Regression analysis is a statistical technique that fits a line to observed data points so that the resulting equation can be used to forecast other data points. It is useful in excess capacity and economies of scale situations. Economies of scale occur when the ratio of asset to sales will change as the size of the firm increases. Regression analysis can lead to improved financial forecasts and better information which can be used to improve management's actions. Quantitative Problem: Jasper Jewelry has $140 million in sales. The company expects that its sales will increase 6% this year. Jasper's CFO uses a simple linear regression to forecast the company's inventory level for a given level of projected sales. On the basis relationship between inventories and sales (in millions of dollars) is as follows: recent history, the estimated Inventories - $9 + 0.09(Sales) Given the estimated sales forecast and the estimated relationship between inventories and sales, what is your forecast of the company's year-end inventory level? Enter your answer in millions. For example, an answer of $10,550,000 should be entered as 10.55. Do not round intermediate calculations. Round your answer to two decimal places. million

Regression analysis is a statistical technique that fits a line to observed data points so that the resulting equation can be used to forecast other data points. It is useful in excess capacity and economies of scale situations. Economies of scale occur when the ratio of asset to sales will change as the size of the firm increases. Regression analysis can lead to improved financial forecasts and better information which can be used to improve management's actions. Quantitative Problem: Jasper Jewelry has $140 million in sales. The company expects that its sales will increase 6% this year. Jasper's CFO uses a simple linear regression to forecast the company's inventory level for a given level of projected sales. On the basis relationship between inventories and sales (in millions of dollars) is as follows: recent history, the estimated Inventories - $9 + 0.09(Sales) Given the estimated sales forecast and the estimated relationship between inventories and sales, what is your forecast of the company's year-end inventory level? Enter your answer in millions. For example, an answer of $10,550,000 should be entered as 10.55. Do not round intermediate calculations. Round your answer to two decimal places. million

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4A: Problems In Applying The Linear Regression Model

Section: Chapter Questions

Problem 2E

See similar textbooks

Similar questions

ABC, Inc., sells tea products to various customers. In recent years, profits have been declining. The CFO of the company investigated the reasons for the profit decline and performed regression analysis for sales and costs. She determined that sales depend on product price, delivery speed, customer services, and marketing expenses. She also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales. List two advantages and two limitations of regression analysis.
Q5. Show that µY = Yµ − µY · 1. Data Mining Regression Evaluation chapter
q23- What is the aspect of sound regression analysis? Select one: a. Keep trying different models until statistical significance is achieved b. Reporting only the results that are statistically significant c. Statistical significance solely based on "p-value < 0.05" d. Economic plausibility and significance of the model Clear my choice
Economics: Industrial Economics Since only allowed 3 questions = Please Answer Parts A. - C. (and include answers to the NOTE PART: sub-questions a.; b.; c. In order to solve the Parts A. - C. questions). Thanks QUESTION: You work for the manager of a small single-product firm. Assume that you have data for your firm on costs, capital rental rate, wages and output. You realize through regression analysis that the data fits very well the following equation: ln(C) = -1.18 + 0.33 ln(r) + 0.67 ln(w) + 0.81 ln(q) A. Determine the production function from which costs were derived. Explain whether it exhibits constant, increasing or decreasing returns to scale. B. From your answer in (a), determine whether your firm should explore the possibility of expanding, knowing that the market is perfectly competitive. The market consists of a couple of large firms producing around 1,000,000 units each, multiple medium-sized firms producing 100,000 units each and a huge amount of small firms…
A multiple regression model, K = a + bX + cY + dZ, is estimated regression software, which produces the following output: a. Are the estimates of a, b, c, and d statistically significant at the 1 percent significance level? b. How much of the total variation is explained by this regression equation? c. Is the overall regression equation statistically significant at the 1 percent level of significance? d. If X equals 50, Y equals 200, and Z equals 45, what value do you predict K will take?
Assume Demand equation of a product as Q = 70 -10 P + 4Pr + 50 I Where Q = Quantity of the product demanded, P = Price of the product (in $), Pr = Price of the related product (in $) and I = Per capital income (in ‘000) State the key steps for analyzing the above demand equation and calculate the regression results. What are the implications of the above regression analysis for management decisions?
Regression of Price to Earning ratios on growth rates, betas, and payout ratios for stocks listed on the in April 2021. Thus a stock with an earnings growth rate of 20%, a beta of 1.15, and a payout ratio of 40% would have had an expected PE ratio of: You are attempting to value a private firm with the following characteristics:The firm had net profits of $10 million. It did not pay dividends, but had depreciation allowances of $5 million and capital expenditures of $12 million in the most recent year. Working capital requirements were negligible.The earnings had grown 25% over the previous five years, and are expected to grow at the same rate over the next five years.The average beta of publicly traded firms, in the same line of business, is 1.15, and the average debt-equity ratio of these firms is 25%. (The tax rate is 40%.) The private firm is an all-equity-financed firm, with no debt. P/E = 18.90 + 0.0695 *Growth - 0.5082 Beta - 0.4262 Payout Estimate the appropriate PE ratio…
Using the following variables: Company Sales Force Commission of 3% and $500,000 in Salary/Administration, and Independent Sales Rep Commission of 5%. If the company sales force and independent sales rep break-even sales volume was $50 Million, in what situation would the use of company sales force be preferred? If the sales volume was less than $5 million If the sales volume was equal to $50 Million If the sales volume was great than $50 Million If the sales volume was less than $50 Million
q22- What is NOT the aspect of sound regression analysis? Select one: a. The effect size that matters economically b. Economic plausibility and significance of the model c. Satisfactory predictive ability of the model d. Reporting only the results that are statistically significant
18. A multiple regression model, K = a + bX + cY + dZ, is estimated regression software, which produces the following output: D. If X equals 50, Y equals 200, and Z equals 45, what value do you predict K will take?
Using the corporate valuation model, the value of a company’s operations is $950 million. The company’s balance sheet shows $50 million in short-term investment. The company also has 150 m in accounts payable, $200 m in note payable, $300 m in long-term debt, $ 240 m in common stock and 160 m in retain earnings. What is your best estimate for the market value of equity per share if total number of shares outstanding = 10 million?
Question 15 When the R2 of a regression equation is very high, it indicates that all the coefficients are statistically significant. the intercept term has no economic meaning. a high proportion of the variation in the dependent variable can be accounted for by the variation in the independent variables. there is a good chance of serial correlation and so the equation must be discarded.