The H.W. Grant Corporation used regression analysis to predict the annual cost of indirect materials. The results were as follows: Indirect Materials Cost Explained by Units Produced Constant $15,675 Standard error of Y estimate $3,500 0.7776 Number of observations 16 X coefficient(s) 10.25 Standard error of coefficient(s) 2.195 What is the cost estimation equation? O A. Y= $12,175 + $10.25X O B. Y= $3,500 + $7.97X O C. Y= $19,175 + $4.67X O D. Y= $15,675 + $10.25X
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- Scenario 4 Sharon Gillespie, a new buyer at Visionex, Inc., was reviewing quotations for a tooling contract submitted by four suppliers. She was evaluating the quotes based on price, target quality levels, and delivery lead time promises. As she was working, her manager, Dave Cox, entered her office. He asked how everything was progressing and if she needed any help. She mentioned she was reviewing quotations from suppliers for a tooling contract. Dave asked who the interested suppliers were and if she had made a decision. Sharon indicated that one supplier, Apex, appeared to fit exactly the requirements Visionex had specified in the proposal. Dave told her to keep up the good work. Later that day Dave again visited Sharons office. He stated that he had done some research on the suppliers and felt that another supplier, Micron, appeared to have the best track record with Visionex. He pointed out that Sharons first choice was a new supplier to Visionex and there was some risk involved with that choice. Dave indicated that it would please him greatly if she selected Micron for the contract. The next day Sharon was having lunch with another buyer, Mark Smith. She mentioned the conversation with Dave and said she honestly felt that Apex was the best choice. When Mark asked Sharon who Dave preferred, she answered, Micron. At that point Mark rolled his eyes and shook his head. Sharon asked what the body language was all about. Mark replied, Look, I know youre new but you should know this. I heard last week that Daves brother-in-law is a new part owner of Micron. I was wondering how soon it would be before he started steering business to that company. He is not the straightest character. Sharon was shocked. After a few moments, she announced that her original choice was still the best selection. At that point Mark reminded Sharon that she was replacing a terminated buyer who did not go along with one of Daves previous preferred suppliers. What should Sharon do in this situation?Scenario 4 Sharon Gillespie, a new buyer at Visionex, Inc., was reviewing quotations for a tooling contract submitted by four suppliers. She was evaluating the quotes based on price, target quality levels, and delivery lead time promises. As she was working, her manager, Dave Cox, entered her office. He asked how everything was progressing and if she needed any help. She mentioned she was reviewing quotations from suppliers for a tooling contract. Dave asked who the interested suppliers were and if she had made a decision. Sharon indicated that one supplier, Apex, appeared to fit exactly the requirements Visionex had specified in the proposal. Dave told her to keep up the good work. Later that day Dave again visited Sharons office. He stated that he had done some research on the suppliers and felt that another supplier, Micron, appeared to have the best track record with Visionex. He pointed out that Sharons first choice was a new supplier to Visionex and there was some risk involved with that choice. Dave indicated that it would please him greatly if she selected Micron for the contract. The next day Sharon was having lunch with another buyer, Mark Smith. She mentioned the conversation with Dave and said she honestly felt that Apex was the best choice. When Mark asked Sharon who Dave preferred, she answered, Micron. At that point Mark rolled his eyes and shook his head. Sharon asked what the body language was all about. Mark replied, Look, I know youre new but you should know this. I heard last week that Daves brother-in-law is a new part owner of Micron. I was wondering how soon it would be before he started steering business to that company. He is not the straightest character. Sharon was shocked. After a few moments, she announced that her original choice was still the best selection. At that point Mark reminded Sharon that she was replacing a terminated buyer who did not go along with one of Daves previous preferred suppliers. Ethical decisions that affect a buyers ethical perspective usually involve the organizational environment, cultural environment, personal environment, and industry environment. Analyze this scenario using these four variables.Scenario 4 Sharon Gillespie, a new buyer at Visionex, Inc., was reviewing quotations for a tooling contract submitted by four suppliers. She was evaluating the quotes based on price, target quality levels, and delivery lead time promises. As she was working, her manager, Dave Cox, entered her office. He asked how everything was progressing and if she needed any help. She mentioned she was reviewing quotations from suppliers for a tooling contract. Dave asked who the interested suppliers were and if she had made a decision. Sharon indicated that one supplier, Apex, appeared to fit exactly the requirements Visionex had specified in the proposal. Dave told her to keep up the good work. Later that day Dave again visited Sharons office. He stated that he had done some research on the suppliers and felt that another supplier, Micron, appeared to have the best track record with Visionex. He pointed out that Sharons first choice was a new supplier to Visionex and there was some risk involved with that choice. Dave indicated that it would please him greatly if she selected Micron for the contract. The next day Sharon was having lunch with another buyer, Mark Smith. She mentioned the conversation with Dave and said she honestly felt that Apex was the best choice. When Mark asked Sharon who Dave preferred, she answered, Micron. At that point Mark rolled his eyes and shook his head. Sharon asked what the body language was all about. Mark replied, Look, I know youre new but you should know this. I heard last week that Daves brother-in-law is a new part owner of Micron. I was wondering how soon it would be before he started steering business to that company. He is not the straightest character. Sharon was shocked. After a few moments, she announced that her original choice was still the best selection. At that point Mark reminded Sharon that she was replacing a terminated buyer who did not go along with one of Daves previous preferred suppliers. What does the Institute of Supply Management code of ethics say about financial conflicts of interest?
- The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?Calculate a regression line for the data and indicate the forecast of sales for a store with advertising spending of R240,000? and R300,000? Store Advertising Sales 1 14 6 2 11 3 3 15 5 4 16 5 5 24 15 6 28 18 7 22 17 8 21 12 9 26 15 10 43 20 11 34 14 12 9 52. Given the data below, forecast Year Mileage 3000 3800 3500 3800 3700 12345 a. the 6th year using the weighted moving average w/weights.7.&.3 b.The 6th year using Exponential Smoothing with F1 =3000 and alpha = .7 c.Calculate the MAD for a and b, tell me which one is the best model d. Calculate the regression line, the forecast for the 6th and the 12th years, the residual of the 4th year, and tell me if it is s good or a bad model
- Q1: Income at the architectural firm Spraggins and Yunes for the period February to July was as follows: Month February March April May June July 72.8 Income (in $ 70.0 thousand) 68.5 64.5 71.7 71.3 Use trend-adjusted exponential smoothing to forecast the firm's August income. Assume that the initial forecast average for February is $65,000 and the initial trend adjustment is 0. The smoothing constants selected are a = .1 and B =.2.Q3. Find forecasted value for 2017 using a = 0.5 and a = 0.7 using exponential smoothing method. Which a is better (10 Years Sales Forecasted sale 2012 25 2013 17 2014 2015 30 2016 27 2017 21Lenovo uses the ZX-81 chip in some of its laptop computers. The prices for the chip during the past 12 months were as follows: a) Use a 2-month moving average on all the data and plot the averages and the prices.b) Use a 3-month moving average a nd add the 3-month plot to the graph created in part (a).c) Which is better (using the mean absolute deviation): the 2-month average or the 3-month average?d) Compute the forecasts for each month using exponential smoothing, with an initial forecast for January of $1.80. Use a = .I, then a = .3, and finally a = .5. Using MAD, whicha is the best?
- Regression and Utility Rates; Sustainability For several years, many utilities haveemployed regression analysis to forecast monthly utility usage by residential customers usingweather forecasts, the number of holidays, the number of days in the month, and other factors.For example, the Connecticut Department of Public Utility Control (CDPUC) has determinedthat regression, properly used, can accurately predict natural gas usage. Most public gas utilities serving Connecticut have reported levels of accuracy from 4% to 10% using regression.One company, Dominion Natural Gas Company of Ohio, uses this approach not to forecast, butto explain to customers why their natural gas bills have gone up or down compared to the priormonth and to the same month of the prior year. The bill shows total MCF (thousand cubic feetof natural gas) used by the customer for that month and why the total MCF usage has changed,based on three factors:1. Change in temperature. Each degree increase in temperature…Make a 15-year simple linear regression forecast. Example: Railroad Products Co. RPC Sales Car Loadings Year ($millions) (millions) 1 9.5 120 2 11.0 135 3 12.0 130 4 12.5 150 5 14.0 170 6 16.0 190 7 18.0 220Lenovo uses the ZX-81 chip in some of its laptopcomputers. The prices for the chip during the past 12 monthswere as follows: a) Use a 2-month moving average on all the data and plot theaverages and the prices.b) Use a 3-month moving average and add the 3-month plot tothe graph created in part (a).c) Which is better (using the mean absolute deviation): the2-month average or the 3-month average?d) Compute the forecasts for each month using exponentialsmoothing, with an initial forecast for January of $1.80. Use a= .1, then a = .3, and finally a = .5. Using MAD, which ais the best?
