Researcher has estimated the following model in STATA, where Sales is a sales revenue (measured in...

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Researcher has estimated the following model in STATA, where Sales is a sales revenue (measured in $1000), Price of a product is measured in $1, and Advert is advertisement expenditure measured in $1000. reg sales price advert Source Model Residual Total sales estat vce SS 1396.53921 1718.94281 e(V) 3115.48202 df Coef. Std. Err. MS 2 698.269683 72 23.8742057 74 42.1011083 t Pit| price -7.907856 1.095993 -7.22 0.000 -10.09268 advert 1.862584 .6831955 -5006587 cons 106.2519 price 2.73 0.008 118.9136 6.351638 18.72 0.000 Covariance matrix of coefficients of regress model advert cons 72) = 29.25 = 0.0000 Number of obs 75 FL 2, Prob > F R-squared Adj R-squared Root PSE price: 1.2012009 advert .01974216 .46675603 Cons -6.795065 -.7484205 40.343304 - 9.4483 0.4329 4.8861 [95% Conf. Intervall -5.723034 3.224509 131.5754 a) Write down the population regression model. b) Provide the interpretation for price coefficient. c) Provide the interpretation for advertisement coefficient. d) Test the hypothesis if price elasticity of demand is elastic. e) Notice to increase Sales Revenue we need to either reduce price of a product or to increase the advertisement cost. The marketing analyst believes that if we reduce price by 40 cents (= $0.4) and increase advertisement costs by $800, the sales revenue would on average increase by $4000. Please conduct a hypothesis test for his claim. Researcher has estimated the following model in STATA, where Sales is a sales revenue (measured in $1000), Price of a product is measured in $1, and Advert is advertisement expenditure measured in $1000. reg sales price advert Source Model Residual Total sales estat vce SS 1396.53921 1718.94281 e(V) 3115.48202 df Coef. Std. Err. MS 2 698.269683 72 23.8742057 74 42.1011083 t Pit| price -7.907856 1.095993 -7.22 0.000 -10.09268 advert 1.862584 .6831955 -5006587 cons 106.2519 price 2.73 0.008 118.9136 6.351638 18.72 0.000 Covariance matrix of coefficients of regress model advert cons 72) = 29.25 = 0.0000 Number of obs 75 FL 2, Prob > F R-squared Adj R-squared Root PSE price: 1.2012009 advert .01974216 .46675603 Cons -6.795065 -.7484205 40.343304 - 9.4483 0.4329 4.8861 [95% Conf. Intervall -5.723034 3.224509 131.5754 a) Write down the population regression model. b) Provide the interpretation for price coefficient. c) Provide the interpretation for advertisement coefficient. d) Test the hypothesis if price elasticity of demand is elastic. e) Notice to increase Sales Revenue we need to either reduce price of a product or to increase the advertisement cost. The marketing analyst believes that if we reduce price by 40 cents (= $0.4) and increase advertisement costs by $800, the sales revenue would on average increase by $4000. Please conduct a hypothesis test for his claim.

Answer rating: 100% (QA)

ANSWER a The population regression model can be written as follows Sales 0 1 Price 2 Advert Where Sales is the sales revenue measured in 1000 Price is ... View the full answer