 0.1219\\\\\nM_{\\eta}\\approx 0(0.5488)+1000(0.3293)+2000(0.1219)=573.1\\\\\nP\\{\\eta^2=0\\}=P\\{\\xi=0\\}\\approx 0.5488\\\\\nP\\{\\eta^2=10^6\\}=P\\{\\xi=1\\}\\approx 0.3293\\\\\nP\\{\\eta^2=4\\cdot 10^6\\}=1-(P\\{\\eta=0\\}+P\\{\\eta=1000\\})\\approx 0.1219\\\\\nM_{\\eta^2}\\approx 0(0.5488)+10^6(0.3293)+4\\cdot 10^6(0.1219)=816900\\\\\nD_{\\eta}=M_{\\eta^2}-(M_{\\eta})^2\\approx 816900-(573.1)^2=488456.39\\\\\n\\sigma_{\\eta}=\\sqrt{D_{\\eta}}\\approx \\sqrt{488456.39}\\approx 698.9\\text{ --- the standard deviation}\\\\\n\\text{of the amount that the insurance company will have to pay}."
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