Chebyshev's inequality:
Let "X" is our random variable.
"MX^2={1 \\over 6}(1^2+2^2+3^2+4^2+5^2+6^2)={91 \\over 6}"
"DX=MX^2-(MX)^2"
"DX={91 \\over 6}-({7 \\over 2})^2={35 \\over 12}"
"\\sigma_x=\\sqrt{DX}=\\sqrt{{35 \\over 12}}"
"k\\sigma_X=2.5=>k={2.5 \\over \\sqrt{{35 \\over 12}}}=\\sqrt{{15 \\over 7}}\\approx1.463850"
"{1 \\over k^2}={7 \\over 15}\\approx0.4667<0.47"
Hence if "X" is the number scored in a throw of a fair die, then the Chebychev’s inequality gives
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