1. Climate change affects everyone regardless of where they are on the globe. You work for an environmental NGO that is currently studying public transit ridership. Specifically, you are looking at what most influences the decision to use the bus to commute. This research may yield insight into these decisions, and help construct better transit policies in cities across Canada. a. Which variables most strongly predict bus ridership? i. At a high level, how do these predictors relate to each other? b. What can you say about the quality of the model you've created? i. Is it a good model to put into production? c. What would your overall conclusions be from this model, and what would you recommend (at a high level) as policy options? in spss, using decision tree model