# MBA624 MSF624 (Fall 2018) Final Exam

MBA624 MSF624 (Fall 2018) Final Exam

### MBA624 MSF624 (Fall 2018) Final Exam

MBA624-MSF624  (Fall 2018) Final Exam

Each question is worth 2.5 points, for a total of 100 points.
Use CAPITAL letters to fill table

Use the following for questions 1 and 2

 Dealership Identifier Number of sales people New Car Brand Number of New cars sold each week Better Business Bureau Rating Profit from New Car Sales A1 18 VW 4 AAA \$12,868.00 A2 15 Toyota 13 AA \$46,410.00 A3 11 Ford 4 AA \$16,068.00 A4 17 VW 9 AA \$37,251.00 A5 18 Toyota 4 AAA \$12,776.00 A6 13 Toyota 15 AAA \$59,115.00 A7 5 VW 3 AA+ \$12,381.00 A8 20 VW 4 AA+ \$15,752.00 A9 6 Honda 4 AA+ \$12,648.00 A10 13 Honda 8 AA+ \$33,240.00 A11 10 Toyota 12 AA+ \$44,460.00 A12 15 VW 4 AAA \$14,504.00 A13 11 Honda 8 AAA \$25,872.00 A14 19 VW 15 A \$60,690.00 A15 14 Dodge 7 AA+ \$25,550.00 A16 13 Honda 5 AA+ \$18,750.00 A17 16 VW 12 A \$44,304.00 A18 17 Ford 9 AAA \$32,391.00 A19 20 VW 3 AAA \$12,240.00 A20 18 Toyota 4 A \$12,012.00

• What is the average for Profit from New Car Sales?
1. \$27,464.10
2. \$25,3140.64
3. \$18,197.10
4. \$16,454.25

• Which of the following is true?
1. New Car Brand and Better Business Bureau Rating are quantitative
2. New Car Brand and Better Business Bureau Rating are ratio
3. New Car Brand and Better Business Bureau Rating are qualitative
4. None of the above are correct

• A new restaurant opened in town. Below is a contingency table with the results of the generations that enjoy and do not enjoy the restaurant.  What is the probability of a Gen X’er enjoying the restaurant? (ch4)
 Enjoy Do Not Enjoy Millennials 5 5 Gen Y 8 2 Gen X 3 7 Baby Boomers 4 6
1. 5000
2. 2500
3. 1750
4. 0750

• The probability of a customer ordering a pumpkin spice latte on Halloween is 23%. What is the probability that three customers, in a row, will order a pumpkin spice latte on Halloween.  Assume the events are independent? (ch4)
1. 46
2. 012
3. 69
4. 053
• A school is 40% male students. Looking at a class of 20 students, what is the probability that more than 11 of the students are male?
1. 0.9435
2. 0.0710
3. 0.1275
4. 0.0565

MBA624 MSF624 (Fall 2018) Final Exam

• A drive thru at a local fast food restaurant averages 6 cars per 30 minutes. What is the probability there will be at least 10 cars in the next hour? (assume Poisson distribution)
1. 0.7576
2. 0.3472
3. 0.1048
4. 0.5385

• A marathoner is now running his marathons with an average time of 2 hours, and 3 minutes, and astandard deviation of 1 minute and her times follow a normal distribution. What is the probability of the marathoner running a marathon time of less than 2 hours?
1. 0014
2. 3666
3. 2145
4. 9914

• The finishing times for a stock car race uniform. The quickest finishing time is 9 minutes and 30 seconds, and the slowest finishing time is 12 minutes.  What is the probability a stock car racer will finish between 10 and 13 minutes?
1. .35126
2. .35
3. .6
4. .8

• Which of the following would indicate a process has special causes of variation?
1. A point is above the lower control limit and below the upper control limit
2. There are 4 consecutive points with the control limits going up
3. A point is above the upper control limit
4. There are 4 consecutive points below the center line and above the lower control limit
5. A, B and D are correct

Use the following data for problems 10-12

Crusty’s pizza company records the number of complaints they receive on their pizzas each day.  The last twenty days are in the table below.

 Day Complaints Day Complaints 1 6 11 6 2 7 12 6 3 7 13 9 4 4 14 8 5 9 15 2 6 10 16 4 7 0 17 10 8 7 18 10 9 3 19 2 10 6 20 7

• The upper control limit for the number of complaints is?
1. 6
2. 4
3. Does not exist
4. 15

• The process is?
1. Is out of control because at least one point is below the upper control limit
2. Is out of control because all the points are above the center line
3. Is in control
4. Out of control because at least one point is above the upper control limit
• The center line for the number of complaints is”
1. 0
2. 4
3. 27
4. 15

Use the following for questions 13-14

Crusty’s has introduced a new pizza and each day asks 40 customers who purchased it if they would recommend it to a friend.  The table below is the number of people out of 40 who said no.

 Day Negative survey responses Day Negative survey responses 1 3 11 2 2 2 12 1 3 10 13 4 4 2 14 2 5 3 15 4 6 3 16 3 7 5 17 2 8 4 18 7 9 3 19 8 10 4 20 0

• What is the lower control limit?
1. 0 or does not exist
2. -3.1
3. 2
4. 5

• Is the process in control?
1. No, point 5 is below the lower control limit
2. Yes, all points are within the control limits
3. No, point 3 exceeds the upper control limit
4. Both A and C are correct

Crusty’s has collected data for the last ten days for the time from when an order is taken until the pizza is finished (see follow data) (five samples are taken each day).

 Day sample 1 sample 2 sample 3 sample 4 sample 5 1 29.54 24.94 24.08 24.72 24.48 2 21.76 19.44 24.56 30.55 28.78 3 20.37 21.89 30.66 21.58 15.43 4 24.07 26.14 25.38 28.19 21.57 5 17.39 25.67 30.92 18.82 24.22 6 21.2 30.59 30.74 26.64 28.6 7 23.26 20.06 21.13 24.41 22.53 8 19.61 21.58 25.01 22.74 26.73 9 29.69 19.02 30.88 24.04 26.31 10 23.04 27.56 21.48 19.41 22.82

• Is the variation of this process under control?
1. The variation of this process appears out of control
2. The variation of this process appears in control
3. Need to check if mean of the process is under control first
4. It can not be determined from the available data.

• Which of the following is true regarding the mean?
1. The upper control limit is 34.1 and the process is in control
2. The lower control limit is 0 and the process is out of control
3. The lower control limit is 18.92 and the process is in control
4. The upper control limit is 29.65 the process is out of control

MBA624 MSF624 (Fall 2018) Final Exam

Use the following data to answer Questions 17-18. It shows temperature recorded on various days of the year (independent variable) and number of patrons at The Ice Cream Shop (dependent variable).

 Temp (X) Patrons (Y) 95 15 35 1 87 11 75 8 13 0

• What is the correlation coefficient between temperature and Ice Cream Shop patrons?
1. 9673
2. 8766
3. 7553
4. 1

• What is the regression equation which uses temperature to predict patrons?
1. Y = 0.1761X – 3.7432
2. Y =3.7432X – 0.1761
3. Y = 10.6 + (-3.08X)
4. Y = – 7.08 + 12.6X

• The marketing manager conduct a regression analysis between discounts (X) and sales (Y). The equation is: Y = 123-12.5X. Values for X that were used to develop the equation ranged from 5% discounts to 50% discounts. Assume the marketing manager wants to estimate sales for discounts of X = 75%. What would you tell the marketing manager?
1. Y = 113.63
2. Y = -814.50
3. It would be inappropriate to estimate Y because the slope is negative
4. It would be inappropriate to estimate Y because the regression equation was developed using discounts of 5% & 50%.

• The number of inches of rain in a calendar year increases the number of inches the river rises. Scientists calculated the following regression equation:y = 0.1909x – 3.0446.  Which of the following is true?
1. There is a correlation between rainfall and the depth of the river.
2. The river will rise about 14 inches if it rains 88 inches.
3. There is no way to predict the river level based on the number of inches of rain.
4. Both A and B are correct

Use the partial Excel regression output to answer Questions 20-23. It explores the relationship between rain and the number if inches the river rises.

• What is the correlation coefficient for this regression equation?
1. 7666
2. 1909
3. 9719
4. 9446

• How many days of rain were captured to generate the regression output (equation)?
1. 1
2. 3
3. 4
4. 5

• What can we say about the coefficient of determination?
1. The coefficient of determination can have values between 0 and 1
2. There is not sufficient supporting evidence at the 0.05 level to conclude there is a relationship between rainfall and the number of inches the river rises.
3. There is sufficient supporting evidence at the 0.05 level to conclude there is a relationship between rainfall and the number of inches the river rises.
4. The coefficient of determination doesn’t tell us anything about the relationship between rainfall and number of inches the river rises
5. Both A and C are correct

• What can we say about the regression equation?
1. When the linear relationship between two variables is significant we can say the independent variable causes the change in the dependent variable.
2. We cannot make assumptions about causation using the regression equation.
3. When the linear relationship between two variables is significant we can say the dependent variable causes the change in the independent variable.
4. It is not important to know if the linear relationship between two variables is significant.

Use the data below for questions 25-27.  These are the sales numbers at a local used car lot from January through June.

 Month Demand January 120 February 110 March 120 April 100 May 125 June 115

• Using a 4 month moving average, what is the forecast for July?
1. 3
2. 120
3. 115
4. 5

• Using a 3 month weighted moving average, where the weight for the most recent month is 0.65, the 2nd most recent month is 0.25 and the third most recent is 0.10, what is the forecast for July?
1. 3
2. 116
3. 106
4. 125

• Using exponential smoothing with an alpha of 0.3, and a January forecast of 110, What is the forecast for July
1. 117
2. 7
3. 9
4. 5

A company had developed a forecast using the Delphi method for January through June.  Use this data to answer questions 28 – 30.

 Month Demand Forecast January 225 240 February 240 230 March 230 235 April 225 230 May 229 225 June 260 230

• Using the data provided what is the Mean Absolute Deviation for the forecast method?
1. 17
2. -3.17
3. 5
4. 69

• Using the data provided, what is the Mean Squared Error?
1. 17
2. 5%
3. 4%
4. 12%

• Using the data provided what is the MAPD?
1. 7%
2. 1%
3. 9%
4. 6%

• Using the data below, which is cars sold at a local used car lot, what is the seasonal index for Q2?

 Q1 Q2 Q3 Q4 Year 1 120 180 210 90 Year 2 140 190 210 110 Year 3 150 210 220 120

1. 210
2. 328
3. 164
4. 297

• A compute store had calculated the seasonal index for each of the quarters of the year. This information is in the chart below. They also have calculated the regression formula to predict sales for each year.  This equation is y = 124x + 1727.  What is the forecast for computer sales for year 4 quarter 3? Round your answer to the nearest whole number.

 Quarter Index Q1 0.164 Q2 0.237 Q3 0.364 Q4 0.235
1. 527
2. 497
3. 809
4. 556

Using the following project outline for problems 33-35

 Task Immediate Predecessor Task Length (Days) A 2 B A 3 C B 1 D B 4 E C,D 2

• What is the critical path?
1. A-B-D-E
2. A-C-E-F
3. B-D-E-F
4. A-F-G-H

• Calculate the expected completion time.
1. 7 days
2. 11 days
3. 19 days
4. 20 days

• What is the slack for task C?
1. 1 days
2. 3 days
3. 5 days
4. 7 days

Using the following project outline, answer problems 36-38

 Task Immediate Predecessor Optimistic Most Likely Pessimistic A 1 2 3 B A 4 5 6 C B 3 6 15 D B 2 4 6 E C 1 4 7 F D 2 3 4 G E,F 4 6 8

• Calculate the average time for task C.
1. 65
2. 3
3. 5
4. 7

• What is the critical path?
1. A-C-F-H-I
2. A-B-C-E-G
3. B-C-D-E-F
4. A-C-E-F-G

• What is the estimated completion time?
1. 12
2. 20
3. 24
4. 30

Use the following crashing table to answer questions 39 and 40

 Project time Period cost Cumulative cost A B C D E F G H I J 37 0 0 36 60 120 1 35 80 200 1 1 34 80 280 2 2 33 80 360 3 2 32 135 495 3 1 2 1 31 180 675 1 4 1 2 1 30 180 855 2 5 1 2 1 29 733.33 1588.33 1 2 5 1 2 1 28 983.33 2571.67 2 1 2 5 1 2 1

• In order to crash this project down to 35 weeks you should
1. Crash activity D by one week and activity H by one weeks for a total crash cost of \$200
2. Crash activity D by one week and activity H by two weeks for a total crash cost of \$60
3. Crash activity C by 1 week, D by 4 weeks, F by 1 week, H by two weeks, and I by 1 week for a total crash cost of \$180
4. Crash Activity D by one week and activity I by two weeks for a total crash cost of \$200

• Your company is offered a bonus of \$280 per week to get the project done early, how many weeks should your company crash this project down to (i.e., to what expected project completion time)?
1. 0
2. 28
3. 30
4. 36
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