The estimated regression equation describing the relationship between the price (P)charged by a monopolist for his product and the quantity (Q) of the productpurchased by consumers is given by: Q = 500,000 - 100 P. Results of a t-test rejectthe null hypothesis for the coefficient multiplying price. The correct interpretationof the B₁ coefficient (equal to -100) is:A) when price is equal to zero, then the average quantity sold is equal to 100B) an increase in price by one dollar on average is associated with a 100 unitdecrease in quantityC) a 1% increase in price is associated with a 100% decrease in quantityOD) an increase in quantity by one unit on average is associated with a $100decrease in price

From the estimated regression equation Q=500,000-100P ......... (1) The t-test statistics…

The estimated regression equation describing the relationship between the price (P) charged by a monopolist for his product and the quantity (Q) of the product purchased by consumers is given by: Q = 500,000 - 100*P. Results of a t-test reject the null hypothesis for the coefficient multiplying price. The correct interpretation of the B₁ coefficient (equal to -100) is: OA) when price is equal to zero, then the average quantity sold is equal to 100 B) an increase in price by one dollar on average is associated with a 100 unit decrease in quantity OC) a 1% increase in price is associated with a 100% decrease in quantity D) an increase in quantity by one unit on average is associated with a $100 decrease in price

The estimated regression equation describing the relationship between the price (P) charged by a monopolist for his product and the quantity (Q) of the product purchased by consumers is given by: Q = 500,000 - 100*P. Results of a t-test reject the null hypothesis for the coefficient multiplying price. The correct interpretation of the B₁ coefficient (equal to -100) is: OA) when price is equal to zero, then the average quantity sold is equal to 100 B) an increase in price by one dollar on average is associated with a 100 unit decrease in quantity OC) a 1% increase in price is associated with a 100% decrease in quantity D) an increase in quantity by one unit on average is associated with a $100 decrease in price

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

Chapter4: Estimating Demand

Section: Chapter Questions

Problem 1E

See similar textbooks

Similar questions

Consider the following multiple regression Price=118.9+0.594BDR+23.5Bath+0.195Hsize+0.004Lsize+0.095Age−48.5Poor, R2=0.75, SER=41.5 (22.7) (2.56) (8.56) (0.017) (0.00049) (0.315) (10.7) The numbers in parentheses below each estimated coefficient are the estimated standard errors. A detailed description of the variables used in the data set is available here . Suppose you wanted to test the hypothesis that BDR equals zero. That is, H0: BDR=0 vs H1: BDR≠0 Report the t-statistic for this test. The t-statistic is ________ (Round your response to three decimal places)
The Pilot Pen Company has decided to use 15 test markets to examine the sensitivity of demand for its new product to various prices, as shown in the following table. Advertising effort was identical in each market. Each market had approximately the same level of business activity and population. Complete the following worksheet and then estimate the demand function for Pilot's new pen using a linear regression model. Test Market Price Charged Quantity Sold (cents) (Thousands of Pens) ii xixi yiyi xixiyiyi xi2xi2 yi2yi2 1 50 20 1,000 2,500 400 2 50 21 1,050 2,500 441 3 55 19 1,045 3,025 361 4 55 19.5 1,072.5 3,025 380.25 5 60 20.5 1,230 3,600 420.25 6 60 19 1,140 3,600 361 7 65 15.5 1,007.5 4,225 240.25 8 65 15 975 4,225 225 9 70 14.5 1,015 4,900 210.25 10 70 15.5 1,085 4,900 240.25 11 80 13 1,040 6,400 169 12 80 14 1,120 6,400 196 13 90 11.5 1,035 8,100 132.25 14 90 11 990 8,100 121 15 40 17 680 1,600 289 Total 980 246 ?…
In a study it was shown that for a sample of 353 college faculty, the correlation was 0.11 between annual raises and teaching evaluations. What would be the coefficient of determination of a regression of annual raises on teaching evaluations for this sample? Interpret your result.
Using the regression results in column (1):a. Is the college–high school earnings difference estimated from thisregression statistically significant at the 5% level? Construct a 95%confidence interval of the difference.b. Is the male–female earnings difference estimated from this regressionstatistically significant at the 5% level? Construct a 95% confidenceinterval for the difference.
In regression analysis, a common metric used in assessing the quality of the model being used to fit the data is known as the R-squared coefficient. Explain the R-squared coefficient. What is the difference between the R-squared and adjusted R-squared coefficients?
1.In econometrics, a sample is Select one: a. the entire group of entities that we are interested in learning about. b. only one observation drawn from the population. c. a subset or part of the population and it is what is used to perform statistical inference. d. the primary thing that econometricians are interested in. 2. The estimated sample regression function is determined by Select one: a. minimizing the sum of squared residuals. b. minimizing the least absolute deviations from the mean. c. minimizing the total deviations from the mean. d. maximizing the sum of squared residuals. 3. Econometrics is Select one: a. the science of collection, organization, analysis, and interpretation of data. b. the use of summary statistics. c. the application of statistical techniques to economic data. d. the study of how people chose to use scarce resources. 4. Simple linear regression analysis determines Select one: a. the true value of the population slope coefficient. b.…
The appropriate statistic to examine the goodness of fit of a two-variable regression model is _____. Select one: a. t-statistic b. F-statistic c. R2-statistic d. Chi-square statistic
Using the regression results in column (1):a. Is the college–high school earnings difference estimated from thisregression statistically significant at the 5% level? Construct a 95%confidence interval of the difference.b. Is the male–female earnings difference estimated from this regressionstatistically significant at the 5% level? Construct a 95% confidenceinterval for the differenc(answer for me part please)
The 2008 sales and profits of seven companies were given as follows Firm Sales ($ Billions) Profit ($ Billions) Fiat 5.7 0.27 Honda 6.7 0.12 BP 0.2 0.01 Toyota 0.6 0.04 Apple 3.8 0.05 IBM 12.5 0.46 Phillips 0.5 0.02 The estimated value for the company’s Profit can be estimated using the equation; Y ̂i = α ̂ + β ̂Xi……………………………………………………………………Eqn.1 Where; Y = Companies Profit X = Companies Sales α ̂ and β ̂ are estimated parameters in the model Calculate the sample regression line, where profit is the dependent variable (Y) and sales is the independent variable (X)
The following data gives the experience of the machine operators and their performance ratings as given by the number of good parts turned out per 100 pieces.Experience(X) 16 12 18 4 3 10 5 12Performance Ratings (Y) 88 87 89 68 78 80 75 83Obtain the regression line of performance ratings on experience and estimate the probable performance if the operator has 7 years of experience.
Investigate what factors determine the number of times a person logs into Facebook per week. It is argued that these four factors are important: number of friends, age in years, whether the person is employed, and whether the student has a Twitter account. The function is: FACEBOOK LOGIN=f(FRIENDS,AGE,EMPLOYED,TWITTER) With this functions and variables in mind: Perform necessary tests and analysis to determine the validity of the regression attached in the below table and function provided The tests and analysis must be broken down into two sections namely: tests that are possible with the given regression’s information and tests that should be conducted but are not possible with the given information. For the tests that are possible please conduct them at a 5% significance level and for those that are not possible only mention their names without any further details
State the Ordinary Least-Squares assumptions of the regression model with one regressor.