Let \({\rm{X}}\) be the total medical expenses (in \({\rm{1000}}\) s of dollars) incurred by a particular individual during a given year. Although \({\rm{X}}\) is a discrete random variable, suppose its distribution is quite well approximated by a continuous distribution with pdf \({\rm{f(x) = k(1 + x/2}}{\rm{.5}}{{\rm{)}}^{{\rm{ - 7}}}}\) for.
a. What is the value of\({\rm{k}}\)?
b. Graph the pdf of \({\rm{X}}\).
c. What are the expected value and standard deviation of total medical expenses?
d. This individual is covered by an insurance plan that entails a \({\rm{\$ 500}}\) deductible provision (so the first \({\rm{\$ 500}}\) worth of expenses are paid by the individual). Then the plan will pay \({\rm{80\% }}\) of any additional expenses exceeding \({\rm{\$ 500}}\), and the maximum payment by the individual (including the deductible amount) is\({\rm{\$ 2500}}\). Let \({\rm{Y}}\) denote the amount of this individual's medical expenses paid by the insurance company. What is the expected value of\({\rm{Y}}\)?
(Hint: First figure out what value of \({\rm{X}}\) corresponds to the maximum out-of-pocket expense of \({\rm{\$ 2500}}\). Then write an expression for \({\rm{Y}}\) as a function of \({\rm{X}}\) (which involves several different pieces) and calculate the expected value of this function.)