Instructions: In order to complete this quiz, please download Excel dataset (Quiz 4 dataset.xlsx"). Please type up your answers and provide the appropriate graphs/tables from Excel. Please upload ONE Word or PDF document that includes your answers and Excel graphs/tables on Moodle. The sharing in any format of Excel files, answers, and/or write ups is a violation of the Honor Code. Your write up must be your independent work. If the write up is not your independent work, it is a violation of the Honor code and will result in a 0 for the assignment. Sunrise Juice Inc. Revenue Analysis Sunrise Juice Inc. is a relatively new company in the large and growing market for healthy juice drinks. Sunrise's philosophy is simple - produce honest to goodness fruit juice without any preservatives or added sugar. Also, using portable, eco-friendly containers is top priority for the company. Sunrise Inc. wants to get a better understanding of its market so that it can gain a larger share and increase its revenue. Over the past several months they have recorded relevant data from daily sales of their products from various vending machines located across Baltimore. This data includes total daily Revenue in dollars, type of Container vended (cans or small BPA free plastic bottles), Flavors (Mango, Apple, Orange), Price in cents (varying by location of vending machine) and competitor's price (Comp Price) in cents. They have hired you as a statistical consultant and have provided you with a sample of their data. 1. Sunrise thinks that revenue may at least partially be explained by the quantitative variables, particularly price. (a) What is the strength of the linear relationship between price and revenue? Explain how you made this determination and interpret the appropriate statistic. (b) Which quantitative variable has the strongest linear relationship with revenue? Justify your answer based on the appropriate statistic. (c) Show graphically the linear relationship between price and revenue. (d) Estimate the regression equation based on the graph in 1(c). (e) State the estimated equation and interpret each of the coefficients. (f) What percentage of the variation in revenue has been explained by your model? 2. Sunrise thinks all of the variables in the data set including type of container, flavors and competitor's price are relevant in explaining their revenue. (a) What is the dependent variable in this model? What are the independent variables? Based on theory or your intuition, what type of relationship do you expect between the dependent variable and each of the independent variables? (b) Estimate the multiple regression equation for revenue based on all of the variables (including the categorical variables). (c) Does the estimated equation match your expectation in 2(b)? Explain. (d) Interpret the coefficient of price. (e) Interpret the coefficient(s) of type of container. (f) For which flavor is revenue higher? Explain your choice carefully using the results from the regression equation. (g) What percentage of the variation in revenue has been explained by your model? Instructions: In order to complete this quiz, please download Excel dataset (Quiz 4 dataset.xlsx"). Please type up your answers and provide the appropriate graphs/tables from Excel. Please upload ONE Word or PDF document that includes your answers and Excel graphs/tables on Moodle. The sharing in any format of Excel files, answers, and/or write ups is a violation of the Honor Code. Your write up must be your independent work. If the write up is not your independent work, it is a violation of the Honor code and will result in a 0 for the assignment. Sunrise Juice Inc. Revenue Analysis Sunrise Juice Inc. is a relatively new company in the large and growing market for healthy juice drinks. Sunrise's philosophy is simple - produce honest to goodness fruit juice without any preservatives or added sugar. Also, using portable, eco-friendly containers is top priority for the company. Sunrise Inc. wants to get a better understanding of its market so that it can gain a larger share and increase its revenue. Over the past several months they have recorded relevant data from daily sales of their products from various vending machines located across Baltimore. This data includes total daily Revenue in dollars, type of Container vended (cans or small BPA free plastic bottles), Flavors (Mango, Apple, Orange), Price in cents (varying by location of vending machine) and competitor's price (Comp Price) in cents. They have hired you as a statistical consultant and have provided you with a sample of their data. 1. Sunrise thinks that revenue may at least partially be explained by the quantitative variables, particularly price. (a) What is the strength of the linear relationship between price and revenue? Explain how you made this determination and interpret the appropriate statistic. (b) Which quantitative variable has the strongest linear relationship with revenue? Justify your answer based on the appropriate statistic. (c) Show graphically the linear relationship between price and revenue. (d) Estimate the regression equation based on the graph in 1(c). (e) State the estimated equation and interpret each of the coefficients. (f) What percentage of the variation in revenue has been explained by your model? 2. Sunrise thinks all of the variables in the data set including type of container, flavors and competitor's price are relevant in explaining their revenue. (a) What is the dependent variable in this model? What are the independent variables? Based on theory or your intuition, what type of relationship do you expect between the dependent variable and each of the independent variables? (b) Estimate the multiple regression equation for revenue based on all of the variables (including the categorical variables). (c) Does the estimated equation match your expectation in 2(b)? Explain. (d) Interpret the coefficient of price. (e) Interpret the coefficient(s) of type of container. (f) For which flavor is revenue higher? Explain your choice carefully using the results from the regression equation. (g) What percentage of the variation in revenue has been explained by your model
