Chebyshev's inequality:
"P\\{|X-\\mu|\\geq k\\sigma\\}\\leq\\frac{1}{k^2}, k\\in R."
Let X is our random variable.
"MX=\\frac{1}{6}(1+2+3+4+5+6)=3.5.\\\\\nMX^2=\\frac{1}{6}(1^2+2^2+3^2+4^2+5^2+6^2)=\\frac{91}{6}.\\\\\nDX=MX^2-(MX)^2=\\frac{91}{6}-(3.5)^2.\\\\\n\\sigma X=\\sqrt{\\frac{91}{6}-(3.5)^2}.\\\\\nk\\sigma X=2.5.\\\\\nk=\\frac{2.5}{\\sqrt{\\frac{91}{6}-(3.5)^2}}\\approx 1.46385.\\\\\n\\frac{1}{k^2}\\approx 0.4666."
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