A survey of passengers on domestic flights revealed these miles:Miles Flown Number of Passengers100 - 49916500 - 89941900 - 1299811300 - 1699111700 - 209992100 - 24996What is the range (in miles)?
Answer(s): D
2499 - 100 = 2399
The coefficient of variation is useful when:
The coefficient of variation is useful when the means of the data sets are widely different or when the observations are in different measurement units.
If you buy an item for $475 and agree to pay for it with 24 monthly payments of $22.50, beginning next month, what annual interest rate, compounded monthly, are you being charged?
Answer(s): C
The interest rate returned by the calculator will be the periodic interest rate. It must be multiplied by the number of periods per year to have the correct answer. On the BAII Plus, press 24 N, 475 PV, 22.50 +/- PMT, 0 FV, CPT I/Y. Then press x 12 = to see the answer. On the HP12C, press 24 n, 475 PV, 22.50 CHS PMT, 0 FV, i.Then press 12 x to see the answer. Make sure the BAII Plus has the P/Y value set to 1.
The semiannually compounded rate is 6% quoted on an annualized basis. The equivalent quarterly compounded rate is:
To solve such problems, think about investing a dollar for 1 year. The final amount should be the same under both the quotations. Under quarterly compounded rate, r, $1 grows to (1+r/4)^4 in 1 year. Under semiannual compounding, it grows to (1+0.06/2)^2 = 1.0609. Since these two should be equal, we get (1+r/4)^4 = 1.0609, giving r = 5.96%. Note that the quarterly compounded rate must be smaller than the semiannually compounded rate, ruling out 6.12 automatically.
A mortgage holding company has found that 1% of its mortgage holders default on their mortgage and lose the property. Furthermore, 90% of those who default are late on at least two monthly payments over the life of their mortgage as compared to 45% of those who do not default. What is the probability that a mortgagee with two or more late monthly payments will default on the mortgage and lose the property?
We have P(def) = 0.01. P(not def) = 0.99. P(two late payments/def) = 0.90. P(two late payments/not def) = 0.45. Using Bayes formula: p(def/two late payments) = (0.01*0.9)/(0.01*0.9 + 0.99*0.45) = 0.0198 = 0.020.
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