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: Number Sold 760 510 975 240 315 475 Price $2.60 $3.40 $1.90 $4.20 $3.10 $4.10 Using simple linear regression and given that the price per cup is $1.80, the forecasted demand for mocha latte coffees will be cups
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- Under what conditions might a firm use multiple forecasting methods?which of the following would be calculated variable from other data: 1. Product Sales Price 2. Product availability 3. Coupon Availability 4. Average Customer ratingIn your bar you find you had the following sales. Use this information to find your average value per ounce and your value for 15 1 L bottles sold. Drink Mint Julep Bourbon Shot Number Sold 25 95 Primary Spirit Volume in Oz 12 1.5 Drink Price $6.50 $3.00
- Outlet All Sales Tortilla Sales Madre's Tortilla Stocked Padre's Tortilla Stocked Store 1 $100,000 $1,000 Yes Yes Store 2 $75,000 $500 Yes Yes Store 3 $50,000 $300 Yes No Store 4 $40,000 $400 No Yes Weighted Distribution or Product Category Value (PCV) Distribution (%) Numerical 4: The marketers at Madre's Tortillas want to know the Product Category Value or Weighted Distribution (%) of their distribution network. How much is it?FOR THIS QUESTION PLEASE REFER TO 3rdTABLEConduct an ABC analysis on the following twelve items. SKU $ Value/Unit Annual Use (units) B 60 580 D 52 620 36 720 K 20 600 38 300 40 250 25 360 16 280 G 480 10 320 12 240 22 120The following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LO
- 105 Which of the following real estate mortgage transactions is subject to the TILA-RESPA Integrated Disclosure rule (TRID)? A) Reverse mortgage B) Home equity line of credit (HELOC) C) A single-family residence loan secured by real property D) Mortgage secured by a mobile home not attached to landUsing the following information, forecast the rooms sales for the next three months for a 750-room lodging operation: Month Days Occupancy % Average Room Rate Month 1 30 65 $155 Month 2 31 80 175 Month 3 30 95 185Café 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 $2.70 760 $3.50 510 $2.00 980 $4.20 250 $3.10 320 $4.05 480 a. Using these data, how many mocha latte coffees would be forecast to be sold according to simple linear regression if the price per cup were $2.80? [Select] What is the MAD? [Select] c. What is the Coefficient of Determination? [Select] [Select] 9 and what does that tell you?
- ABC 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 the naive approach.How would a fast-moving consumer good (FMCG) retailer use collaborative forecasting to improve supply chain performance? 1) manufacturer new product introductions can be better integrated with category assortment plans 2) retail promotional plans can be shared with suppliers to reduce the bullwhip effect 3) retail promotional plans can be shared with suppliers to ensure adequate availability 4) all of the aboveIf ABC Corporation has following historical data about sales volume: Years Sales Years Sales Years Sales Years Sales 2001 110 2006 99 2011 100 2016 110 2002 112 2007 101 2012 104 2017 111 2003 122 2008 95 2013 108 2018 109 2004 111 2009 98 2014 102 2019 114 2005 104 2010 96 2015 115 2020 112 Note: All the sale values are in thousands. Required: Which type of forecasting approach is suitable for this type of data? Which forecasting technique is best to employ in order to forecast the above data? And also define the suggested technique. Calculate the predicted values by employing the discussed technique in part (b) on the above data.