EBK ESSENTIALS OF STATISTICS FOR BUSINE
EBK ESSENTIALS OF STATISTICS FOR BUSINE
8th Edition
ISBN: 8220103648783
Author: Anderson
Publisher: CENGAGE L
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Chapter 6, Problem 39SE

A business executive, transferred from Chicago to Atlanta, needs to sell her house in Chicago quickly. The executive’s employer has offered to buy the house for $210,000, but the offer expires at the end of the week. The executive does not currently have a better offer but can afford to leave the house on the market for another month. From conversations with her realtor, the executive believes the price she will get by leaving the house on the market for another month is uniformly distributed between $200,000 and $225,000.

  1. a. If she leaves the house on the market for another month, what is the mathematical expression for the probability density function of the sales price?
  2. b. If she leaves it on the market for another month, what is the probability she will get at least $215,000 for the house?
  3. c. If she leaves it on the market for another month, what is the probability she will get less than $210,000?
  4. d. Should the executive leave the house on the market for another month? Why or why not?

a.

Expert Solution
Check Mark
To determine

Obtain the mathematical expression for the probability density function.

Answer to Problem 39SE

The probability density function for sales price is,

f(x)={125,000for 200,000x250,0000            elsewhere

Explanation of Solution

Calculation:

The executive’s employer offers to buy a house for $210,000 and this offer will be expired by the end of the week. Post discussion with business executive’s relator, the seller believes that by leaving the house in the market for another month, the price for house will be uniformly distributed between $200,000 and $225,000.

The probability density function for uniform distribution is,

f(x)={1bafor axb0  elsewhere

The probability density function for sales price is,

f(x)={125,000for 200,000x250,0000            elsewhere

b.

Expert Solution
Check Mark
To determine

Find the probability that the house will get with at least $215,000.

Answer to Problem 39SE

The probability that the house will get with at least $215,000 is 0.4.

Explanation of Solution

Calculation:

The cumulative density function for uniform distribution is,

P(xX)=Xaba

The probability that the house will get with at least $215,000 is,

P(x>215,000)=1P(x215,000)=1215,000200,00025,000=115,00025,000=0.4

Thus, the value of P(x>215,000) is 0.4.

c.

Expert Solution
Check Mark
To determine

Find the probability that the house will get less than $210,000.

Answer to Problem 39SE

The probability that the house will get less than $210,000 is 0.4.

Explanation of Solution

Calculation:

The probability that the house will get less than $210,000 is,

P(x<210,000)=210,000200,00025,000=10,00025,000=0.4

Thus, the value of P(x<210,000) is 0.4.

d.

Expert Solution
Check Mark
To determine

Explain whether the executive can leave the house in the market for another month or not.

Explanation of Solution

Calculation:

If the house is left in market for another month, the average sales price of house is,

E(x)=a+b2=200,000+225,0002=425,0002=212,500

This indicates that if the executive leaves the house in the market for another month, then the expected sales price is $2,500 higher than the before price $210,000. If the house is left in the market for another month, the executive will get less than the company’s offer with 0.4 probability. It represents that the executive can leave the house in the market for another month with an excepted cost of $212,500.

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Chapter 6 Solutions

EBK ESSENTIALS OF STATISTICS FOR BUSINE

Ch. 6.2 - Given that z is a standard normal random variable,...Ch. 6.2 - Given that z is a standard normal random variable,...Ch. 6.2 - 13. Given that z is a standard normal random...Ch. 6.2 - Given that z is a standard normal random variable,...Ch. 6.2 - Given that z is a standard normal random variable,...Ch. 6.2 - Given that z is a standard normal random variable,...Ch. 6.2 - 17. The mean cost of domestic airfares in the...Ch. 6.2 - The average return for large-cap domestic stock...Ch. 6.2 - Automobile Repair Costs. Automobile repair costs...Ch. 6.2 - Gasoline Prices. Suppose that the average price...Ch. 6.2 - Mensa Membership. A person must score in the upper...Ch. 6.2 - Television Viewing. Suppose that the mean daily...Ch. 6.2 - Time to Complete Final Exam. The time needed to...Ch. 6.2 - Labor Day Travel Costs. The American Automobile...Ch. 6.2 - 25. New York City is the most expensive city in...Ch. 6.3 - A binomial probability distribution has p=.20 and...Ch. 6.3 - Assume a binomial probability distribution has p =...Ch. 6.3 - Prob. 28ECh. 6.3 - Prob. 29ECh. 6.3 - 30. Playing video and computer games is very...Ch. 6.3 - Prob. 31ECh. 6.4 - Consider the following exponential probability...Ch. 6.4 - 33. Consider the following exponential probability...Ch. 6.4 - 34. Battery life between charges for the Motorola...Ch. 6.4 - 35. The time between arrivals of vehicles at a...Ch. 6.4 - Prob. 36ECh. 6.4 - Prob. 37ECh. 6.4 - 38. The Boston Fire Department receives 911 calls...Ch. 6 - 39. A business executive, transferred from Chicago...Ch. 6 - NCAA Scholarships. The NCAA estimates that the...Ch. 6 - Production Defects. Motorola used the normal...Ch. 6 - 42. During early 2012, economic hardship was...Ch. 6 - 43. The port of South Louisiana, located along 54...Ch. 6 - Service Contract Offer. Ward Doering Auto Sales is...Ch. 6 - The XO Group Inc. conducted a survey of 13,000...Ch. 6 - College Admissions Test Scores. Assume that the...Ch. 6 - 47. According to the National Association of...Ch. 6 - 48. A machine fills containers with a particular...Ch. 6 - Prob. 49SECh. 6 - Playing Blackjack. A blackjack player at a Las...Ch. 6 - Mean Time Between Failures. The mean time between...Ch. 6 - Prob. 52SECh. 6 - Do you dislike waiting in line? Supermarket chain...Ch. 6 - Prob. 54SE
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