Hotel Sport is in the suburb of large metropolitan area near a sports complex that has a stadium suitable for baseball and soccer games. The 250-room independent hotel is a select-service property in the mid-range category. Its rate structure is simple:

Rack                                         $190

Weekend                                 $159

Low season/Government    $140

Groups (of 15+)                     $130

Best available rate                 $120

Late August is traditionally a slow season in the hotel and business picks up in September after area businesses and government offices are back in full gear. The sell rate in late August is the $140 low season rate. For the weekend of August 20 to 22 the forecasted occupancy is around 130 rooms. The reservations on the book are 90 guaranteed and 25 non-guaranteed reservations. The hotel expects 15 walk-ins.

Questions

1. It is July 29. What rate should the revenue manager approve to quote for reservation inquiries for the weekend of August 20–22?

2. Now it is July 30. One day later: The Major League Soccer Franchise of the city had just clinched a spot in the playoffs and the first game in the elimination round will be against a team from California, the L. A. Galaxy. They have the world’s most famous superstar, David Beckham, in its lineup on August 21. All the hotels in the city are filling up fast and phones with reservation inquiries are ringing off the hook at the Sport.

What rate should the revenue manager approve to quote now for group reservation inquiries for the weekend of August 20–22? Are there any stay control measures that should be considered?

1) True or False? In a simple regression with the sample size being 20, we find the sum of squared residuals to be 1800, then the mean square error of the regression equals 10.

2) True or False? A local trucking company fitted a regression to relate the travel time (days) of its shipments as a function of the distance traveled (miles). The fitted regression is Time = −7.126 + 0.0214 Distance, based on a sample of 20 shipments. The estimated standard error of the slope is 0.0053. In a right-tailed test for a nonpositive slope at ? ൌ 0.01, we fail to reject the null hypothesis that the slope is no more than zero.

3) True or False? Smaller mean square errors lead to wider prediction intervals for Y.

4)True or False? If there is non-normality of errors, the OLS estimators of the slope and intercept will be biased and inconsistent.

5) True or False? In a runs test with 80 residuals, we find there are 60 zero centerline crossings. It suggests there is negative autocorrelation for the errors

6) True or False? In a simple regression with 25 observations, a leverage statistic of 0.1 would indicate the corresponding observation has high leverage.

7) True or False? A studentized residual equal to -2.5 indicates the original residual is unusual.

16. The accompanying table shows a portion of a data set that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City.

a. Estimate the sample regression equation that enables us to predict property taxes on the basis of the size of the home. (Round your answers to 2 decimal places.)

TaxesˆTaxes^ =  +  Size.

b. Interpret the slope coefficient.

• As Size increases by 1 square foot, the property taxes are predicted to increase by $6.67.

• As Property Taxes increase by 1 dollar, the size of the house increases by 6.67 ft.

c. Predict the property taxes for a 1,600-square-foot home. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal pl

A survey of 500 major U.S. manufacturing plants was completed in order to gain information about water pollution near each plant facility. Data have been collected on the amount of WATER POLLUTANTS (PL) found within ½ mile of each plant. (No plants were within 50 miles of each other). The pollutants were measured as the average parts per million based on each gallon of water sampled for each plant. For each plant, the AMOUNT OF WATER (W) used and the AVERAGE RAINFALL (R) was recorded. Plants were classified to be within one of four TYPES (chemical, paper, consumer durable goods, others) and the plant AGE (under 15 years; 15 years or older) was noted. A scale for LOCAL ENVIRONMENTAL REGULATIONS ENFORCEMENT was made (Strong enforcement; Moderate enforcement; Minimal to No Enforcement). Using these data, (20 points) a. Specify a linear model that would allow you test the effects of the impact of each variable above. b. Interpret each parameter in your model. c. Show how you would test the hypothesis that chemical and paper plant pollution is equal. d. How would you test the impact of local regulation enforcement on plant’s pollution

“I rented a car through price line via the internet. I got a great price for 10 days at 25$ a day. I reserved the car from Vernon NJ and I was scheduled to pick it up at the Ontario California airport. When I arrived to pick it up the Budget attendant said that priceline cancelled the reservation. I said no problem, I am here so reinstate it. They said sure and asked for $89 per day. I immediately called priceline who refused to do anything. I explained that I was stranded 2600 miles from home and rep kept repeating there was nothing she could do, it was budget who cancelled it- I demanded that the budget rep print the cancel order and; low and behold Budget cancelled it but it appears that it was in concert with priceline.” This is an example of: q) everyday low pricing h) dynamic pricing r) uniform delivered pricing i) loss-leader pricing s) bait and switch deceptive pricing j) price lining/pricing points t) price fixing p) cash discounts o) trade discounts l) basing-point pricing k) flexible-price policy

Making Money, Inc. is considering the purchase of a new truck so it can make more money. The truck costs $120,000.

Making Money, Inc. had been renting the truck every week for $500 per week plus $1.20 per mile. On average, the truck is traveling 75 miles per week.

If Making Money, Inc. purchases the truck, it will only have to pay for diesel fuel and maintenance, at about $.50 per mile. Insurance costs for the new truck are $5,000 per year.

The truck will probably be worth $20,000 (in real terms) after six years, when the company would be looking to sell the truck.

Assume a nominal discount rate of 10% and a forecasted inflation rate of 2.5%. The tax code is rapidly changing, so we are going to ignore taxes for now.

WHAT IS THE NPV of BUYING vs RENTING? (round to nearest whole dollar)

Hint: All numbers given in the questions are in real terms. Assume CF at end of year, for simplicity.

Hint #2:

Step 1: list assumptions

Step 2: calc real interest rate

Step 3: Calc cost (NPV) to rent

Step 4: Calc cost (NPV) to buy

Step 5: subtract NPVs

6. The coolest stars are those whose color is

a. blue
b. red
c. yellow
d. white


7. A pulsar is a powerful source of radio (and sometimes light) waves thought to be coming from

a. rapidly spinning white dwarf stars
b. supernovas
c. spinning stars composed primarily of neutrons
d. ordinary stars like our Sun which happen to be more energetic than the average


8. The existence of "black holes" has been

a. verified by actual astronomical observations
b. derived from a theoretical analysis of how large stars evolve and explode
c. disproved by recent astronomical evidence
d. used to explain the formation of our solar system


9. Our Milky-way galaxy has a diameter of approximately

a. 1,000,000 miles
b. 1,000,000,000 km
c. 4 light years
d. 100,000 light years


10. Current theories indicate that our universe is composed of huge galactic cluster of stars. These clusters

a. travel randomly in all directions
b. are all moving in the same direction
c. are approaching one another due to gravitational attractive forces
d. are moving away from one another at very high speeds

The accompanying table shows a portion of a data set that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City.

a. Estimate the sample regression equation that enables us to predict property taxes on the basis of the size of the home. (Round your answers to 2 decimal places.)

TaxesˆTaxes^ =  +  Size.

b. Interpret the slope coefficient.

• As Property Taxes increase by 1 dollar, the size of the house increases by 6.85 ft.

• As Size increases by 1 square foot, the property taxes are predicted to increase by $6.85.

c. Predict the property taxes for a 1,300-square-foot home. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)

  TaxesˆTaxes^               

rev: 12_08_2018_QC_CS-150875

1. A new entrepreneur wants to estimate the costs of an offsite team-building event for her 14 employees. She was able to gather the following information on a 3-day program in which she is interested. Use the unit technique to estimate the cost per employee of this event. Assume there will 100% participation in all activities.