The following question refers to this regression equation (standard errors for each of the estimated coefficients are in parenthesis). Q=8,400-8" P+5" A+ 4** Px +0.05**1, (1,732) (2.29) (1.36) (1.75) (0.15) Q = Quantity demanded P = Price 1,100 Advertising expenditures, in thousands = 20 P = price of competitor's good = 600/= average monthly income 10,000 What is the advertising elasticity of demand? Round your answer to two decimal places. Your Answer: The t-statistic is computed by dividing the regression coefficient by the standard error of the coefficient. dividing the regression coefficient by the standard error of the estimate. dividing the standard error of the coefficient by the regression coefficient. dividing the R2 by the F-statistic. none of the specified answers are correct.
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- 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?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…
- 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…Consider the following estimated regression for 220 home sales from a community in 2019 (estimated standard errors in parentheses) Price = 119.2 + 0.485BDR + 23.4Bath + 0.156Hsize + 0.002Lsize + 0.09Age (0.011) (2.61) (8.94) (0.00048) (0.311) R2 = 0.72 where Price denote the selling house price (measured in $1000s), BDR denote the number of bedrooms, Bath denote the number of bathrooms, Hsize denote the size of the house (in square feet), Lsize denote the lot size (in square feet), and Age denote the age of the house (in years).Imagine that you work for the maker of a leading brand of low-calorie, frozen microwavable food that estimates the following demand equation for its product using data from 26 supermarkets around the country for the month of April. Note: The following is a regression equation. Standard errors are in parentheses for the demand for widgets. QD = - 5200 - 42P + 20PX + 5.2I + 0.20A + 0.25M (2.002) (17.5) (6.2) (2.5) (0.09) (0.21) R2 = 0.55 n = 26 F = 4.88 Your supervisor has asked you to compute the elasticities for each independent variable. Assume the following values for the independent variables: Q = Quantity demanded of 3-pack units P (in cents) = Price of the product = 500 cents per 3-pack unit PX (in cents) = Price of leading competitor's product = 600 cents per 3-pack unit I (in dollars) = Per capita income of the standard metropolitan statistical area (SMSA) in…
- 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…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) ¹3Consider the output here from a regression in R. What is 3₂? Coefficients: Estimate (Intercept) 1.708 5.404 -1.478 9.531 X1 X2 X3 Std. Error 0.555 2.792 0.6 2.758
- Regression analysis was applied between $ sales (y) and $ advertising (r) across all the branches of a major 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 be the predicted difference in their sales?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.General Cereals is using a regression model to estimate the demand for Tweetie Sweeties, a whistle-shaped, sugar-coated breakfast cereal for children. The following (multiplicative exponential) demand function is being used: QD = 6,280 P(-2.15) A1.75N2.70 where QD = quantity demanded, in 10-oz boxes P = price per box, in dollars A = advertising expenditures on daytime television, in dollars N = proportion of the population under 12 years old, in percent What is the point price elasticity of demand for Tweetie Sweeties? 1.75 -1.23 2.70 -2.15 What is the advertising elasticity of demand? 0.65 1.75 -2.15 2.70 According to the estimated model, a percent increase in the proportion of the population under 12 years old by percent. the quantity demanded