The manufacturer of a certain kind of light bulb claims that the lifetime of the bulb in hours, X can be modeled as a random quantity with PDF.
fX(x)=0,c/x^2
x< 100
x> 100, where e is a constant. i. What value must e take in order for this to define a valid PDF? ii. What is the probability that the bulb lasts no longer than 150 hours? ii. Given that a bulb lasts longer than 150 hours, what is the probability that it lasts longer than 200 hours? Evaluate the cumulative distribution function.
"i)"
"\\int_{-\\infty}^{\\infty} f(x)dx=c\\int_{100}^{\\infty}{\\frac 1 {x^2}}dx=-c\\times{\\frac 1 x}|_{100}^{\\infty}={\\frac c {100}}=1\\implies c=100"
"ii)"
(ii) "P(X<150)=100\\int_{100}^{150}{\\frac 1 {x^2}}dx=-100\\times{\\frac 1 x}|_{100}^{150}=-100({\\frac 1 {150}}-{\\frac 1 {100}})={\\frac 1 3}"
"iii)"
"P(X<200|X>150)={\\frac {P(150<X<200)} {P(X>150)}}"
"P(X>150)=1-P(X<150)=1-{1\\over3}={\\frac 2 3}"
"P(150<X<200)=100\\int_{150}^{200}{\\frac 1 {x^2}}dx=-100\\times{\\frac 1 x}|_{150}^{200}=-100\\times({\\frac 1 {200}}-{\\frac 1 {150}})={\\frac 1 6}"
So,
"P(X<200|X>150)={\\frac {{\\frac 1 6}} {\\frac 2 3}}={1\\over4}"
"iv)"
Let F(x) be a cumulative distribution function, then "F(x)=\\int_{-\\infty}^x f(t)dt".
So, "F(x) = 0" when "x < 100" and,
"F(x)=100\u222b ^{\nx}_\n{100}\n\u200b{1\\over\n \nt^ \n2}\n \n\u200b\n dt=\u2212100\\times{1\\over \nt\n}\n\u200b\n \u2223 ^{\nx}_\n{100}\n\u200b\n =1\u2212 \n{100\\over x}\n\u200b" when "x \\ge100"
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