Let X be a continuous random variable with values uniformly distributed over the interval [0, 20]. (a) Find the mean and variance of X. (b) \(P(|X - 10| \ge 2)\), \(P(|X - 10| \ge 5)\), \(P(|X - 10| \ge 9)\) and \(P(|X - 10| \ge 20)\) exactly. How do your answers compare with those of Exercise 1? How good is Chebyshev’s Inequality in this case?
\(E(X)={(a+b)}/2\)
\(Var(X)={(b - a)^2}/12\)
So Mean \(E(X)\) is :
print((0+20)/2)## [1] 10
and Variance \(Var(X)\) is :
print(((20-0)**2)/12)## [1] 33.33333
=\(1-P(-2 \lt (X -10) \lt 2)\)
=\(1-P(-2+10 \lt X \lt 2 +10)\)
=\(1-P(8 \lt X \lt 12)\)
=\(1-[P(X \lt 12) - P(X \le 8)]\)
=\(1-[12/20 - 8/20]\)
print(1-((12/20) - (8/20)))## [1] 0.8
\(P(|X - 10| \ge 5)\)
=\(1-P(|X - 10| \lt 5)\)
=\(1-P(-5 \lt (X-10) \lt 5)\)
=\(1-P(-5+10 \lt X \lt 5+10)\)
=\(1-P(5 \lt X \lt 15)\)
=\(1-[P(X \lt 15) - P(X \le 5)]\)
print(1-((15/20) - (5/20)))## [1] 0.5
\(P(|X - 10| \ge 9)\)
=\(1-P(|X - 10| \lt 9)\)
=\(1-P(-9 \lt (X-10) \lt 9)\)
=\(1-P(-9+10 \lt X \lt 9+10)\)
=\(1-P(1 \lt X \le 19)\)
=\(1-[P(X \lt 19) - P(X \le 1)]\)
print(1-((19/20) - (1/20)))## [1] 0.1
\(P(|X - 10| \ge 20)\)
=\(1-P(|X - 10| \lt 20)\)
=\(1-P(-20 \lt (X-10) \lt 20)\)
=\(1-P(-20+10 \lt X \lt 20+10)\)
=\(1-P(-10 \lt X \le 30)\)
=\(1-P(0 \lt X \le 20)\)
=\(1-1\)
print(1-1)## [1] 0
How do your answers compare with those of Exercise 1? How good is Chebyshev’s Inequality in this case?
Answer :
From problem 1 :
Chebyshev estimates are in general not very accurate. We see variance for \(\epsilon=2, 5, 9, 20\)