Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity_Qs 19

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Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity Question 1 Which of the following is not a limitation of learning curve analysis? A. Learning curve analysis assumes that the percentage improvement from learning only fully occurs when production doubles. B. Learning curve analysis cannot be used when it is difficult to accurately measure the impact of efficiency improvements. C. Learning curve analysis assumes all improvements in production efficiency are caused by employee learning. D. Learning curve analysis can only be used to predict performance that is within the range of data used to develop the analysis. Question 2 How does a multiple linear regression equation differ from a simple linear regression equation? A. More than one independent variable is used to predict a dependent variable in a multiple linear regression equation but only one independent variable is used to predict a dependent variable in a simple linear regression equation. B. More than one dependent variable is predicted by a multiple linear regression equation but only one dependent variable is predicted in a simple linear regression equation. C. A multiple linear regression is likely to be less accurate than a simple linear regression model. D. A multiple linear regression is likely to be less difficult to interpret than a simple linear regression model. Question 3 Wall, Corp. (Wall) is the leading manufacturer of drywall in the United States. Wall is trying to predict cash flow for the next year. Depreciation of $1 million is included in cost of goods sold (COGS). There is no depreciation expense as part of selling, general and administration expense (SG&A). Wall is not forecasting any capital expenditures or change in net working capital. Wall's tax rate is 20%. Below are Wall's estimates in millions: Based on the above estimates, what will be Wall's after-tax cash flow for next year? A. $0.04 B. $0.05 C. $17.25 D. $1.04

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity Question 4 Eight quarters of production data from Pear, Inc., a cell phone manufacturing company, are presented below. The regression analysis results on these data are displayed below. Based on the regression analysis result above, and with approximately 68% confidence, predict the total cost to produce 2,500 phones next quarter. A. $3,318,119 B. Between $2,960,994 and $3,675,244 C. Between $3,230,992 and $3,405,246 D. Between $3,143,865 and $3,492,373 Question 5 Which of the following is a benefit of expected value computations? A. The underlying probabilities used in the expected value formula are usually based on subjective judgments. B. The expected value computation reduces multiple outcomes down to a single value, which is easily understood and can be entered into a budget plan. C. The expected value computation is the most likely outcome in the future. D. Expected value computations incorporate multiple possibilities, making them more representative of a certain future. Question 6 Eight quarters of production data from Pear, Inc., a cell phone manufacturing company, are presented below.

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity The regression analysis results on these data are displayed below. What does the Multiple R statistic represent in this analysis? A. The Multiple R statistic of 0.98 indicates how much we understand about total costs in the dataset based on the volume of phone production and number of shutdowns. The 0.98 statistic means that variance (change) in the phone production and number of shutdowns explains 98% of the variance (change) in total costs. B. The Multiple R statistic of 0.98 indicates how much we understand about total costs in the dataset based on the volume of phone production and number of shutdowns. The 0.98 statistic means that variance (change) in the phone production and number of shutdowns explains 2% of the variance (change) in total costs. C. The Multiple R statistic of 0.98 is the correlation of total costs, volume of phone production, and number of shutdowns. There is a 2% correlation between these numbers. D. The Multiple R statistic of 0.98 is the correlation of total costs, volume of phone production, and number of shutdowns. There is a 98% correlation between these numbers. Question 7 Which of the following is the proper formula for computing the cumulative average? A. The formula for c alculating the cumulative average is Y = aXb , where Y = cumulative average per unit, a = time required for first unit, X = cumulative number of units, and b = ln learning curve % ÷ ln 2. B. The formula for calculating the cumulative average is Y = aXb, where Y = cumulative average per unit, a = time required for first unit, X = cumulative number of units, and b = ln learning curve % ÷ ln 2. C. The formula for calculating the cumulative average is Y = abX b , where Y = cumulative average per unit, a = time required for first unit, X = cumulative number of units, and b = ln learning curve % ÷ ln 2.

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity D. The formula for calculating the cumulative average is Y = aXb , where Y = cumulative average per unit, a = time required for all units, X = cumulative number of units, and b = ln learning curve % ÷ ln 2. Question 8 The Madeline Company prepares the following distribution of sales forecasts for various economic conditions and the probability of those conditions. What is the expected value of sales for Madeline? A. $13,000,000 B. $13,100,000 C. $14,000,000 D. $5,000,000. Question 9 The Laney Company prepares the following distribution of cash flow forecasts for a possible investment under various economic conditions and the probability of those conditions. If the investment requires an initial investment of $150,000, should Laney make the investment? A. Yes, because the expected net cash flow from the investment is $50,000. B. Yes, because the expected net cash flow from the investment is $110,000. C. No, because there is a chance that the net cash flow from the investment will be an outflow of $550,000. D. Yes, because the most likely net cash flow from the investment is $150,000. Question 10 Wall, Corp. (Wall) is the leading manufacturer of drywall in the United States. A competitor has announced plans to begin selling a new and improved type of drywall starting next year. To compete and maintain their position as the leading manufacturer, Wall decided to start producing an improved type of drywall as well. When the production line started, it took 20 hours to make the first batch of 100 8' by 4' sheets. Wall estimates the learning rate to be 80%. Forecast the cumulative average time per batch to make the first four batches of 8' by 4' sheets, and use that average to determine the total production time to make these four batches of sheets. A. 12.8 hours B. 51.2 hours C. 80 hours D. 64 hours Question 11 The Joseph Company prepares the following distribution of net cash flows for a possible investment

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity under various economic conditions and the probability of those conditions. What is Joseph's expected net cash flow from this investment A. $2,270,000 B. $1,900,000 C. $2,000,000 D. $5,000,000. Question 12 Jamie's Jams conducted a regression analysis on its shipping costs for the last year, which resulted in the following equation: $3.25x + $115. If Jamie plans to ship 287 pints of jam next month, what are the shipping costs expected to be? A. $1,047.75 B. $932.75 C. $817.75 D. $118.25 Question 13 Eight quarters of production data from Pear, Inc., a cell phone manufacturing company, are presented below. The regression analysis results on these data are displayed below. What is the regression equation (total cost equation) for the above information?

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity A. Total costs = $1,080(Phones) + $466,096 B. Total costs = $24,675(Shut Downs) + $309,413 C. Total costs = $1,080(Phones) + $100,963(Shut Downs) + $466,096 D. Total costs = $114(Phones) + $24,675(Shut Downs) + $309,413 Question 14 A company implements a new process to manufacture its product and uses 100 hours to complete one unit. It expects that the new process will be subject to an 80% learning curve. If the company assumes the learning curve will follow the cumulative average-time learning model, how many total hours will be needed to produce the third and fourth batches? A. 256 hours B. 96 hours C. 160 hours D. 64 hours Question 15 Eight quarters of production data from Pear, Inc., a cell phone manufacturing company, are presented below. The regression analysis results on these data are displayed below. What is the regression equation (total cost equation) for the above information? A. Total costs = $147(Phones) + $356,978 B. Total costs = $1,473,119(Phones) + 738 C. Total costs = $356,978(Phones) + $147 D. Total costs = $738(Phones) + $1,473,119 Question 16 Which of the following is a limitation of expected value analysis?

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