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Homework answers / question archive / Rutgers University PSYCHOLOGY 01:830:123 Chapter 4 Sample test 1)Which forecasting model is based upon salespersons' estimates of expected sales?   2

Rutgers University PSYCHOLOGY 01:830:123 Chapter 4 Sample test 1)Which forecasting model is based upon salespersons' estimates of expected sales?   2

Management

Rutgers University

PSYCHOLOGY 01:830:123

Chapter 4 Sample test

1)Which forecasting model is based upon salespersons' estimates of expected sales?

 

2. A forecast that projects a company's sales is

 

3. CPFR is

 

4. The forecasting time horizon that would typically be easiest to predict for would be the

 

5. A tracking signal

 

6. Which forecasting method considers several variables that are related to the variable being predicted?

 

7. What is a data pattern that repeats itself after a period of days, weeks, months, or quarters?

 

8. Which of the following is a quantitative forecasting method?

 

9. Which one of the following statements is NOT true about the forecasting in the service sector?

 

10. A tracking signal

 

 
   
 

 

11. Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of these coffees sold over six different price values:

 

Price

Number Sold

$2.70

765

$3.40

515

$2.10

990

$4.10

240

$3.10

320

$4.05

475

 

Using simple linear regression and given that the price per cup is $1.80, the forecasted demand for mocha latte coffees will be

 

12. The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6weeks:

 

Week Of

Pints Used

August 31

360

September 7

370

September 14

412

September 21

383

September 28

366

October 5

374

 

  1. The forecasted demand for the week of October 12 using a 3-week moving average =

pints.

 

  1. Using a 3-week weighted moving average, with weights of 0.20, 0.25, and 0.55, using 0.55 for the most recent week, the forecasted demand for the week of October 12 =

 

  1. If the forecasted demand for the week of August 31 is 360 and alpha = 0.30, using exponentialsmoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12

 

Week Of

Pints Used

Forecast for this Date

August

360

 

September 7

370

 

September 14

412

 

September 21

383

 

September 28

366

 

October 5

374

 

October 12

-

 

 

 
   
 

 

 

13. The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as follows:

 

Year

1

2

3

4

5

Mileage

3000

4050

3500

3800

3750

 

  1. Using a 2-year moving average, the forecast for year 6 =

 

  1. If a 2-year moving average is used to make the forecast, the MAD based on this =

 

  1. The forecast for year 6 using a weighted 2-year moving average with weights of 0.35 and

0.65 (the weight of 0.65 is for the most recent period) =.

 

  1. Using exponential smoothing with alpha = 0.200 and the forecast for year 1 being 3000 the forecast for year 6 =

 

Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the previous month. Gershon has collected the data shown in the following table:

 

 

  1. Using the least-squares regression method, the equation for forecasting is

 

  1. The estimate for guitar sales if Maroon 5 performed on TV 10 times =

 

  1. The correlation coefficient (r) for this model =

 

The coefficient of determination (r2) for this model =

The percentage of variation in sales that can be explained by TV appearances =

 

 

 
   
 

 

 

14. Sales of tablet computers at Ted Glickman's electronics store in Washington, D.C., over the past 10 weeks are shown in the table below:

 

 

Week           1

2

3

4

5

6

7

8

9

10

Demand 20

21

27

37

25

30

37

24

25

30

 

  1. The forecast for weeks 2 through 10 using exponential smoothing with alpha =

 

  1. For the forecast developed using exponential smoothing (alpha = 0.60 and initial forecast 20.0), the MAD =
  2. For the forecast developed using exponential smoothing (alpha = 0.60 and initial forecast 20.0), the tracking signal =

 

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