Understanding Key Forecasting Techniques: Regression & Learning Curves

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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.

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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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Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity A. Expected value analysis assumes that there will be no changes in past performance in the future (for example, efficiency will not improve). B. Expected value analysis can only be used when performance is expected to be within the relevant range of activity. C. Expected value measures the “average” outcome of a situation. D. Expected value analysis cannot be used when it is difficult to accurately measure the impact of efficiency improvements. Question 17 Wall, Corp. (Wall) is the leading manufacturer of drywall in the United States. Wall is trying to predict total sales revenue for next year. A new competitor has announced plans to begin selling a new and improved type of drywall starting next year. Wall believes the new product has a 50% chance of lowering sales of 8' by 4' sheets of drywall, their only product, from 1,235,305 sheets to 1,054,255 sheets. If turns out that the new product does reduce Wall's sales volume, there is a 20% chance that Wall will also be forced to reduce its price of $15.00 per sheet to $13.50 per sheet in order to stay competitive at the new sales volume of 1,054,255 sheets. Based on these estimates, what is the expected sales revenue for next year? A. $17,171,700.00 B. $18,529,575.00 C. $17,013,561.75 D. $17,603,096.25 Question 18 Which of the following is a benefit of linear regression analysis? A. Linear regression analysis can be used to help predict costs at various levels of output. B. Linear regression analysis assumes the relationship between the dependent variable and independent variable is linear. C. Linear regression analysis can be used to predict performance that is within the range of data used to develop the regression equation. D. Linear regression analysis can be used to estimate the time and cost to perform an activity under the assumption that people become more efficient the more times they perform the task. Question 19 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 29 hours to make the first batch of 100 8' by 4' sheets. Wall estimates the learning rate to be 75%. Forecast the cumulative average time per batch to make the first seven batches of 8' by 4' sheets, and use that average to determine the total production time to make these seven batches of sheets? A. 589.77 hours B. 203 hours C. 90.52 hours

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity D. 12.93 hours Question 20 The Andrew 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 Andrew? A. $7,900,000 B. $7,000,000 C. $8,000,000 D. $10,000,000. Question 21 The Dana Hotel prepares the following distribution of expected visitors for various economic conditions and the probability of those conditions. What is the expected number of visitors for Dana? A. 9,000 B. 18,000 C. 10,200 D. 10,000 Question 22 Connor's Shirt Shop performed a regression analysis on its delivery costs for the previous 12 months. The number of deliveries during those 12 months ranged from 10,000 deliveries to 15,000 deliveries. The regression analysis yielded an intercept of $9,000, a coefficient on deliveries of $3.50, and an R squared of 92.6%. If Connor expects to make 14,000 deliveries in the next month, what would Connor estimate total delivery costs to be? A. $53,708 B. $44,000 C. $49,000 D. $58,000 Question 23 A regression analysis of production costs produced the following output: Based on these results, what is the estimated cost for a production level of 1,200 units? A. $47,763 B. $55,394 C. $7,636

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity D. $40,120 Question 24 Tough Tables (TT) plans to begin manufacturing a new line of indestructible tables by the end of the year. Their target customers are families with small children. TT believes that the first table will take them 17 hours to manufacture and estimates the learning rate to be 85%. Forecast the cumulative average time per table to make the first five tables, and use that average to determine the total production time to make the first five tables. A. 58.28 hours B. 85 hours C. 99.65 hours D. 11.66 hours Question 25 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. Which measure from the regression analysis result is the best indicator of how much we understand about total costs in the dataset based on the volume of phone production in the dataset? A. R Square of 0.81 B. Adjusted R Square of 0.78 C. Multiple R of 0.90 D. Standard Error of $87,127

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Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity Question 26 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. Evaluate the estimate for total fixed costs. A. B. C. D. Question 27 A company implements a new process to manufacture its product and spends $500 on labor to produce 50 units. 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, what will be the total labor cost to produce 200 units? A. $1,280 B. $320 C. $1,024 D. $1,600

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity Question 28 Wall, Corp. (Wall) is the leading manufacturer of sheetrock in the United States. Wall is trying to forecast direct material costs for next year. The cost of calcium sulfate dihydrate (gypsum) used in sheetrock production fluctuates from year to year. Below are Wall's estimates for the cost of a pound of gypsum next year. Based on these estimates, what is the expected cost per pound of gypsum next year? A. $1.45 B. $1.73 C. $1.85 D. $1.76 Question 29 BusyBee Cleaning Co. is evaluating its costs to clean a standard office. The controller has done a linear regression of the hours spent cleaning various offices and the total costs (labor, supplies, transportation) for each office cleaned. The regression analysis yielded the following information. What is the best description of the costs of cleaning an office based on this regression analysis? A. The cost is $100 per hour to clean an office. B. There is $25 of fixed costs and $75 of variable costs per hour to clean an office. C. There is $25 of variable costs per hour and $75 of fixed costs to clean an office. D. The cost is $25 per hour to clean an office. Question 30 Which of the following is not a benefit of learning curve analysis? A. Learning curve analysis can be used to help predict costs at various levels of output. B. Learning curve analysis assumes efficiency improvements are greatest when production begins and decrease as production increases. C. Learning curve analysis can incorporate various rates of efficiency improvements depending on circumstances. D. Learning curve analysis takes into consideration that people tend to get more efficient at performing a task the more times they perform the task. Question 31 Which of the following concerning simple linear regression analysis is not correct? A. A higher coefficient of determination (R-squared) is preferred to a lower one since it measures the amount of variability in the dependent variable explained by changes in the independent variable.

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity B. A higher t-value for the independent variable coefficient is preferred to a lower one since it measures the statistical significance of the relationship between an independent variable and dependent variable. C. If a new piece of energy-efficient equipment is purchased, a regression analysis performed using past data on energy usage and units produced is not valid for predicting energy usage and various levels of production. D. The coefficient of t he “intercept” resulting from a regression analysis where marketing expenditures ranging from $10,000 per month to $20,000 per month and sales ranging from $250,000 per month to $600,000 per month are used is the estimated sales when marketing expenditures are zero. Question 32 Calhat, Inc. is beginning the production of a new product to be used in cargo ships. Management believes that the company will experience a learning curve of 80% on production. Production of the first unit required 8,000 direct labor hours. If eight units are planned for production, the cumulative average direct labor hours per unit of the product will be A. 5,120 hours. B. 1,678 hours. C. 4,096 hours D. 5,346 hours Question 33 Finish the following sentence: Learning curve analysis is focused on the ____________ improvement rather than on the ____________ improvement for each unit of output. A. Curved; flat B. Cumulative average; individual C. Individual; cumulative average D. Flat; curved Question 34 Eight quarters of production data from Pear, Inc., a cell phone manufacturing company, are presented below.

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Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity 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 that includes two shutdowns. A. Between $3,033,820 and $3,702,224 B. $3,368,022 C. Between $3,276,484 and $3,459,560 D. $3,368,022 Between $3,276,484 and $3,459,560 Question 35 An electronics company has developed a regression model to forecast quarterly sales. The model explains the relationship between the company’s sales and the amount it spends on marketing activities. The regression equation for the model is expressed below. s = $3(m) + $150,000 where: s = sales per quarter m = total dollars spent on marketing activities per quarter If the company has forecasted sales of $189,000 for the next quarter, what amount is it planning to spend on marketing activities in the next quarter? A. $13,000 B. $39,000 C. $63,000 D. $113,000 Question 36 Which of the following is a benefit of learning curve analysis? A. Learning curve analysis can be used to help predict costs at various levels of output. B. Learning curve analysis assumes efficiency improvements are greatest when production begins and decrease as production increases. C. Learning curve analysis produces diagnostic statistics that can be used to evaluate the quality of the analysis.

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity D. Learning curve analysis assumes all improvements in production efficiency are caused by employee learning. Question 37 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, what is the average time per unit when producing two batches? A. 80 hours B. 60 hours C. 90 hours D. 160 hours Question 38 Which of the following statements is not true? A. A multiple linear regression is likely to be more difficult to interpret than a simple linear regression model. B. A multiple linear regression is likely to be more accurate than a simple linear regression model. C. A multiple linear regression is likely to be less costly than a simple linear regression model to develop. D. Multi-collinearity can be a problem in multiple linear regression but not in simple linear regression. Question 39 Which of the following is a benefit of expected value analysis? A. Expected value analysis assumes a decision-maker is risk neutral. B. Expected value analysis provides a way to predict future costs using past data. C. Expected value measures the “average” outcome of a si tuation. D. Expected value analysis attempts to apply objectivity to uncertain situations. Question 40 Gill's Golf Gear (GGG) conducted a regression analysis on its shipping costs for the last year, which resulted in the following equation: $2.30x + $375. If GGG plans to ship 320 boxes of golf balls next month, what are the shipping costs expected to be? A. $377.30 B. $736.00 C. $862.50 D. $1,111.00 Question 41 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 complete four batches?

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity A. 256 hours B. 204.8 hours C. 400 hours D. 64 hours Question 42 The Urban 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 $240,000, should Urban make the investment? A. Yes, because the expected net cash flow from the investment is $260,000. B. Yes, because the expected net cash flow from the investment is $250,000. C. No, because there is a chance that the net cash flow from the investment will be an outflow of $140,000. D. Yes, because the most likely net cash flow from the investment is $160,000. Question 43 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. Describe the confidence interval for the variable cost per phone as found in the regression analysis results. A. There is a 95% probability that the variable cost per phone is between $379 and $1,097. B. There is a 5% probability that the variable cost per phone is between $379 and $1,097.

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Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity C. There is a 95% probability that the variable cost per phone is less than $379 or greater than $1,097. D. There is a 95% probability that the variable cost per phone is between $738 and $1,097 Question 44 Which of the following is a shortcoming of learning curve analysis? A. Learning curve analysis assumes the learning rate is constant. B. Because learning curve analysis is not working to anticipate where costs are moving, organizations are unable to establish more relevant budgets with appropriate stretch targets. C. Learning curve analysis is focused on machine learning. Hence, learning curve analysis may not be relevant to more human-intensive processes. D. Learning curve analysis is anticipating movement in future costs by recognizing that the organization is learning and becoming more efficient with its processes. Question 45 Which of the following is not a limitation of linear regression analysis? A. Linear regression analysis assumes that there will be no changes in past performance in the future (for example, efficiency will not improve). B. Linear regression analysis can only be used to predict performance that is within the range of data used to develop the regression equation. C. Linear regression analysis assumes the relationship between the dependent variable and independent variable is linear. D. Regression analysis cannot be used when it is difficult to accurately measure the impact of efficiency improvements. Question 46 A company uses regression analysis in which monthly advertising expenses are used to predict monthly product sales, both in millions of dollars. The results show a regression coefficient for the independent variable equal to 0.8. This coefficient value indicates that A. on average, every additional dollar of advertising results in $0.8 of additional sales. B. advertising is not a good predictor of sales because the coefficient is so small. C. when monthly advertising is at its average level, product sales will be $800,000. D. the average monthly advertising expenditure in the sample is $800,000. Question 47 Which of the following is a benefit of expected value analysis? A. Expected value analysis can be used to separate a mixed cost into its fixed and variable components. B. Expected value analysis can be used to estimate the time and cost to perform an activity under the assumption that people become more efficient the more times they perform the task. C. Expected value analysis can be used to help predict costs at various levels of output. D. Expected value analysis attempts to apply objectivity to uncertain situations.

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity Question 48 A company implements a new process to manufacture its product and spends $400 on labor to produce one batch. It expects that the new process will be subject to a 70% learning curve. If the company assumes the learning curve will follow the cumulative average-time learning model, what will be the total labor cost to produce 200 units if each batch is 100 units? A. $560 B. $160 C. $680 D. $280 Question 49 Which of the following correctly describes the use of the output from a simple linear regression analysis? A. The coefficient of the “intercept” is the estimate of variable amount per unit of the independent variable and the coefficient on the independent variable is the estimate of the fixed component of the dependent variable. B. The coefficient of the “intercept” is the estimate of the fixed component of the dependent variable and the coefficient on the independent variable is the estimate of variable amount per unit of the independent variable. C. The coefficient of the “intercept” is the estimate of the total amount of the dependent variable and the coefficient on the independent variable is the estimate of the variable amount per unit of the independent variable. D. The coefficient of the “intercept” is the estimate of the fixed component of the dependent variable and the coefficient on the independent variable is the estimate of the amount of variability explained by the regression equation. Question 50 Which of the following is 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 can only be used to predict performance that is within the range of data used in the analysis. C. Learning curve analysis assumes a decision-maker is risk neutral. D. Learning curve analysis assumes that there will be no changes in past performance in the future. Question 51 Ben's Toy Shop performed a regression analysis on its shipping costs for the previous 12 months. The number of units shipped during those 12 months ranged from 1,500 units to 2,150 units. The regression analysis yielded an intercept of $10,000, a coefficient on units shipped of $25, and an R-squared of 94.2%. If Ben expects to ship 1,800 units in the next month, what would Ben estimate total shipping costs to be? A. $51,810 B. $55,000

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity C. $45,000 D. $63,750 Question 52 Which of the following is a limitation of regression analysis? A. Regression analysis measures the “average” out come of a situation. B. Regression analysis can only be used to predict performance that is within the range of data used to develop the regression equation. C. Regression analysis assumes all improvements in production efficiency are caused by employee learning. D. Regression analysis cannot be used when it is difficult to accurately measure the impact of efficiency improvements. Question 53 A toy company is in the process of forecasting sales for a new toy. The company has the following estimates of unit sales with a corresponding probability distribution. How many units should the company forecast for sales of the new toys? A. 350,000 B. 433,750 C. 458,250 D. 1,375,000 Question 54 In a simple linear regression equation where units produced is used to predict electricity costs, which of the following is true? A. Units produced is the independent variable and electricity costs is the dependent variable. B. Units produced is the dependent variable and electricity costs is the independent variable. C. Units produced and electricity costs are both independent variables. D. Units produced and electricity costs are both dependent variables. Question 55 In a simple linear regression equation where advertising expenditures is used to predict sales, which of the following is true? A. Advertising expenditures is the independent variable and sales is the dependent variable. B. Advertising expenditures is the dependent variable and sales is the independent variable. C. Advertising expenditures and sales are both independent variables. D. Advertising expenditures and sales are both dependent variables. Question 56 A corporation has determined that when the quantity produced in units doubles from x to 2x, the

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Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity average time per unit for 2x units is 90% of the average time per unit for x units. The decline in time per unit as production doubles is an example of the: A. incremental unit-time learning model. B. cumulative average-time learning model. C. high-low cost estimation model. D. simple regression cost estimation model. Question 57 The Tucker 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 $750,000 should Tucker make the investment? A. No, because the expected net cash flow from the investment is an outflow of $50,000. B. No, because the expected net cash flow from the investment is an outflow of $110,000. C. Yes, because there is a chance that the net cash flow from the investment will be an inflow of $550,000. D. Yes, because the expected net cash flow from the investment is an inflow of $1,350,000. Question 58 A manager is reviewing a potential investment that has significant uncertainty related to its ultimate financial outcome. The manager has estimated the following probabilities for the various levels of net cash flows that may result from the investment. What is the expected value of net cash flows that the manager should use in evaluating the investment? A. $100,000 B. $200,000 C. $140,000 D. $400,000 Question 59 The Nicholas Ski Lodge prepares the following distribution of expected visitors for various weather conditions and the probability of those conditions. What is the expected number of visitors for Nicholas? A. 40,000

Part 1 Forecasting Techniques Regression Analysis, Learning Curve, Expected Value, Sensitivity B. 85,000 C. 46,750 D. 50,000 Question 60 Which of the following is not a benefit of regression analysis? A. Regression analysis can be used to help predict costs at various levels of output. B. Regression analysis can be used to separate a mixed cost into its fixed and variable components. C. Regression analysis produces diagnostic statistics that can be used to evaluate the quality of the equation produced. D. Regression analysis can be used to estimate the time and cost to perform an activity under the assumption that people become more efficient the more times they perform the task.

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