... 1.9 Brown's, a local bakery, is worried about increased costsparticularly energy. Last year's records can provide a fairly good estimate of the parameters for this year. Wende Brown, the owner, does not believe things have changed much, but she did invest an additional $3,000 for modifications to the bakery's ovens to make them more energy efficient. The modifications were supposed to make the ovens at least 15% more efficient. Brown has asked you to check the energy savings of the new ovens and also to look over other measures of the bakery's productivity to see if the modifications were beneficial. You have the following data to work LAST YEAR | NOW with: [PX] Production {dozen) 1,500 1,500 Labor (hours) 350 325 Capital investment () | 15,000 18,000 Energy (BTU) 3,000 2,750 .. 1.15 In December, General Motors produced 6,600 customized vans at its plant in Detroit. The labor productivity at this plant is known to have been 0.10 vans per labor-hour during that month. 300 laborers were employed at the plant that month. a. How many hours did the average laborer work that month? b. If productivity can be increased to 0.11 vans per labor-hour, how many hours would the average laborer work that month? ... 2.12 Rao Technologies, a California-based high-tech manufacturer, is considering outsourcing some of its electronics production. Four firms have responded to its request for bids, and CEO Mohan Rao has started to perform an analysis on the scores his OM team has entered in the table below. Ratings Of Outsource Providers FACTOR WEIGHT Labor Quality procedures Logistics system Price Trustworthiness Technology in place Management team Weights are on a scale from 1 through 30, and the outsourcing provider scores are on a scale of 1 through 5. The weight for the labor factor is shown as a w because Rao's OM team cannot agree on a value for this weight. For what range of values of w, if any, is company C a recommended outsourcing provider, according to the factor-rating method? .. 4.6 The monthly sales for Yazici Batteries, Inc., were as follows: MONTH SALES January 20 February 21 March 15 April 14 May 13 June 18 July 17 August 18 September 20 October 20 November 21 December 23 a. Plot the monthly sales data. b. Forecast January sales using each of the following: i. Naive method. i. A 3-month moving average. ili. A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months. iv. Exponential smoothing using an o = .3 and a September forecast of 18. v. A trend projection. c. With the data given, which method would allow you to forecast next March's sales? [PX]. 4.29 The number of disk drives (in millions) made at a plant in Taiwan during the past 5 years follows: YEAR | DISK DRIVES 140 a. Forecast the number of disk drives to be made next year, using linear regression. b. Compute the mean squared error (MSE) when using linear regression. . Compute the mean absolute percent error (MAPE). [PX] .. 4.48 Janice Carrillo, a Gainesville, Florida, real estate developer, has devised a regression model to help determine residential housing prices in northeastern Florida. The model was developed using recent sales in a particular neighborhood. The price (Y) of the house is based on the size (square footage = X) of the house. The model is: Y =13473 +37.65X The coefficient of correlation for the model is 0.63. a. Use the model to predict the selling price of a house that is 1,860 square feet. b. An 1,860-square-foot house recently sold for $95,000. Explain why this is not what the model predicted. c. If you were going to use multiple regression to develop such a model, what other quantitative variables might you include? d. What is the value of the coefficient of determination in this problem? [PX] .. 4.53 Thirteen students entered the business program at Sante Fe College 2 years ago. The following table indicates what each student scored on the high school SAT math exam and their grade-point averages (GPAs) after students were in the Sante Fe program for 2 years: STUDENT A G SAT SCORE | 421 415 GPA 2.90 2.15 STUDENT H I J K L M SAT SCORE | 481 729 | 501 613 | 709 | 366 GPA 253 | 3.22 | 1.99 | 2.75 | 3.90 | 1.60 a. Is there a meaningful relationship between SAT math scores and grades? b. If a student scores a 350, what do you think his or her GPA will he? c. What about a student who scores 8007