Questions
Group Exercise #7 The tourist industry is subject to enormous seasonal variation.   A hotel in Bermuda...

Group Exercise #7

The tourist industry is subject to enormous seasonal variation.   A hotel in Bermuda has recorded its occupancy rate for each quarter over a 5-year period.    These data are shown in the following table:

Year

Quarter

Occupancy Rate

1995

1

0.561

2

0.702

3

0.800

4

0.568

1996

1

0.575

2

0.738

3

0.868

4

0.605

1997

1

0.594

2

0.738

3

0.729

4

0.600

1998

1

0.622

2

0.708

3

0.806

4

0.632

1999

1

0.665

2

0.835

3

0.873

4

0.670

  1. Calculate the seasonal indices for each quarter in order to measure seasonal variation.     Also, include the Trend Line Equation. (Hint:   Because the regression line yt = β0 + β1t    represents trend, it follows that the time series divided by the predicted values produces ytyt = St X Rtà seasonal & random variation.   And, because there is no cyclical effect, use this method to compute seasonal indices.)

  1. What can you infer from the Seasonal Indices?

  1. Deseasonalize the occupancy rates and assess.   (Hint:   Graphically compare the original and adjusted data sets.   Accordingly, provide data-supported inference/s.)

  1. Forecast each quarter’s occupancy rate for 2000.

  1. As an alternative to calculating and using seasonal indices to measure seasonal variations, indicator variables can be used in a multiple regression model.   Accordingly, use indicator variables and regression analysis to forecast hotel occupancy in 2000.   How does this compare to the forecast produced by using seasonal indices?  

In: Statistics and Probability

A). Suppose Travel and Leisure reported the average hotel price in Miami, Florida, was $153.57 per...

A). Suppose Travel and Leisure reported the average hotel price in Miami, Florida, was $153.57 per night in 2019. Assume the population standard deviation is $26.86 and that a random sample of 30 hotels was selected. Calculate the standard error of the mean.

B). According to the US Labor Department, the average hourly wage for private-sector production and non-supervisory workers was $20.04 in February 2013. Assume the standard deviation for this population is $6.00 per hour. A random sample of 35 workers from this group was selected. What is the standard error of the mean?

C). According to the US Labor Department, the average hourly wage for private-sector production and non-supervisory workers was $20.04 in February 2013. Assume the standard deviation for this population is $6.00 per hour. A random sample of 35 workers from this group was selected. What is the probability that the mean for this sample is less than $19.00?

D). According to the US Labor Department, the average hourly wage for private-sector production and non-supervisory workers was $20.04 in February 2013. Assume the standard deviation for this population is $6.00 per hour. A random sample of 35 workers from this group was selected. What is the probability that the mean for this sample is more than $20.84??

How would we interpret the probability calculated in the questions D?

E). According to the US Labor Department, the average hourly wage for private-sector production and non-supervisory workers was $20.04 in February 2013. Assume the standard deviation for this population is $6.00 per hour. A random sample of 35 workers from this group was selected. What is the probability that the mean for this sample is exactly $20.00?

In: Statistics and Probability

1-Younger, Inc. manufactures recliners for the hotel industry. It has two products, the Heater and the...

1-Younger, Inc. manufactures recliners for the hotel industry. It has two products, the Heater and the Massager, and total overhead is $3,160,000. The company plans to manufacture 400 Heaters and 100 Massagers this year. In manufacturing the recliners, the company must perform 600 material moves for the Heater and 400 for the Massager; it processes 900 purchase orders for the Heater and 700 for the Massager; and the company’s employees work 1,400 direct labor hours on the Heater product and 3,400 on the Massager. Younger’s total material handling costs are $2,000,000 and its total processing costs are $1,160,000. Using ABC, how much overhead would be assigned to the Heater product? $1,852,500

Answer:

2-Baxter Accounting Services estimates for next year revenues of $3,000,000, direct labor of $600,000, and overhead of $1,050,000. Under traditional costing, what is overhead rate is applied to audit jobs? 175% of direct labor

Answer:

3-Gant Accounting performs two types of services, Audit and Tax. Gant’s overhead costs consist of computer support, $300,000; and legal support, $150,000. Information on the two services is:

                                                              Audit                                       Tax         

Direct labor cost                                         $50,000                                  $100,000

CPU minutes                                                 40,000                                      10,000

Legal hours used                                               200                                          800

What is overhead applied to audit services using traditional costing? $150,000

What is overhead applied to tax services using traditional costing? $300,000

What is overhead applied to audit services using activity-based costing? $270,000.

What is overhead applied to tax services using activity-based costing? $180,000.

Gant Accounting performs tax services for Cathy Lane. Direct labor cost is $1,200; 600 CPU minutes were used; and 1 legal hour was used. What is the total cost of the Lane job using activity-based costing? $4,950

Answer:

In: Accounting

1- Assume that visitors of a hotel on average pay $20 for minibar per night per...

1- Assume that visitors of a hotel on average pay $20 for minibar per night per room, with a standard deviation of $3. Assume further that minibar expenses are normally distributed.
a- What percentage of rooms are expected to pay more than $25 per night, i.e. P(x > 25)
b- What percentage of rooms are expected to pay more than $40 per night, i.e. P( x > 40)?
c- What percentage of rooms are expected to pay less than $12 per night, i.e. P( x < 12)?
d- What percentage of rooms are expected to pay between $18 and $24, i.e. P(18 < x < 24)?
e- What percentage of rooms are expected to pay between $16 and $19, i.e. P (16 < x < 19)?

In: Statistics and Probability

Forecasting labour costs is a key aspect of hotel revenue management that enables hoteliers to appropriately...

Forecasting labour costs is a key aspect of hotel revenue management that enables hoteliers to appropriately allocate hotel resources and fix pricing strategies. Mary, the President of Hellenic Hoteliers Federation (HHF) is interested in investigating how labour costs (variable L_COST) relate to the number of rooms in a hotel (variable Total_Rooms). Suppose that HHF has hired you as a business analyst to develop a linear model to predict hotel labour costs based on the total number of rooms per hotel using the data provided. 3.1 Use the least squares method to estimate the regression coefficients b0 and b1 3.2 State the regression equation 3.3 Plot on the same graph, the scatter diagram and the regression line 3.4 Give the interpretation of the regression coefficients b0 and b1 as well as the result of the t-test on the individual variables (assume a significance level of 5%) Determine the correlation coefficient of the two variables and provide an interpretation of its meaning in the context of this problem.Check statistically, at the 0.05 level of significance whether there is any evidence of a linear relationship between labour cost and total number of rooms per hotel

STARS Total_Rooms Region_ID ARR_MAY ARR_AUG L_COST
5 412 1 95 160 2.165.000
5 313 1 94 173 2.214.985
5 265 1 81 174 1.393.550
5 204 1 131 225 2.460.634
5 172 1 90 195 1.151.600
5 133 1 71 136 801.469
5 127 1 85 114 1.072.000
4 322 1 70 159 1.608.013
4 241 1 64 109 793.009
4 172 1 68 148 1.383.854
4 121 1 64 132 494.566
4 70 1 59 128 437.684
4 65 1 25 63 83.000
3 93 1 76 130 626.000
3 75 1 40 60 37.735
3 69 1 60 70 256.658
3 66 1 51 65 230.000
3 54 1 65 90 200.000
2 68 1 45 55 199.000
1 57 1 35 90 11.720
4 38 1 22 51 59.200
4 27 1 70 100 130.000
3 47 1 60 120 255.020
3 32 1 40 60 3.500
3 27 1 48 55 20.906
2 48 1 52 60 284.569
2 39 1 53 104 107.447
2 35 1 80 110 64.702
2 23 1 40 50 6.500
1 25 1 59 128 156.316
4 10 1 90 105 15.950
3 18 1 94 104 722.069
2 17 1 29 53 6.121
2 29 1 26 44 30.000
1 21 1 42 54 5.700
1 23 1 30 35 50.237
2 15 1 47 50 19.670
1 8 1 31 49 7.888
1 15 1 40 55 3.500
1 18 1 35 40 112.181
4 10 1 57 97 30.000
2 26 1 35 40 3.575
5 306 2 113 235 2.074.000
5 240 2 61 132 1.312.601
5 330 2 112 240 434.237
5 139 2 100 130 495.000
4 353 2 87 152 1.511.457
4 324 2 112 211 1.800.000
4 276 2 95 160 2.050.000
4 221 2 47 102 623.117
4 200 2 77 178 796.026
4 117 2 48 91 360.000
3 170 2 60 104 538.848
3 122 2 25 33 568.536
5 57 2 68 140 300.000
4 62 2 55 75 249.205
3 98 2 38 75 150.000
3 75 2 45 70 220.000
3 62 2 45 90 50.302
5 50 2 100 180 517.729
4 27 2 180 250 51.000
3 44 2 38 84 75.704
3 33 2 99 218 271.724
3 25 2 45 95 118.049
2 30 2 30 55 40.000
3 10 2 40 70 10.000
2 18 2 60 100 10.000
2 73 2 22 41 70.000
2 21 2 55 100 12.000
1 22 2 40 100 20.000
1 25 2 80 120 36.277
1 25 2 80 120 36.277
1 31 2 18 35 10.450
3 16 2 80 100 14.300
2 15 2 30 45 4.296
1 16 2 25 70 379.498
1 22 2 30 35 1.520
4 12 2 215 265 45.000
4 34 2 133 218 96.619
2 37 2 35 95 270.000
2 25 2 100 150 60.000
2 10 2 70 100 12.500
5 270 3 60 90 1.934.820
5 261 3 119 211 3.000.000
5 219 3 93 162 1.675.995
5 280 3 81 138 903.000
5 378 3 44 128 2.429.367
5 181 3 100 187 1.143.850
5 166 3 98 183 900.000
5 119 3 100 150 600.000
5 174 3 102 211 2.500.000
5 124 3 103 160 1.103.939
4 112 3 40 56 363.825
4 227 3 69 123 1.538.000
4 161 3 112 213 1.370.968
4 216 3 80 124 1.339.903
3 102 3 53 91 173.481
4 96 3 73 134 210.000
4 97 3 94 120 441.737
4 56 3 70 100 96.000
3 72 3 40 75 177.833
3 62 3 50 90 252.390
3 78 3 70 120 377.182
3 74 3 80 95 111.000
3 33 3 85 120 238.000
3 30 3 50 80 45.000
3 39 3 30 68 50.000
3 32 3 30 100 40.000
2 25 3 32 55 61.766
2 41 3 50 90 166.903
2 24 3 70 120 116.056
2 49 3 30 73 41.000
2 43 3 94 120 195.821
2 20 3 70 120 96.713
2 32 3 19 45 6.500
2 14 3 35 70 5.500
2 14 3 50 80 4.000
1 13 3 25 45 15.000
1 13 3 30 50 9.500
2 53 3 55 80 48.200
3 11 3 95 120 3.000
1 16 3 25 31 27.084
1 21 3 16 40 30.000
1 21 3 16 40 20.000
1 46 3 19 23 43.549
1 21 3 30 40 10.000

In: Statistics and Probability

Forecasting labour costs is a key aspect of hotel revenue management that enables hoteliers to appropriately...

Forecasting labour costs is a key aspect of hotel revenue management that enables hoteliers to appropriately allocate hotel resources and fix pricing strategies. Mary, the President of Hellenic Hoteliers Federation (HHF) is interested in investigating how labour costs (variable L_COST) relate to the number of rooms in a hotel (variable Total_Rooms). Suppose that HHF has hired you as a business analyst to develop a linear model to predict hotel labour costs based on the total number of rooms per hotel using the data provided. 3.1 Use the least squares method to estimate the regression coefficients b0 and b1 3.2 State the regression equation 3.3 Plot on the same graph, the scatter diagram and the regression line3.4 Give the interpretation of the regression coefficients b0 and b1 as well as the result of the t-test on the individual variables (assume a significance level of 5%) Determine the correlation coefficient of the two variables and provide an interpretation of its meaning in the context of this problem 3.6 Check statistically, at the 0.05 level of significance whether there is any evidence of a linear relationship between labour cost and total number of rooms per hotel

STARS Total_Rooms Region_ID ARR_MAY ARR_AUG L_COST
5 412 1 95 160 2.165.000
5 313 1 94 173 2.214.985
5 265 1 81 174 1.393.550
5 204 1 131 225 2.460.634
5 172 1 90 195 1.151.600
5 133 1 71 136 801.469
5 127 1 85 114 1.072.000
4 322 1 70 159 1.608.013
4 241 1 64 109 793.009
4 172 1 68 148 1.383.854
4 121 1 64 132 494.566
4 70 1 59 128 437.684
4 65 1 25 63 83.000
3 93 1 76 130 626.000
3 75 1 40 60 37.735
3 69 1 60 70 256.658
3 66 1 51 65 230.000
3 54 1 65 90 200.000
2 68 1 45 55 199.000
1 57 1 35 90 11.720
4 38 1 22 51 59.200
4 27 1 70 100 130.000
3 47 1 60 120 255.020
3 32 1 40 60 3.500
3 27 1 48 55 20.906
2 48 1 52 60 284.569
2 39 1 53 104 107.447
2 35 1 80 110 64.702
2 23 1 40 50 6.500
1 25 1 59 128 156.316
4 10 1 90 105 15.950
3 18 1 94 104 722.069
2 17 1 29 53 6.121
2 29 1 26 44 30.000
1 21 1 42 54 5.700
1 23 1 30 35 50.237
2 15 1 47 50 19.670
1 8 1 31 49 7.888
1 20 1 35 45 0
1 11 1 40 55 0
1 15 1 40 55 3.500
1 18 1 35 40 112.181
3 23 1 40 55 0
4 10 1 57 97 30.000
2 26 1 35 40 3.575
5 306 2 113 235 2.074.000
5 240 2 61 132 1.312.601
5 330 2 112 240 434.237
5 139 2 100 130 495.000
4 353 2 87 152 1.511.457
4 324 2 112 211 1.800.000
4 276 2 95 160 2.050.000
4 221 2 47 102 623.117
4 200 2 77 178 796.026
4 117 2 48 91 360.000
3 170 2 60 104 538.848
3 122 2 25 33 568.536
5 57 2 68 140 300.000
4 62 2 55 75 249.205
3 98 2 38 75 150.000
3 75 2 45 70 220.000
3 62 2 45 90 50.302
5 50 2 100 180 517.729
4 27 2 180 250 51.000
3 44 2 38 84 75.704
3 33 2 99 218 271.724
3 25 2 45 95 118.049
2 42 2 28 40 0
2 30 2 30 55 40.000
1 44 2 16 35 0
3 10 2 40 70 10.000
2 18 2 60 100 10.000
1 18 2 16 20 0
2 73 2 22 41 70.000
2 21 2 55 100 12.000
1 22 2 40 100 20.000
1 25 2 80 120 36.277
1 25 2 80 120 36.277
1 31 2 18 35 10.450
3 16 2 80 100 14.300
2 15 2 30 45 4.296
1 12 2 40 65 0
1 11 2 30 50 0
1 16 2 25 70 379.498
1 22 2 30 35 1.520
4 12 2 215 265 45.000
4 34 2 133 218 96.619
2 37 2 35 95 270.000
2 25 2 100 150 60.000
2 10 2 70 100 12.500
5 270 3 60 90 1.934.820
5 261 3 119 211 3.000.000
5 219 3 93 162 1.675.995
5 280 3 81 138 903.000
5 378 3 44 128 2.429.367
5 181 3 100 187 1.143.850
5 166 3 98 183 900.000
5 119 3 100 150 600.000
5 174 3 102 211 2.500.000
5 124 3 103 160 1.103.939
4 112 3 40 56 363.825
4 227 3 69 123 1.538.000
4 161 3 112 213 1.370.968
4 216 3 80 124 1.339.903
3 102 3 53 91 173.481
4 96 3 73 134 210.000
4 97 3 94 120 441.737
4 56 3 70 100 96.000
3 72 3 40 75 177.833
3 62 3 50 90 252.390
3 78 3 70 120 377.182
3 74 3 80 95 111.000
3 33 3 85 120 238.000
3 30 3 50 80 45.000
3 39 3 30 68 50.000
3 32 3 30 100 40.000
2 25 3 32 55 61.766
2 41 3 50 90 166.903
2 24 3 70 120 116.056
2 49 3 30 73 41.000
2 43 3 94 120 195.821
4 9 3 100 180 0
2 20 3 70 120 96.713
2 32 3 19 45 6.500
2 14 3 35 70 5.500
2 14 3 50 80 4.000
1 13 3 25 45 15.000
1 13 3 30 50 9.500
2 53 3 55 80 48.200
3 11 3 95 120 3.000
1 16 3 25 31 27.084
1 21 3 16 40 30.000
1 21 3 16 40 20.000
1 46 3 19 23 43.549
1 21 3 30 40 10.000

In: Statistics and Probability

You operate a luxury hotel in Baltimore that famous celebrities rent for extended periods. The daily...

You operate a luxury hotel in Baltimore that famous celebrities rent for extended periods. The daily price is per room is $1,950. Operating costs average $60,000 per day, regardless of the number of rooms rented. Construct a spreadsheet model to determine the profit if 60 rooms are rented. The manager has observed that the number of rooms rented during any given day varies between 50 and 80 (the total number of rooms available).

a.Use data tables to evaluate the profit for this range of unit rentals.

b.Suppose the manager is considering lowering or increasing the daily price by $100. How will profit be affected? (Hint: use a two-way data table).

In: Statistics and Probability

Once upon a time a new hotel manager, whose staff was responsible for selling banquets and...

Once upon a time a new hotel manager, whose staff was responsible for selling banquets and hotel packages, was highly motivated to take advantage of a year-end bonus program for managers. In order to win the bonus, he needed to bring in new business so he decided to initiate a contest for his sales agents. He announced that he would pay $100 to the agent who had brought in the most new clients by the end of the month. He then sat back in his chair to await the results and decide how he would spend his bonus money. While visions of bonuses danced through his head, his sales agents were busily belly-aching for the following reasons:

(1) They were used to working as a team and resented being encouraged to compete against each other.
(2) In the manager's last contest, a new sales agent had reportedly cheated and "stole" new clients from the old-timers.
(3) The winner of the last contest was paid the prize money several months late, only after she had "shaken" it out of the sales manager.
(4) One sales agent's position had been cut, so the agents felt they were already operating beyond full capacity and working extra hours.
(5) The sales manager had not endeared himself to the agents, and they felt he was just using them to get his bonus.
(6) The sales agents felt as if they were being manipulated and perceivd the $100 bonus as an insult.

Not surprisingly, then, the sales agents decided to ignore the contest. The sales manger was angry when he saw the low level of new business at the end of the month and concluded that the agents were lazy. He told them they were unprofessional and complained about them at staff meetings so that soon everyone in the organization had heard about their "laziness." Old-timers who knew better scratched their heads because they remembered how hard the sales agents used to work before the new manager was hired. Within a few months, some of the agents quit and went to work for a competitor.

Questions:

(1) Should this manager go back to school and learn about the theories of motivation? What mistakes did he make?

(2) Which motivation theories apply to this case? Explain your answer. Does Expectancy Theory apply, and if so, how (explain)? What about Reinforcement Theory or Self-Determination Theory? Be sure to explain your answers.

(3) What do you think the sales manager should have done to try to motivate his sales agents? Relate your motivational strategies to the theories that we have discussed in class.

In: Economics

A resort hotel administrator is assigned to conduct performance reviews of the 47 guest services representatives...

A resort hotel administrator is assigned to conduct performance reviews of the 47 guest services representatives at the resort, and the length of time that the administrator typically spends doing each of these performance reviews is normally distributed with a mean of 63.9 minutes and a standard deviation of 18.4 minutes. The administrator is scheduled to meet with 7 guest service representatives today.

Standard Normal Distribution Table

a. What is the probability that the administrator will spend an average of less than one hour with each of the representatives?

Round to four decimal places if necessary

b. What is the probability that the administrator will spend a total of more than 7.5 hours with all 7 of the representatives?

Round to four decimal places if necessary

c. Within what range of values will the middle 99% of average times spent with each of the 7 representatives fall?

Range:

to

minutes

Round to one decimal place if necessary

d. What is the maximum total length of time the administrator would expect to spend with all 7 guest service representatives today, with a probability of 0.98?

minutes

Round to one decimal place if necessary

In: Statistics and Probability

Use the SEM formula and show all work. How satisfied are hotel managers with the computer...

Use the SEM formula and show all work.

How satisfied are hotel managers with the computer systems their hotels use? A survey was sent to 400 managers in hotels of size 200 to 500 rooms in Chicago and Detroit. In all, 101 managers returned the survey. Two questions concerned their degree of satisfaction with the ease of use of their computer systems and with the level computer training they had received. The managers responded using a seven-point scale, with 1 meaning "not satisfied", and 4 meaning "moderately satisfied," and 7 meaning "very satisfied".

a. What do you think is the population for this study? What are the major shortcomings in the obtained data?

b. The mean response for satisfaction with ease of use was 5.396. Find the 95% confidence interval for the managers sampled. (Assume the sample SD = 1.75)

c. Provide an interpretation for your answer in part B.

d. For satisfaction with training, the mean response was 4.398. Assuming the sample SD is 1.75, find the 99% confidence interval for the managers sampled.

e. Provide an interpretation of your answer obtained for part D.

In: Statistics and Probability