My App is a small but growing start-up that sees demand for several of its apps increasing quickly. The table below shows the last sixmonths of downloads. Use a forecast for the first month of 220,000, an initial trend forecast of 35,000, and smoothing parameters of015 for both demand smoothing and trend smoothingMonth (t) Monthly Application Downloads Forecast for Next MonthTrend220,000.0035,000.00200,0002250, 100334,000380,000440,000500,000(Round your answers to 2 decimal places.)Complete the table above, filling in the "Forecast for next month" and "Trend" columns, using doublea.exponential smoothing(Round your answers to 2 decimal places.)Month 7's forecast isb.

Double exponential smoothing is a forecasting model which identify the forecasting with the…

Answered: My App is a small but growing start-up…

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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Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 4 5 6 Value 19 14 15 12 18 13 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE = (b) mean squared error MSE = (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE = % (d) What is the forecast for week 7?
Collaborative Planning, Forecasting and Replenishment (CPFR) states cooperative management of demand and supply through joint visibility and replenishment of products in the SC. Select one: a. True b. False
The following represents the actual demand and two different sets of forecasts using different methods. Compute the MAD for each forecasting method and determine the best method for this set of data. Year-Qtr Actual demand Forecast methos 1 MAD1 (A-F) Forecast Method 2 MAD2 (A-F) 2020-3 98 97 89 2020-4 108 110 106 2021-1 83 68 70 2021-2 100 101 102 2021-3 95 86 87 2021-4 90 94 92 2022-1 71 68 72 2022-2 104 105 106 2022-3 84 91 88 2022-4 80 93 91 2023-1 78 68 70 2023-2 120 118 122
Please help with the correct answers in details: Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 4 5 6 Value 19 12 17 10 18 15 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE = (b) mean squared error MSE = (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE = % (d) What is the forecast for week 7?
Please answer it ASAP. With only short explanation. Please answer fast i will really upvote.
As a Sales Head for a consumer durable firm, you wish to have sales forecast trends based on past sales rendered. Briefly describe the methods of forecasting future demand on the basis of past sales.
Smart Phone covers sales for the past 12 months is given below. Management forecast's for the months of March, April, May, and June are listed Month Unit Sales Management's Forecast Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 100 95 95 112 126 118 95 85 101 94 89 110 122 114 108 112 a) What is the MAD for the forecast developed by management sales (round your response to two decimal places) What in the MAPE for the forecast developed by management % (round your response to two decimal places). %3D
B. The following table shows the number of televisions sold over the last ten years at a local electronic store. year TV sales 1 150 2 300 3 480 4 600 5 630 6 640 7 700 8 825 9 900 10 980 i. Using the trend projection, develop a formula to predict sales for years 11 and 12. Develop a table to calculate the slope and intercept. Please Show All Working. Use that formula to forecast television sales for years 11 and 12
what are the differences between the following models? 1) Moving average models 2) Simple exponential smoothing 3) Holt's exponential smoothing 4) Winter's exponential smoothing 5) The Bass model In your answer, write down the equation for each model. What does each variable mean? Finally, why would I use one model as opposed to the others? For example, the Bass Model is used to forecast the adoption rate for new innovations, or sigmoid shaped growth.
From the following annual data of sales (in 000 .$.) Find the trend values by using least square method. Also estimate the sales of 2014. Year 2004 2005 2006 2007 2008 2009 2010 Sales {In 000 $} 77 88 94 85 91 98 90
1. Favors Distribution Company purchases small imported trinkets in bulk, packages them, and sells them to retail stores. They are conducting an inventory control study of all their items. The following data for the year 2006 are for one such item, which is not seasonal. [10 Points] Month Sales Jan Feb 18 19 Mar Apr May Jun 17 21 20 19 Jul 20 Aug 23 a. Use trend projection to estimate the relationship between time and sales (state the trend line equation in this problem). b. Calculate forecasts for February 2007, April 2007, and February 2008
Year Season Sales 2018 Winter 40 2018 Spring 29 2018 Summer 31 2018 Fall 40 2019 Winter 102 2019 Spring 87 2019 Summer 96 2019 Fall 132 2020 Winter 105 2020 Spring 93 2020 Summer 105 2020 Fall 117 2021 Winter 141 2021 Spring 39 2021 Summer 114 2021 Fall 123 What is the slope of the trend equation obtained by linear regression? Round to two decimal digits. What is the intercept of the trend equation obtained by linear regression? Round to two decimal digits. What is the seasonal index for Spring? Round to two decimal digits. The quarter number for Winter of 2018 is 1. What is the quarter number for Spring of 2025? What is the trend based forecast for Spring of 2025. Round to a whole number. What is the seasonally adjusted trend based forecast for Spring of 2025? Please do not use excel to find the slope and intercept, thank you so much!

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