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Budget Analysis: A budget is an expression of management's expectations and goals concerning future revenues and costs. To increase their effectiveness, many budgets are flexible, including allowances for the effect of variation in uncontrolled variables. For example, the costs and revenues of many production plants are greatly affected by the number of units produced by the plant during the budget period, and this may be beyond a plant manager's control. Standard cost- accounting procedures can be used to adjust the direct-cost parts of the budget for the level of production, but it is often more difficult to handle overhead. In many cases, statistical methods are used to predict or forecast overhead from the level of production using historical data. As a simple example, consider the historical data for a certain plant. Enter the data into EXCEL and analyze it to answer the following items. (a) Construct a scatterplot of y versus x. (b) State the model equation. a. PRODUCTION = + OVERHEAD 0 1 b. OVERHEAD = PRODUCTION 1 c. PRODUCTION = OVERHEAD1 d. PRODUCTION = + OVERHEAD 1 0 e. OVERHEAD = + PRODUCTION 0 1 f. OVERHEAD = + PRODUCTION 1 0 In the model equation above, what does OVERHEAD represent? a. The predicted value of the predictor variable b. The predicted value of the explanatory variable c. The predicted value of the response variable d. The predicted value of the independent variable In the model equation above, what does represent? 0 a. The model intercept b. The response variable c. The explanatory variable d. The slope associated with the explanatory variable In the model equation above, what does represent? 1 a. The slope associated with the explanatory variable b. The response variable c. The model intercept d. The explanatory variable In the model equation above, what is the x-variable? a. The response variable PRODUCTION b. The explanatory variable OVERHEAD c. The explanatory variable PRODUCTION d. The response variable OVERHEAD Provide the sample-based estimates for the model parameters. (Round your answers to three decimal places.) = _____ +________ x (c) Graph the regression line on the scatterplot. (d) Use the model to predict the overhead cost associated with the production of 50,000 units. (Round your answer to two decimal places.) $ _______ The actual overhead cost was $13,000 when 50,000 units were produced (See the raw data above). Calculate the residual. (Round your answer to two decimal places.) $ _______ Interpret the residual you calculated immediately above by mentally inserting the ABSOLUTE VALUE of the residual into the blanks below. a. When using this model to make predictions, we expect to be _______ units closer to the true value, on average. b. Our prediction was _______ units higher than the actual overhead cost when 50,000 units were produced. Our prediction was an underestimate. c. Our prediction was _______ units lower than the actual overhead cost when 50,000 units were produced. Our prediction was an ov.

- 1. Budget Analysis: A budget is an expression of management's expectations and goals concerning future revenues and costs. To increase their effectiveness, many budgets are flexible, including allowances for the effect of variation in uncontrolled variables. For example, the costs and revenues of many production plants are greatly affected by the number of units produced by the plant during the budget period, and this may be beyond a plant manager's control. Standard cost- accounting procedures can be used to adjust the direct-cost parts of the budget for the level of production, but it is often more difficult to handle overhead. In many cases, statistical methods are used to predict or forecast overhead from the level of production using historical data. As a simple example, consider the historical data for a certain plant. Enter the data into EXCEL and analyze it to answer the following items. (a) Construct a scatterplot of y versus x. (b) State the model equation. a. PRODUCTION = 0 + 1 OVERHEAD b. OVERHEAD = 1 PRODUCTION c. PRODUCTION = 1 OVERHEAD d. PRODUCTION = 1 + 0 OVERHEAD e. OVERHEAD = 0 + 1 PRODUCTION f. OVERHEAD = 1 + 0 PRODUCTION In the model equation above, what does OVERHEAD represent? a. The predicted value of the predictor variable b. The predicted value of the explanatory variable c. The predicted value of the response variable d. The predicted value of the independent variable In the model equation above, what does 0 represent? a. The model intercept b. The response variable c. The explanatory variable d. The slope associated with the explanatory variable In the model equation above, what does 1 represent? a. The slope associated with the explanatory variable b. The response variable c. The model intercept d. The explanatory variable In the model equation above, what is the x-variable?
- 2. a. The response variable PRODUCTION b. The explanatory variable OVERHEAD c. The explanatory variable PRODUCTION d. The response variable OVERHEAD Provide the sample-based estimates for the model parameters. (Round your answers to three decimal places.) = _____ +________ x (c) Graph the regression line on the scatterplot. (d) Use the model to predict the overhead cost associated with the production of 50,000 units. (Round your answer to two decimal places.) $ _______ The actual overhead cost was $13,000 when 50,000 units were produced (See the raw data above). Calculate the residual. (Round your answer to two decimal places.) $ _______ Interpret the residual you calculated immediately above by mentally inserting the ABSOLUTE VALUE of the residual into the blanks below. a. When using this model to make predictions, we expect to be _______ units closer to the true value, on average. b. Our prediction was _______ units higher than the actual overhead cost when 50,000 units were produced. Our prediction was an underestimate. c. Our prediction was _______ units lower than the actual overhead cost when 50,000 units were produced. Our prediction was an overestimate. d. Our prediction was _______ units higher than the actual overhead cost when 50,000 units were produced. Our prediction was an overestimate. e. Our prediction was _______ units lower than the actual overhead cost when 50,000 units were produced. Our prediction was an underestimate. f. When using this model to make predictions, we expect to be off by _______ units, on average. (e) Use the model to predict the overhead cost associated with the production of 100,000 units. (Round your answer to five decimal places.) _________thousands of dollars The actual overhead cost was $15,100 when 100,000 units were produced (See the raw data above). Calculate the residual. (Round your answer to five decimal places.) ________thousands of dollars Interpret the residual you calculated immediately above by mentally inserting the ABSOLUTE VALUE of the residual into the blanks below. a. Our prediction was _______ units higher than the actual overhead cost when 50,000 units were produced. Our prediction was an underestimate. b. When using this model to make predictions, we expect to be off by _______ units, on average. c. When using this model to make predictions, we expect to be _______ units closer to the true
- 3. value, on average. d. Our prediction was _______ units higher than the actual overhead cost when 100,000 units were produced. Our prediction was an overestimate. e. Our prediction was _______ units lower than the actual overhead cost when 100,000 units were produced. Our prediction was an underestimate. f. Our prediction was _______ units lower than the actual overhead cost when 50,000 units were produced. Our prediction was an overestimate. Production (in 10,000) units: 5 6 7 8 9 10 11 Overhead costs (in $1,000): 13 11.6 14 15 15.7 15.1 17.5