Regression analysis was applied between $ sales (y) and $ advertising (r) across all the branches of amajor international corporation. The following regression function was obtained. ŷ = 5000 + 7.25r(a) Predict the amount for sales where the advertising amount is $ 1,000,000.00.(b) If the advertising budgets of two branches of the corporation differ by $30,000, then what will bethe predicted difference in their sales?

We are going to use regression analysis to answer this question.

Regression analysis was applied between $ sales (y) and $ advertising (x) across all the branches of a major international corporation. The following regression function was obtained. ŷ = 5000 + 7.25 (a) Predict the amount for sales where the advertising amount is $ 1,000,000.00. (b) If the advertising budgets of two branches of the corporation differ by $30,000, then what will be the predicted difference in their sales?

Regression analysis was applied between $ sales (y) and $ advertising (x) across all the branches of a major international corporation. The following regression function was obtained. ŷ = 5000 + 7.25 (a) Predict the amount for sales where the advertising amount is $ 1,000,000.00. (b) If the advertising budgets of two branches of the corporation differ by $30,000, then what will be the predicted difference in their sales?

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

ChapterB: Differential Calculus Techniques In Management

Section: Chapter Questions

Problem 8E

See similar textbooks

Similar questions

The regression equation Netincome = 2,049 +.0478 Revenue was estimated from a sample of 100 leading world companies (variables are in millions of dollars). (0-1) If Revenue = 1, then Netincome = (a-2) Choose the correct statement. (b) Choose the right option. (c) O Increasing the revenue raises the net income. Decreasing the revenue raises the net income. O Increasing the revenue lowers the net income. million. (Round your answer to 2 decimal places.) O The intercept is not meaningful because a firm cannot have net income when revenue is zero. The intercept is meaningful because a firm can have net income when revenue is zero. If Revenue = 24,574, then NetIncome = million. (Round your answer to the nearest whole number.)
potter makes and sells ceramic bowls. It is observed that when the price is $32, only 9 bowls are sold in a week; but when the price decreases to $10, weekly sales rise to 20. Assuming that demand can be modelled by a linear function, (a) obtain a formula for Pin terms of Q (b) Calculate for the slope of the curve if the relationship between p and Q is linear. (c) comment on the likely reliability of the model
You are the manager of a firm that produces a vegetable cooking oil in Ghana. In order to make informed decision, you engaged an economist to estimate the demand equation for your product. Using data from 25 supermarkets around the country for the month of February, 2021, the estimated linear regression result for your product is shown in the table below: Variable Constant Parameter Estimates Standard error -164.0 20.24 Price of vegetable cooking oil (P,) Price of palm oil (P,) Per capita Income () -3.50 1.55 2,50 0.28 0.45 0.52 R-squared 0.8672 Adjusted R-squared 0.8132 F-statistic 15.6893 a) Suppose the average price of 3 gallons of vegetable cooking oil is GH¢12, price of 2 gallons of palm oil is GH¢60, the per capita income of Ghana is GH¢420. i. Write down the estimated demand equation for your firm's product and interpret the parameter estimates. ii. Detemine the quantity of vegetable cooking oil sold. Estimate the own price elasticity of demand and state the type of demand curve…
Water is being poured into a large, cone-shaped cistern. The volume of water, measured in cm³, is reported at different time intervals, measured in seconds. A regression analysis was completed and is displayed in the computer output. Regression Analysis: cuberoot (Volume) versus Time Predictor Coef SE Coef Constant -0.006 0.00017 -35.294 0.000 Time 0.640 0.000018 35512.6 0.000 s=0.030 R-Sq=1.000 R-sq (adj)=1.000 What is the equation of the least-squares regression line? Volume = 0.640 - 0.006(Time) Volume = 0.640 - 0.006(Time) Volume = -0.006 + 0.640(Time) Volume = - 0.006 + 0.640(Time?)
As an auto insurance risk analyst, it is your job to research risk profiles for various types of drivers. One common area of concern for auto insurance companies is the risk involved when offering policies to younger, less experienced drivers. The U.S. Department of Transportation recently conducted a study in which it analyzed the relationship between 1) the number of fatal accidents per 1000 licenses, and 2) the percentage of licensed drivers under the age of 21 in a sample of 42 cities. Your first step in the analysis is to construct a scatterplot of the data. FIGURE. SCATTERPLOT FOR U.S. DEPARTMENT OF TRANSPORATION PROBLEM U.S. Department of Transportation The Relationship Between Fatal Accident Frequency and Driver Age 4.5 3.5 3 2.5 1.5 1 0.5 6. 10 12 14 16 18 Percentage of drivers under age 21 Upon visual inspection, you determine that the variables do have a linear relationship. After a linear pattern has been established visually, you now proceed with performing linear…
The table to the right contains price-demand and total cost data for the production of projectors, where p is the wholesale price (in dollars) of a projector for an annual demand of x projectors and C is the total cost (in dollars) of producing x projectors. Answer the following questions (A) - (D). (A) Find a quadratic regression equation for the price-demand data, using x as the independent variable. X 270 360 520 780 The fixed costs are $. (Round to the nearest dollar as needed.) ITTI y = (Type an expression using x as the variable. Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) Use the linear regression equation found in the previous step to estimate the fixed costs and variable costs per projector. The variable costs are $ per projector. (Round to the nearest dollar as needed.) (C) Find the break even points. The break even points are (Type ordered pairs. Use a comma to separate answers as needed. Round to the nearest integer as…
Suppose you are the manager of a firm that produces good X in Ghana. In order to make informed decision, you engaged an economist to estimate the demand equation for your product. Using data from 30 supermarkets around the country for the month of April, 2021, the estimated linear regression result for your product is shown in the table below: Variable Parameter Estimates Standard error Constant -164.0 20.24 Price of good X (P,) Price of good Y (P,) -3.50 1.55 2.50 0.28 Per capita Income (/) 0.45 0.52 R-squared 0.8672 Adjusted R-squared 0.8132 F-statistic 15.6893 a) Suppose the average price of 3 units of good X is GH¢12, price of 2 units of goodY is GH¢60, the per capita income of Ghana is GH¢420. 1. Write down the estimated demand equation for your firm's product and interpret the parameter estimates. Determine the quantity of good X sold. Estimate the own price elasticity of demand and state the type of demand curve 11. 111. your firm has?
Q4. The Omantel firm has estimate the Sales of fibre internet connections in Oman with the related to advertising expenditure made by the company over the past 26 months. Following is the firm estimated results of the regression equation. DEPENDENT VARIABLE: Y R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 26 0.85121212 8.747 0.0187 PARAMETER STANDARD VARIABLE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 7.6 6.33232 1.200 0.2643969 3.53 0.52228 ? 0.0001428 a. What is the dependent and independent variables in the above regression equation of Omantel firm? b. Calculate the estimated t-ratio. Test the slope estimates for statistical significance at the 10 percent significance level. d. Interpret the coefficient of determination.
1. Consider a linear regression model y = XB + € with E(e) = 0. The bias of the ridge estimator of 3 obtained by minimizing Q(B) = (y — Xß)¹ (y — Xß) + r(BTB), for some r > 0, is ——(X²X + r1)-¹8 1 (X¹X +rI)-¹3 r -r(XTX+rI) ¹8 r(X¹X+r1) ¹3
Suppose you are the manager of a firm that produces good X in Ghana In order to make informed decision, you engaged an economist to estimate the demand equation for your product. Using data from 30 supermarkets around the country for the month of April, 2021, the estimated linear regression result for your product is shown in the table below: Variable Parameter Estimates Standard error Constant -164.0 20.24 Price of good X (P) Price of good Y (P,) -3.50 1.55 2.50 0.28 Per capita Income () 0.45 0.52 R-squared Adjusted R-squared 0.8672 0.8132 F-statistic 15.6893 a) Suppose the average price of 3 units of good X is GH¢12, price of 2 units of goodY is GH¢60, the per capita income of Ghana is GH¢420. Write down the estimated demand equation for your firm's product and interpret 1. the parameter estimates. Determine the quantity of good X sold. Estimate the own price elasticity of demand and state the type of demand curve 1. 11 your firm has? What would be the effect of a price increase on…
Bounds Inc. determined through regression analysis that its sales (S) are a function of the amount of advertising (measured in units) in two different media. This relationship is given by the following equation (X = newspapers, Y = magazines): S (X, Y) = 200X+100Y− 10X2− 20Y2 + 20XY Find the level of newspaper and magazine advertising that maximizes the firm’s sales. Calculate the firm’s sales at the optimal values of newspaper and magazine advertising determined in part (a).
Determine the mode choice (personal vehicle or bus system) for the following regression model: Utility Function: Umode – (8.333 x 10-4)*(Access time in sec) – (6.667 x 10-4)*(Wait Time in sec) – (5.00 x 10-4)*(Riding time in sec) – (1.40)*(Cost, $) PARAMETER PERSONAL VEHICLE CITY BUS SYSTEM MODE CONSTANT -0.01 -0.07 ACCESS TIME (SECS) 300 600 WAITING TIME (SECS) 0 900 RIDING TIME (SECS) 1,500 6,000 COST (DOLLARS) $1.50 $1.00