MK336 Study Guide - Final Guide: Predictive Analytics
29 Apr 2019
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90 minutes during class time @ walker 634. Understand the relationship concept value of customer base understand the idic model. Bases for segmenting a market criteria for evaluating a segment review rfm & two binning methods review the k-means clustering review the k-means clustering assignment (focus on reading the clusters) Understand association analysis and the quality measures of rules sequence analysis and the quality measures of rules. Know the three types of analytics able to identify examples / analytical techniques used in each of the analytics types what is predictive analytics typical outputs of a predictive analytics model. What is decision tree what are the nodes in the tree understand the properties of tree: understand branches, leaves in a tree understand the rationale for data partitioning in modeling. Review the class slides / notes review the assignments. 30 multiple-choice, true/false, fill-in, matching (3. 0 points each) 3 short-answer questions (35 points total), result/insight interpretation and insight-driven recommendations.
