Lab 2: Part 1: Linear Regression Welcome to CastAway Cruise Lines TM! CastAway Cruise LinesTM is a short to midterm cruise operator based out of the port on Miami We maintain a feet ol s elegant /esseis that each nave approximately 750 cubins per ship Each snip has 30 suites (S,, 120 F Balcony (E) Cabins. 150 cabins equipped with a window (W; and 450 .r terior (!) cabins. In addition to room type, we track: total cost, room costs, ship board expenses, casino expenses, and excursion expenses for all of our customers Our primary concern is maintaining our customer satisfaction amongst our patrons. For all of analysis, make sure that Customer Satisfaction is "Target' while Overall_1_5_Satisfaction is 'Rejected'. As our newest (and only) data analyst you are tasked with the following projects: 1. Is there a relationship between how much a patron's entire trip costs and their overall satisfaction: Provide the visual and numerical values that you referenced and justify your conclusion. (Hint. set customer satisfaction to 'Input' for this question to show it in the correlation matri" of variable clustering results. Change it back to target for the other questions.) What would be the best possible model you could build, without any categorical variables, to predict customer satisfaction (Remember to change the role of Customer Satisfaction back to Target.)? How strong of a predictive model is this? is there any potential for multicollinearity? How did you determine these attributes? 3. Does the choice of the type of room have significance impact on the overall level of customer satisfaction if it is the only predictor? If so which room type(s) is different from the reference type (cabins with a window): How did you come to this conclusion." 4. Taking both the collinearity diagnostics into account as well using the categorical data, what is the best model you can create? Can you improve upon this model by creating other categorical variables? Which variable(s) did you remove due to multicollinearity. J. How can you use this model to increase customer satisfaction. Give specific examples and tie it back to the individual coefficients