Answer to Question #330807 in Statistics and Probability for Tarie

Question #330807

The random variable Y = LogX has N(12,6) distribution. Find (a) The pdf of X (b) Mean and variance of X (c) P ( X ≤ 1000


1
Expert's answer
2022-04-20T09:51:04-0400

a). The pdf of "X" is a density of "X". The variable "Y=log\\,X" has a normal distribution with parameters "\\mu=12" and "\\sigma^2=6". Variable "X>0", since it appears under the function "log". Therefore, "P(X\\leq0)=0". The distribution of "X" is similar to the log-normal distribution.

We have: "P(log\\,X\\leq z)=P(Y\\leq z)=\\int_{-\\infty}^zg(y)dy," where "g(y)=\\frac{1}{\\sqrt{12\\pi}}e^{-\\frac12\\left(\\frac{y-12}{\\sqrt{6}}\\right)^2}". "P(X\\leq s)=P(log\\,X\\leq log\\,s)=\\int_{0}^{log(s)}g(y)dy". The derivative(due to the Leibniz’s Theorem) is: "f(s)=(P(X\\leq s))'=g(log(s))\\frac{1}{s\\,\\,ln(10)}=\\frac{1}{(\\sqrt{12\\pi})\\,\\,(ln(10))s}e^{-\\frac12\\left(\\frac{log(s)-12}{\\sqrt{6}}\\right)^2}".

Thus, the pdf of "X" is: "f(s)=\\frac{1}{(\\sqrt{12\\pi})\\,\\,(ln(10))s}e^{-\\frac12\\left(\\frac{log(s)-12}{\\sqrt{6}}\\right)^2}"

b). "E[X]=\\int_{0}^{+\\infty}\\frac{1}{(\\sqrt{12\\pi})\\,\\,(ln(10))}e^{-\\frac12\\left(\\frac{log(s)-12}{\\sqrt{6}}\\right)^2}ds." Make the change of variables: "x=ln(s)". Then, we receive: "s=e^x". "E[X]=\\int_{-\\infty}^{+\\infty}\\frac{e^x}{(\\sqrt{12\\pi})\\,\\,(ln(10))}e^{-\\frac12\\left(\\frac{\\frac{x}{ln(10)}-12}{\\sqrt{6}}\\right)^2}dx=e^{\\frac1{12}(a^2-144)}\\int_{-\\infty}^{+\\infty}\\frac{1}{\\,ln\\,(10)\\sqrt{6\\pi}\\,\\,}e^{-\\frac12\\left({\\frac{x-a\\,ln(10)}{\\sqrt{6}\\,ln(10)}}\\right)^2}dx,"

where "a=6\\,ln(10)+3". The last integral is equal to "1" (it becomes the Gaussian integral after simple changes). Thus, we get: "E[X]=e^{\\frac1{12}((6\\,ln(10)+3)^2-144)}".

"Var[X]=E[X^2]-(E[X])^2".

"E[X^2]=\\int_{0}^{+\\infty}\\frac{s}{(\\sqrt{12\\pi})\\,\\,(ln(10))}e^{-\\frac12\\left(\\frac{log(s)-12}{\\sqrt{6}}\\right)^2}ds." Make the change "s=e^x". We get: "E[X^2]=\\int_{-\\infty}^{+\\infty}\\frac{e^{2x}}{(\\sqrt{12\\pi})\\,\\,(ln(10))}e^{-\\frac12\\left(\\frac{\\frac{x}{ln(10)}-12}{\\sqrt{6}}\\right)^2}dx=e^{\\frac1{12}(b^2-144)}\\int_{-\\infty}^{+\\infty}\\frac{1}{\\,ln\\,(10)\\sqrt{12\\pi}\\,\\,}e^{-\\frac12\\left({\\frac{x-b\\,ln(10)}{\\sqrt{6},ln(10)}}\\right)^2}dx,"

where "b=12\\,ln(10)+3." Thus, "Var[X]=e^{\\frac1{12}((12\\,ln(10)+3)^2-144)}-e^{\\frac1{6}((6\\,ln(10)+3)^2-144)}".

We received: "E[X]=e^{\\frac1{12}((6\\,ln(10)+3)^2-144)}", "Var[X]=e^{\\frac1{12}((12\\,ln(10)+3)^2-144)}-e^{\\frac1{6}((6\\,ln(10)+3)^2-144)}"

c). "P(X\\leq1000)=\\int_{0}^{1000}\\frac{1}{(\\sqrt{12\\pi})\\,\\,(ln(10))s}e^{-\\frac12\\left(\\frac{log(s)-12}{\\sqrt{6}}\\right)^2}ds\\approx0.0001" (it is rounded to 4 decimal places)


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