Using the actual sales (in units) over the past 15 months, a demand planner at a leading e-commerce firm hasforecasted the demand for a popular consumer product as shown below. Forecast 1 and Forecast 2 represent theoutputs of two comparative forecasting methods currently used by the sales and marketing, and operationsdepartments of the firm.MonthOctober 22November 22December 22January 23February 23March 23April 23May 23June 23July 23August 23September 23October 23November 23December 23Actual sales (units)120 000138 000172 000120 000114 00098 000118 000112 000132 000138 000108 000126 000144 000162 000189 000QUESTION 24Determine the mean absolute deviation of Forecast 1.A 234 290 unitsa 18 721 unitsc 19 524 units22 670 unitsQUESTION 25Determine the mean absolute deviation of Forecast 2.A 21 638 unitsa 35 280 unitsc. 19 330 units23 600 unitsForecast 1 (units)133 280130 620127300121 440120 750119 000121 600124 900121 500122400126 720133 780Forecast 2 (units)143 330143 330135 330110 670110 000109 330120 670127 330126 000124 000126 000144 000

The question is about forecasting.Given :To find :24 ) Mean absolute deviation of forecast 125 )…

Answered: Using the actual sales (in units) over…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Use the Financial database from “Excel Databases.xls” on Blackboard. Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company. Use Excel to develop the multiple linear regression model. Assume a 5% level of significance. Which independent variable is the strongest predictor of the average P/E ratio of a company? A. Total Revenues B. Average Yield C. Earnings Per Share D.Return on Equity E. Total Assets F.Dividends Per Share Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287…
Forecasting: 1. How does the number of periods in moving average affect the responsiveness of the forecast? 2. Contrast the terms sales and demand. 3. KA commercial bakery has recorded sales (in dezens) for three products, as shown below: Blueberry MuHins Cinnamon Buns Day Cupcakes 30 18 45 34 17 26 32 19 27 34 23 35 2 22 30 23 48 23 29 34 36 25. 20 29 24 14 10 31 26 18 35 31 11 27 47 28 26 27 37 34 13 14 31 24 15 33 33 22 a. Predict orders for the following day for cach of the products using an appropriate naive method. b What should the use of sales data instead of demand imply. RNN N N N H.NM p
How do you figure this out using conjoint analysis in a linear regression? Determine how various attributes impact the purchase of a car. There are four attributes, each with three levels: Brand: Ford = 1, Chrysler = 2, GM = 3 MPG: 15 MPG = 1, 20 MPG = 2, 25 MPG = 3 Horsepower (HP): 100 HP = 1, 150 HP = 2, 200 HP = 3 Price: $18,000 = 1, $21,000 = 2, $24,000 = 3 The nine product profiles ranked in the data file were evaluated by a consumer. (a) For this market segment, rank the product attributes from most important to least important. Below is the data provided. Brand MPG Power Price Rank 1 1 1 1 4 1 2 2 3 7 1 3 3 2 3 2 1 2 2 6 2 2 3 1 2 2 3 1 3 9 3 1 3 3 8 3 2 1 2 5 3 3 2 1 1
Month Actual demand Forecasted Demand 1 950 1000 2 1070 1000 3 1100 1000 4 960 1000 5 1090 1000 6 1050 1000 For the dataset above, compute the overall MAPE.
As a sales analyst for the shoe retailer Foot Locker, one of your responsibilities is measuring store productivity and then reporting your conclusion back to management. Foot Locker uses sales per square foot as a measure of store productivity. While preparing your report for the second quarter results (Q2), you are able to determine that annual sales for last year ran at a rate of $406 per square foot. Therefore, $406 per square foot will be your sales estimate for the population of all Foot Locker stores during Q2. For your Q2 Sales Report, you decide to take a random sample of 64 stores. Using annual data from last year, you are able to determine that the standard deviation for sales per square foot for all 3,400 stores was $80. Therefore $80 per square foot will be your population standard deviation when compiling your Q2 report. Management has asked for the probability that your sample mean based on 64 stores is 1) within $15 and 2) within $5 of the population mean…
As a sales analyst for the shoe retailer Foot Locker, one of your responsibilities is measuring store productivity and then reporting your conclusion back to management. Foot Locker uses sales per square foot as a measure of store productivity. While preparing your report for the second quarter results (Q2), you are able to determine that annual sales for last year ran at a rate of $406 per square foot. Therefore, $406 per square foot will be your sales estimate for the population of all Foot Locker stores during Q2. For your Q2 Sales Report, you decide to take a random sample of 64 stores. Using annual data from last year, you are able to determine that the standard deviation for sales per square foot for all 3,400 stores was $80. Therefore $80 per square foot will be your population standard deviation when compiling your Q2 report. You anticipate that management would be comfortable with a probability of 0.500 when offering your estimate of the sample mean. Using σ = $80…
A group of researchers carried out a survey of household expenditure for an average family and the data are shown in Table 3. Table 3 Commodity 2016 2017 Quantity 105 Price Quantity 100 Price Rice (kg) Bread (loaf) Cocoa powder (kg) Milk (liter) Sugar (kg) 7.30 8.60 3.02 16 3.10 18 10.26 25 7.83 33 6.10 56 6.55 78 2.85 11 2.95 15 (i) Compute the Average Price Relative (APR) index for 2016 and 2017, using 2016 as the base year. (ii) Calculate Paasche Price Index for 2017 (year 2016 = 100). Interpret the answer. (iii) Calculate Laspeyres Price Index for 2017 (year 2016 = 100). Interpret the answer. (iv) Calculate the Fisher's Price index.
A biscuit production manager wants to investigate the linear relationship between the number of items produced and the production cost. To pursue his/her objective, the manager recorded the data on the number of items produced per day and the production cost per day (in thousands of Malaysian Ringgit) as shown in Table 3 Table 3 Days 1 2 4 6. 7 8 10 11 Number of items, (x) 26 67 86 17 10 44 53 40 77 80 20 20 Production cost, (y) 21 60 69 47 50 | 98 39 55 85 104 37 20 a) Name the TWo (2) most popular correlation coefficients. OPearson Oz-table OT-table Ochi-square Ospearman b) Calculate the correlation coefficient, r. ху x2 y2 26 21 676 44 60 2640 1936 3600 53 69 3657 2809 4761 47 1880 2209 77 50 3850 5929 2500 80 98 7840 6400 9604 20 39 780 400 1521 20 55 1100 400 3025 67 5695 4489 7225 86 104 8944 7396 10816 17 37 629 289 1369 10 20 200 100 400 E y² = Σχ ΣΥ- Σχy- Ex? = || || **Answer should be up to 4 decimal place (dp) r = c) Based on the correlation coefficient, robtained, make a…
An automobile manufacturer is considering mechanical design changes in one of its top-selling cars to reduce the weight of the car by at least 420 pounds to improve its fuel efficiency. Design engineers have identified 10 changes that could be made in the car to make it lighter (e.g., using composite body pieces rather than metal). The weight saved by each design change and the estimated costs of implementing each change are summarized in the following table. Design Change 1 2 3 4 6 7 8 10 Weight Saved (Ibs) 50 75 25 150 60 95 200 40 80 30 Cost (in $1,000s) 150 350 50 650 90 35 450 75 110 30 Changes 4 and 7 represent alternate ways of modifying the engine block and, therefore, only one of these options could be selected. The company wants to determine which changes to make in order to reduce the total weight of the car by at least 420 pounds in the least costly manner. (a) Formulate an ILP model for this problem to minimize cost (in thousands of dollars). (Let X, = 1 if design change i…
The following are historical demand data: ACTUAL YEAR 2011 SEASON DEMAND Spring 201 Summer 142 Fall 380 Winter 578 2012 Spring 469 Summer 273 Fall Winter 683 963 Use regression analysis on deseasonalized demand to forecast demand in summer 2013. (Do not round intermediate calculations. Round your answer to the nearest whole number.) Forecast for summer 2013
Use regression analysis on deseasonalized demand to forecast demand in summer 2013. Forecast for summer 2023 ______

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