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Let price denote a price index for the goods sold by a restaurant, advert the amount spent on advertising, sales the sales for the restaurant, and consider the following regression sales = ß1 + B2price + ßzadvert + e We estimate the above regression in R and obtain the following output: ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) 84.259 19.050 4.423 3.38e-05 *** ## price -2.868 3.287 -0.873 0.3858 ## advert 4.246 2.049 2.072 e.0418 * ## --- ## Signif. codes: A **** e.001 *** 0.01 '*' 0.05 '.' 0.1 ' 1 ## ## Residual standard error: 14.65 on 72 degrees of freedom ## Multiple R-squared: 0.0645, Adjusted R-squared: 0.03851 ## F-statistic: 2.482 on 2 and 72 DF, p-value: 0.09071 Suppose we are interested in testing the null hypothesis Ho : B2 = 0, ß3 = 0 against the alternative H1 : B2 # 0 or ßz # 0. Based on the displayed output, which of the following statements is true? O a. We should reject the null hypothesis at the 30% error level but not the 20% error level. O b. We should reject the null hypothesis at the 5% error level but not the 1% error level. O c. We should reject the null hypothesis at the 20% error level but not the 10% error level. O d. We should reject the null hypothesis at the 10% error level but not the 5% error level. O e. All the other statements are false.

Let price denote a price index for the goods sold by a restaurant, advert the amount spent on advertising, sales the sales for the restaurant, and consider the following regression sales = ß1 + B2price + ßzadvert + e We estimate the above regression in R and obtain the following output: ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) 84.259 19.050 4.423 3.38e-05 *** ## price -2.868 3.287 -0.873 0.3858 ## advert 4.246 2.049 2.072 e.0418 * ## --- ## Signif. codes: A **** e.001 *** 0.01 '*' 0.05 '.' 0.1 ' 1 ## ## Residual standard error: 14.65 on 72 degrees of freedom ## Multiple R-squared: 0.0645, Adjusted R-squared: 0.03851 ## F-statistic: 2.482 on 2 and 72 DF, p-value: 0.09071 Suppose we are interested in testing the null hypothesis Ho : B2 = 0, ß3 = 0 against the alternative H1 : B2 # 0 or ßz # 0. Based on the displayed output, which of the following statements is true? O a. We should reject the null hypothesis at the 30% error level but not the 20% error level. O b. We should reject the null hypothesis at the 5% error level but not the 1% error level. O c. We should reject the null hypothesis at the 20% error level but not the 10% error level. O d. We should reject the null hypothesis at the 10% error level but not the 5% error level. O e. All the other statements are false.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Let price denote a price index for the goods sold by a restaurant, advert the amount spent on advertising, sales the sales for the restaurant, and consider the following regression sales = Bi + B2price + Bzadvert + e We estimate the above regression in R and obtain the following output: ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) ## price 84.259 19.050 4.423 3.38e-05 *** -2.868 3.287 -0.873 0.3858 ## advert 4.246 2.049 2.072 0.0418 * ## ## Signif. codes: A '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 '' 1 ## ## Residual standard error: 14.65 on 72 degrees of freedom ## Multiple R-squared: 0.0645, Adjusted R-squared: 0.03851 ## F-statistic: 2.482 on 2 and 72 DF, p-value: 0.09071 Suppose we are interested in testing the null hypothesis Ho : B2 = 0, ß3 = 0 against the alternative H1 : B2 # 0 or ß3 # 0. Based on the displayed output, which of the following statements is true? O a. We should reject the null hypothesis at the 30% error level but not the 20% error level. b. We should reject the null hypothesis at the 5% error level but not the 1% error level. O c. We should reject the null hypothesis at the 20% error level but not the 10% error level. O d. We should reject the null hypothesis at the 10% error level but not the 5% error level. O e. All the other statements are false.
Transcribed Image Text:Let price denote a price index for the goods sold by a restaurant, advert the amount spent on advertising, sales the sales for the restaurant, and consider the following regression sales = Bi + B2price + Bzadvert + e We estimate the above regression in R and obtain the following output: ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) ## price 84.259 19.050 4.423 3.38e-05 *** -2.868 3.287 -0.873 0.3858 ## advert 4.246 2.049 2.072 0.0418 * ## ## Signif. codes: A '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 '' 1 ## ## Residual standard error: 14.65 on 72 degrees of freedom ## Multiple R-squared: 0.0645, Adjusted R-squared: 0.03851 ## F-statistic: 2.482 on 2 and 72 DF, p-value: 0.09071 Suppose we are interested in testing the null hypothesis Ho : B2 = 0, ß3 = 0 against the alternative H1 : B2 # 0 or ß3 # 0. Based on the displayed output, which of the following statements is true? O a. We should reject the null hypothesis at the 30% error level but not the 20% error level. b. We should reject the null hypothesis at the 5% error level but not the 1% error level. O c. We should reject the null hypothesis at the 20% error level but not the 10% error level. O d. We should reject the null hypothesis at the 10% error level but not the 5% error level. O e. All the other statements are false.
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