Curry Rubber manufactures rubber bands for retail companies. The accounting manager has performed a regression analysis of past data. You notice that the formula has an R-squared of 0.68, a t-value of 2.2, and a standard error of the estimate of $218,200. The estimate for next quarter costs is $2,597,623. Calculate Standard Error as a % of predicted total cost which represents a measure of precision of his regression analysis? (Round your answer to one decimal place, i.e., 0.052 = 5.2%.)
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Curry Rubber manufactures rubber bands for retail companies. The
Standard error can be explained as deviation of sample distribution from its population.
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- Jensen Tire Auto is deciding whether to purchase a maintenance contract for its new computer wheel alignment and balancing machine. Managers feel that maintenance expense should be related to usage, and they collected the following information on weekly usage (hours) and annual maintenance expense (in hundreds of dollars). a. Develop a scatter chart with weekly usage hours as the independent variable. What does the scatter chart indicate about the relationship between weekly usage and annual maintenance expense? b. Use the data to develop an estimated regression equation that could be used to predict the annual maintenance expense for a given number of hours of weekly usage. What is the estimated regression model? c. Test whether each of the regression parameters 0 and 1 is equal to zero at a 0.05 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? d. How much of the variation in the sample values of annual maintenance expense does the model you estimated in part (b) explain? e. If the maintenance contract costs 3,000 per year, would you recommend purchasing it? Why or why not?Newport, Inc. used Excel to run a least-squares regression analysis, which resulted in the following output: Regression Statistics Multiple R R Square Observations 0.7225 0.8500 30 Coefficients Standard Error T Stat P-Value 0.021 Intercept Production (X) 31,000 5.87 3,493 2.86 0.4640 14.30 0.000 a. What is Newport's total fixed cost? Total Fixed Cost b. What is Newport's variable cost per unit? (Round your intermediate calculations to 2 decimal places.) Variable Cost per unit c. What total cost would Newport predict for a month in which they sold 5,000 units? Total Costs d. What proportion of variation in Newport's cost is explained by variation in production? (Round your intermediate calculations to 2 decimal places.) Proportion of VariationAssume you have asked your data folks to determine the relationship between customer service scores (i.e. the ratings provided by customers in response to a survey) and profit. The analyst reports the following: "I gathered data for the last 48 months and ran a regression where profit in a given month is the dependent variable and customer service score in that same month is the independent variable. I found an intercept of $10,000 (p-value: 0.31) and the coefficient on customer service score is $1,200 (p-value: 0.22). The R-2 (which is appropriate when there is just one independent variable) is 0.07." What do you infer from the results (two to three sentences, sticking to the information provided) and why?
- Company X tried selling widgets at various prices to see how much profit they would make. The following table shows the widget selling price, x, and the total profit earned at that price, y. Write a quadratic regression equation for this set of data, rounding all coefficients to the nearest tenth. Using this equation, find the profit, to the nearest dollar, for a selling price of 24.25 dollars. Price (x) Profit (y) 15.50 26727 18.50 36348 26.50 48488 35.75 54878 42.50 48488A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The data are stored in the accompanying table. The least-squares regression equation for these data is Y₁ = - 13,863.426 +2.437X, and the standard error of the estimate is Syx = 15,910.578. Assume that the straight-line model is appropriate and there are no serious violations the assumptions of the least-squares regression model. Complete parts (a) and (b) below Click the icon to view the data on program per-year tuition and mean starting salary a. At the 0.01 level of significance, is there evidence of a linear relationship between the starting salary upon graduation and program per-year tuition? Determine the hypotheses for the test. Ho B₁ = D H₁ P₁ #0 (Type integers or decimals. Do not round.)…Star, Inc. used Excel to run a least-squares regression analysis, which resulted in the following output: Regression Statistics Multiple R 0.9798 R Square 0.9560 Observations 30 Coefficients Standard Error T Stat P-Value Intercept 174,302 60,902 2.86 0.021 Production (X) 11.06 0.9237 11.97 0.000 What total cost would Star predict for a month in which production is 2,000 units? Multiple Choice $21,419 $62,749 $173,282 $196,422
- A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 156 students who took the course last semester are provided in the tile MktHrsPts. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between total points earned and hours spent studying? Develop an estimated regression equation showing how total points earned is related to hours spent studying. What is the estimated regression model? Test whether each of the regression parameters β0 and β1 is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? How much of the variation in the sample values of total point earned does the model you estimated in part (b) explain? Mark Sweeney spent 95 hours studying. Use the regression model you estimated in part (b) to predict the total points Mark earned.The following time series shows the sales of a particular product over the past 12 months. Construct a time series plot. What type of pattern exists in the data? Use α = 0.3 to compute the exponential smoothing values for the time series. Use trial and error to find a value of the exponential smoothing coefficient α that results in a relatively small MSE.The management of Brinkley Corporation is interested in using simulation to estimate the profit per unit for a new product. The selling price for the product will be $45 per unit. Probability distributions for the purchase cost, the labor cost, and the transportation cost are estimated as follows: ProcurementCost ($) Probability LaborCost ($) Probability TransportationCost ($) Probability 10 0.2 18 0.25 2 0.74 12 0.35 20 0.35 5 0.26 13 0.45 22 0.1 25 0.3 Compute profit per unit for the base-case, worst-case, and best-case scenarios.Profit per unit for the base-case: $ fill in the blank 1Profit per unit for the worst-case: $ fill in the blank 2Profit per unit for the best-case: $ fill in the blank 3 Construct a simulation model to estimate the mean profit per unit. If required, round your answer to the nearest cent.Mean profit per unit = $ fill in the blank 4 Why is the simulation approach to risk analysis preferable to generating a variety of…
- JASON: Do you have 10 or 15 minutes that you can spare? YOU: Sure, I've got a meeting in an hour, but I don't want to start something new and then be interrupted by the meeting, so how can I help? JASON: I've been reviewing the company's financial statements and looking for ways to improve our performance, in general, and the company's return on equity, or ROE, in particular. Anja, my new team leader, suggested that I start by using a DuPont analysis, and I'd like to run my numbers and conclusions by you to see whether I've missed anything. Here are the balance sheet and income statement data that Anja gave me, and here are my notes with my calculations. Could you start by making sure that my numbers are correct? YOU: Give me a minute to look at these financial statements and to remember what I know about the DuPont analysis. Balance Sheet Data Cash Accounts receivable Inventory Current assets Net fixed assets Total assets $1,000,000 Accounts payable 2,000,000 Accruals 3,000,000…Blaster, Inc. recently conducted a least-squares regression analysis to predict selling expenses. The company has constructed the following regression equation: Y = 339,000 + 8.30X. Which of the following statements is false if the primary cost driver is number of units sold? Multiple Choice a.) The company anticipates $339,000 of fixed selling expenses. b.) "Y" represents total selling expenses. c.) The company expects both variable and fixed selling expenses. d.) For each unit sold, total selling expenses will increase by $8.30. e.) "X" represents the number of hours worked during the period.Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2. 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. Compute the quarterly forecasts for next year based on the model you developed in part (b). Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part (b) to capture seasonal effects and create a variable t such that t = 1 for quarter 1 in year 1, t = 2 for quarter 2 in year 1, … t = 12 for quarter 4 in year 3. Compute the quarterly forecasts for next year based on the model you developed in part (d). Is the model you developed in part (b) or the model you developed in part (d) more effective? Justify your answer.