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

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

See similar textbooks

Similar questions

E3
A multiple regression of y on a constant x and x2 produces the following results: ŷ = 4 + 0.4x + 0.9x2, R2 8/60, e'e 520, n = 29, %3D 29 X'X %3D 50 10 10 80 Test the hypothesis that the two slopes sum to 1.
determine the regression line equation plot the line on a graph and summarize the results( reject or do not) is there enough evidence?
Finally consider the regression model with an extra covariate: Yi = Bo + B1x1i + B2x2; + €; Let 32=3.13, it's standard error s.e.(B1)=1.12 and assume n=811. Based only on this information, decide if it is useful to include X2i in the regression model. Carefully showing every step of your hypothesis test and explaining your answer. Use signifi- cance level a = .05.
You use a dataset with 538 observations to run a simple linear regression. You find that the coefficient estimate is 3.258 and that the standard error of the coefficient estimate is 1.794. What is the lower end of the 98% confidence interval (of a two- sided test)? (you need to write a number that is rounded to the fourth digit after the decimal).
Assess whether the error terms of the econometric model in Wage=b0+b1(lQ) are normally distributed using the residuals from the sample regression function in wage=166.99+8.3(IQ), based on a histogram of frequency distribution, the skewness and kurtosis values, as well as the Jarque-Bera test statistic.
A researcher investigating whether government expenditure crowds out investment estimates a regression on data for 30 countries. I-investment; G-government recurrent expenditure; Y=gross domestic product; all measured in $US billion. P= population measured in million. Standard errors are in parentheses. Î= 18.10 (7.79) R² = 0.99 1.07G + 36Y (0.14) (0.02) She suspects that countries with higher GDP may have more variability in their investment. She sorts the observations by increasing size of gdp per capita (Y)and estimates the regression again for the 11 countries with the lowest gdp(Y)and the 11 countries with the largest gdp(Y). The RSS1 from the first regression is 7186. The RSS2 from the second regresison is 28101. Perform a Goldfeld-Quandt Test at a 5% significance level. a. The test statistic for this test is 0.256 b. The critical value defining the rejection region for Ho is 3.18 c. Is there heterscedasticity? Yes=1 or No-0. The answer is 0
19. The White test test statistic is n*R² ~x²(S-1). Where is the R² in the test statistic measured? A. The original econometric model when estimated using the White Robust Estimator B. The average from all the auxiliary regressions estimated with each explanatory variable as a function of the other explanatory variables C. The original econometric model before any test of heteroskedasticity has been performed D. The auxiliary regression of residuals as a function of the explanatory variables generating the heteroscedasticity 20. With annual times series data of 50 observations, how many observations are available to estimate the consumption econometric model CONt = Bo+ ß₁DISPYt + B₂CONt-1+ut A. 50 B. 47 C. 45 D. 49 21. Suppose the estimated simple linear demand equation for single-game tickets for a major football league is q=4.58-0.51p where q is the number of tickets sold measured in thousands and p is the dollar price of a ticket. Further assume that the point of the means_is…
"Why can’t I just test the individual coefficients one at a time"? is this approach is unreliable?
Suppose we have sample data on (y,x) of size n. Consider regressing y on x and a constant using the least square method (OLS estimation). The estimated equation is y = 2.59 +5.19 x + e where e is the residual. The standard errors for the constant and the coefficient were 0.51 and 1.58 respectively. To test the null hypothesis of zero coefficient (for x) at a given significance level, we may use t-statistic. Compute the t-statistic for the coefficient. Make sure the answer is round up to the nearest hundredth. e.g. 3.015 --> 3.02
Q. 30 The t test can be used for testing the JOINT significance of ALL explanatory variables x2, x3, and x4 in a multiple regression model. O True O False
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.