Understanding Business
12th Edition
ISBN: 9781259929434
Author: William Nickels
Publisher: McGraw-Hill Education
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Question
Sales of industrial vacuum cleaners at Yarena Supply CO. over the past 13 months are as follows:
Sales in P1,000 |
Month |
Sales in P1,000 |
Month |
11 |
January |
14 |
August |
14 |
February |
17 |
September |
15 |
March |
12 |
October |
10 |
April |
14 |
November |
15 |
May |
16 |
December |
17 |
June |
11 |
January |
11 |
July |
|
|
Required suing a moving average with three periods, determine the demand for vacuum cleaners for next February?
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- Using exponential smoothing with alpha = .2, and assuming the forecast for period 11 was 80, what would the forecast for period 14 be?arrow_forwardABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using a five-month moving average approach.arrow_forwardQUESTION 4 Suppose the following are the seasonal indices for the first three quarters of the year for a quarterly series: Quarter Seasonal Index Q1 72.4 Q2 85.3 Q3 109.6 Remember that the seasonal indices should average 100 so you should be able to infer the seasonal index for Q4. Furthermore, suppose that the estimated coeffcients from a regression of the deseasonalized series on Time are given below: Coefficients Intercept 2,506 Time 71.3 If the original value of the series in a Q1 was 2,040, then what is the seasonally adjusted value? (please round your answer to 1 decimal place)arrow_forward
- part b)arrow_forwardThe moving average forecast method should only be used with time series data demonstrating a linear trend. Question 17 options: True Falsearrow_forwardIn January a battery dealer pridicts February demand of 2000 2 charger battery whereas the actual demand was 1756 unit of batteries , using a smoothing constant of alpha 0.34, the dealer wishes to forecast the march demand using the exponential smoothing model ?arrow_forward
- What is the distinction between simulated and anticipated average demand:arrow_forwardAssuming the following deseasonalized demand, what would your Level and Trend FORECAST factors be for future deseasonalized demand estimates? (Hint, you might want to use excel for this) period 1 2 3 4 5 6 7 8 9 10 13673 6640 2737 3486 141 13186) 5448 3485 7728 16591 8236 3316 855358 11 12 13 15 16 17 18 19 Demand Deseasonalized D₁ Demand D 3200 7658 4420 2384 3654 8680 5795 1953 4742 20 4472 4657 4956 5074 5157 5917 6646 6850 6791 6573 6363 6308 6932 7887 8662 8989 O Level-4696 Trend-343 O Level-3612. Trend-264 O Level 3629; Trend-263 O Level-2528: Trend-185arrow_forwardYear 1 Demand Year 2 Demand Year 3 Demand 1 12 1 16 1 14 45 25 32 3 76 52 3 71 84 4 4 62 4 47 a. Determine the seasonal factors for each quarter. b. Based on the result of part (a), determine the deseasonalized demand series. c. Predict the demand for each quarter of Year 4 for the deseasonalized series from a six-quarter moving average. d. Using the results from parts (a) and (c), predict the demand for the shoes for each quarter of Year 4.arrow_forward
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