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In Exercises 5–36, express all probabilities as fractions.

FedEx Deliveries With a short time remaining in the day, a FedEx driver has time to make deliveries at 6 locations among the 9 locations remaining. How many different routes are possible?

Short Answer

Expert verified

The number of different routes possible is equal to 60480.

Step by step solution

01

Given information

Six deliveries at six different locations are to be made by the FedEx driver.

The different possible routes are to be computed.

02

Permutation

The total number of possible ways to choose r units from n units, when the order of the arrangements is considered, is computed using permutation.

Prn=n!n-r!r!

03

Calculation

The total number of locations is equal to 9.

The number of deliveries to be made is 6.

The total number of possible routes that can be taken to make the deliveries is equal to:

9P6=9!9-6!6!=60480

Therefore, the number of different routes possible to make the six deliveries is equal to 60480.

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Most popular questions from this chapter

In Exercises 9–20, use the data in the following table, which lists drive-thru order accuracy at popular fast food chains (data from a QSR Drive-Thru Study). Assume that orders are randomly selected from those included in the table.

McDonald’s

Burger King

Wendy’s

Taco Bell

Order Accurate

329

264

249

145

OrderNotAccurate

33

54

31

13

Fast Food Drive-Thru Accuracy If two orders are selected, find the probability that they are both from Burger King.

a. Assume that the selections are made with replacement. Are the events independent?

b. Assume that the selections are made without replacement. Are the events independent?

In Exercises 9–20, use the data in the following table, which lists drive-thru order accuracy at popular fast food chains (data from a QSR Drive-Thru Study). Assume that orders are randomly selected from those included in the table.

McDonald’s

Burger King

Wendy’s

Taco Bell

Order Accurate

329

264

249

145

OrderNotAccurate

33

54

31

13

Fast Food Drive-Thru Accuracy If one order is selected, find the probability of getting food that is not from McDonald’s.

Denomination Effect. In Exercises 13–16, use the data in the following table. In an experiment to study the effects of using a \(1 bill or a \)1 bill, college students were given either a \(1 bill or a \)1 bill and they could either keep the money or spend it on gum. The results are summarized in the table (based on data from “The Denomination Effect,” by Priya Raghubir and Joydeep Srivastava, Journal of Consumer Research, Vol. 36).

Purchased Gum

Kept the Money

Students Given A \(1 bill

27

46

Students Given a \)1 bill

12

34

Denomination Effect

a. Find the probability of randomly selecting a student who spent the money, given that the student was given a \(1 bill.

b. Find the probability of randomly selecting a student who kept the money, given that the student was given a \)1 bill.

c. What do the preceding results suggest?

Odds. In Exercises 41–44, answer the given questions that involve odds.

Relative Risk and Odds Ratio In a clinical trial of 2103 subjects treated with Nasonex, 26 reported headaches. In a control group of 1671 subjects given a placebo, 22 reported headaches. Denoting the proportion of headaches in the treatment group by ptand denoting the proportion of headaches in the control (placebo) group by role="math" localid="1644405830274" pc, the relative risk is ptpc. The relative risk is a measure of the strength of the effect of the Nasonex treatment. Another such measure is the odds ratio, which is the ratio of the odds in favor of a headache for the treatment group to the odds in favor of a headache for the control (placebo) group, found by evaluating the following:pt/1-ptpc/1-pc

The relative risk and odds ratios are commonly used in medicine and epidemiological studies. Find the relative risk and odds ratio for the headache data. What do the results suggest about the risk of a headache from the Nasonex treatment?

At Least One. In Exercises 5–12, find the probability.

At Least One Defective iPhone It has been reported that 20% of iPhones manufactured by Foxconn for a product launch did not meet Apple’s quality standards. An engineer needs at least one defective iPhone so she can try to identify the problem(s). If she randomly selects 15 iPhones from a very large batch, what is the probability that she will get at least 1 that is defective? Is that probability high enough so that she can be reasonably sure of getting a defect for her work?

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