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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. 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 |
- The forecasted demand for the week of October 12 using a 3-week moving average =
pints.
- 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 =
- 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 |
- Using a 2-year moving average, the forecast for year 6 =
- If a 2-year moving average is used to make the forecast, the MAD based on this =
- 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) =.
- 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:
- Using the least-squares regression method, the equation for forecasting is
- The estimate for guitar sales if Maroon 5 performed on TV 10 times =
- 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 |
- The forecast for weeks 2 through 10 using exponential smoothing with alpha =
- For the forecast developed using exponential smoothing (alpha = 0.60 and initial forecast 20.0), the MAD =
- For the forecast developed using exponential smoothing (alpha = 0.60 and initial forecast 20.0), the tracking signal =
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