Predictive Accuracy And Modelling For Explanatory Power Essay

Through using R, we have created a set of models that help to predict the likelihood of a customer churning. By working together in the analysis stage we were able to ‘bounce’ ideas off one another and grasp a further understanding of the data and customer churn. We created two different models: modelling for predictive accuracy and modelling for explanatory power. What is our team structure? In the group we have four team members that consists of three males and one female; Ryan Campion, Samuel O’Connell, Hunter Stewart, and myself, Hannah Lowe. We’ve all worked really well together. Everyone has contributed and we have managed to meet the allocated times set to doing this assignment. There has been no group issues, or any person putting in any less effort than the other. In the analysis stage we tackled it as a group: we didn’t work as individuals. We worked on one computer and used the lab work we had done prior to aid us with our models. The reason for this is that we were confused slightly as how to read the models from the start; by discussing it with one another we were able to grasp a better concept of what we were looking for. In the reporting stage we all worked independently, within our own time frame. There was a discussion on the findings from the data, which is in our reports, but in our own words. The presentation was worked on collectively. I organised the parts that were to be discussed, these areas were the distributed to other members. We all wroteShow MoreRelatedBig Data Analytics Driven Enterprise Asset Management For Asset Intensive Industries6539 Words   |  27 Pagesis now ubiquitous in our daily life and economy more than ever before. 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