Chapter 5: Q33E (page 220)
Show that when \({\rm{X}}\) and \({\rm{Y}}\) are independent, \({\rm{Cov(X,Y) = Corr(X,Y) = 0}}\).
Short Answer
\({\rm{X}}\) and \({\rm{Y}}\) are independent when \({\rm{Cov(X,Y) = 0}}\).
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Chapter 5: Q33E (page 220)
Show that when \({\rm{X}}\) and \({\rm{Y}}\) are independent, \({\rm{Cov(X,Y) = Corr(X,Y) = 0}}\).
\({\rm{X}}\) and \({\rm{Y}}\) are independent when \({\rm{Cov(X,Y) = 0}}\).
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Refer to Exercise \({\rm{46}}\). Suppose the distribution is normal (the cited article makes that assumption and even includes the corresponding normal density curve).
a. Calculate \({\rm{P}}\)(\(69\text{拢}\bar{X}\text{拢}71\)) when \({\rm{n = 16}}\).
b. How likely is it that the sample mean diameter exceeds \({\rm{71}}\) when \({\rm{n = 25}}\)?
Consider a small ferry that can accommodate cars and buses. The toll for cars is\({\rm{\$ 3}}\), and the toll for buses is\({\rm{\$ 10}}\). Let \({\rm{X}}\) and \({\rm{Y}}\) denote the number of cars and buses, respectively, carried on a single trip. Suppose the joint distribution of \({\rm{X}}\) and\({\rm{Y}}\). Compute the expected revenue from a single trip.
Exercise introduced random variables X and Y, the number of cars and buses, respectively, carried by ferry on a single trip. The joint pmf of X and Y is given in the table in Exercise. It is readily verified that X and Y are independent.
a. Compute the expected value, variance, and standard deviation of the total number of vehicles on a single trip.
b. If each car is charged\(\$ {\bf{3}}\)and each bus\(\$ {\bf{10}}\), compute the expected value, variance, and standard deviation of the revenue resulting from a single trip.
There are \({\rm{40}}\) students in an elementary statistics class. On the basis of years of experience, the instructor knows that the time needed to grade a randomly chosen first examination paper is a random variable with an expected value of \({\rm{6}}\)min and a standard deviation of \({\rm{6}}\)min.
a. If grading times are independent and the instructor begins grading at \({\rm{6:50}}\) p.m. and grades continuously, what is the (approximate) probability that he is through grading before the \({\rm{11:00}}\) p.m. TV news begins?
b. If the sports report begins at \({\rm{11:10,}}\) what is the probability that he misses part of the report if he waits until grading is done before turning on the TV?
I have three errands to take care of in the Administration Building. Let \({\rm{Xi = }}\)the time that it takes for the \({\rm{ ith}}\)errand\({\rm{(i = 1,2,3)}}\), and let \({{\rm{X}}_{\rm{4}}}{\rm{ = }}\)the total time in minutes that I spend walking to and from the building and between each errand. Suppose the \({\rm{Xi`s}}\)are independent, and normally distributed, with the following means and standard deviations: \({{\rm{\mu }}_{{{\rm{X}}_{\rm{1}}}}}{\rm{ = 15,}}{{\rm{\sigma }}_{{{\rm{X}}_{\rm{1}}}}}{\rm{ = 4,}}{{\rm{\mu }}_{{{\rm{X}}_{\rm{2}}}}}{\rm{ = 5,}}{{\rm{\sigma }}_{{{\rm{X}}_{\rm{2}}}}}{\rm{ = 1,}}{{\rm{\mu }}_{{{\rm{X}}_{\rm{3}}}}}{\rm{ = 8,}}{{\rm{\sigma }}_{{{\rm{X}}_{\rm{3}}}}}{\rm{ = 2,}}{{\rm{\mu }}_{{{\rm{X}}_{\rm{4}}}}}{\rm{ = 12,}}{{\rm{\sigma }}_{{{\rm{X}}_{\rm{4}}}}}{\rm{ = 3}}\).plan to leave my office at precisely \({\rm{10:00}}\)a.m. and wish to post a note on my door that reads, 鈥淚 will return by \({\rm{t}}\)a.m.鈥 What time\({\rm{t}}\)should I write down if I want the probability of my arriving after \({\rm{t}}\) to be \({\rm{.01}}\)?
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