**Quarterly Demand Forecasting for Smartphones****Objective:**Analyze the quarterly smartphone demand data at a retailer and forecast the demand for year 5 using Winter's model. The model involves smoothing parameters, alpha (α) = 0.05, beta (β) = 0.10, and gamma (γ) = 0.15. Evaluate the accuracy of the forecast by calculating the Mean Absolute Deviation (MAD), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). Explore alternative values for α, β, and γ to achieve a lower MAD or MSE.**Data Table:**| **Year** | **Quarter** | **Demand** ||----------|-------------|------------|| 1 | I | 513 || | II | 932 || | III | 1,509 || | IV | 1,902 || 2 | I | 693 || | II | 1,163 || | III | 1,857 || | IV | 2,469 || 3 | I | 846 || | II | 1,439 || | III | 2,271 || | IV | 3,079 || 4 | I | 1,070 || | II | 1,751 || | III | 2,785 || | IV | 3,613 |**Instructions:**1. **Evaluate the Model:** - Use the given initial values for α, β, and γ to implement Winter’s model. - Calculate the MAD, MAPE, and MSE to assess forecast accuracy.2. **Optimize Parameters:** - Experiment with different values of α, β, and γ. - Identify combinations that result in lower MAD or MSE for improved forecast accuracy.**Diagrams:**- The table provides raw demand data that should be visualized using time series plots to better understand seasonal variations and trends.- Compare forecasted demand against actual demand visually to identify discrepancies.**Conclusion:**This analysis provides insights into both historical demand patterns and forecasts, which are crucial for inventory management and strategic planning in the retail sector.

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Answered: 4. Quarterly demand for smartphones at…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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Please do not give solution in image format thanku A small manufacturing firm has recorded a time series of the cost per unit for the firm’s leading product over the past eight years. Year 1 2 3 4 5 6 7 8 Cost/Unit ($) 20 24.5 28.2 27.5 26.6 30 31 36 a) If you are not given a base value or trend, what would be the forecast for the year 10 made at the end of year 8 (α=0.2, β=0.4). b) Forecast for the year 9 using 1) 5-month weighted average using 0.1,0.1,0.1,0.2,0.3, with the heaviest weight applied to the recent month 2) Exponential smoothing using α =0.2 and forecast of 21 for year 5 3) If α value was not provided in the question above, what value of α would you choose?
Given the following historical data, what is the simple three-period moving average forecast for period 6? Period 1 2 3 4 5 67.67 68.2 67.3 68.4 Value 73 66 64 73 66
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Answer this using excel on a spreads
In a retail store, the actual sales of a particular product (in thousands of units) over the past few months are as follows: Month Sales 1 16 2 22 3 18 4 20 5 23 Using exponential smoothing method with α (smoothing constant) of 0.75 and the given forecast for month 1 equal to 10, what is the forecast for month 6?
41) A medium-term forecast is considered to cover what length of time? A) 2-4 weeks B) 1 month to 1 year C) 2-4 years D) 5-10 years E) 20 years 42) When is the exponential smoothing model equivalent to the naÃ¯ve forecasting model? A) ? = 0 B) ? = 0.5 C) ? = 1 D) during the first period in which it is used E) never 43) Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130. Suppose a one-semester moving average was used to forecast enrollment (this is sometimes referred to as a naÃ¯ve forecast). Thus, the forecast for the second semester would be 120, for the third semester it would be 126, and for the last semester it would be 110. What would the MSE be for this situation? A) 196.00 B) 230.67 C) 100.00 D) 42.00 E) None of the above 44) Which of the following methods tells whether the forecast tends to be too high or too low? A) MAD B) MSE C) MAPE D) decomposition E) bias 45) Assume that you have tried three different…
Given the following historical data, what is the simple three-period moving average forecast for period 6? Period Value 1 73 2 68 3 65 4 72 5 67
Problem 5 You are trying to determine what forecast method to use. Based upon the following historical data, calculate the following forecast and specify what procedure you would utilize. MAY JUNE MONTH JANUARY FEBRUARY MARCH APRIL DEMAND 62 65 67 68 71 73 MONTH JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER DEMAND 76 78 78 80 84 85 a. Calculate the simple three-month moving average for periods 4 to 12. b. Calculate the weighted three-month moving average for periods 4 to 12. Use weights of 0.50, 0.30, and 0.20 for the most recent, second most recent, and third most recent periods, respectively. c. Calculate the single exponential smoothing forecast for periods 2 to 12 using an initial forecast (F₁) of 61 and a of 0.30. d. Calculate the exponential smoothing with trend component forecast for periods 2 to 12 using an initial trend forecast (T₁) of 1.8, and initial exponential smoothing forecast (F₁) of 60, an a of 0.30 and ō of 0.30. e. Calculate the MAD for the forecasts made by each…
Historical sales data is shown below. Week Actual Forecast 1 328 300 2 272 3 245 4 223 5 205 6 Using alpha (α) = 0.2, what is the exponential smoothing forecast for period 6? Note: Round your answer to 2 decimal places. Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.
Use a pivot table to display the quarterly sales and estimate the percentage of sales in each quarter. (Hint: Q1 = approx. 25%; all hints are all approximate values,
Practice examples. Please show solution. Thank you.
*** Can you please demonstrate how to do parts d, e, f? Given: Year Demand 1 7 2 9 3 5 4 9 5 Predict the value for Year 5: 2 year moving average What is MSE for 2 year moving average? 2 year moving average using 0.6 (weight for the oldest period) and 0.4(weight for most recent period Exponential smoothing, =0.2 and forecast for Year 1 = 5 Linear trend Which forecast method has the least amount of error using MAD? What is the coefficient?

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