SCMG 614 Descriptive Data Mining Assignment Solution by Expert

 

Assignment Detail:-

  • Number of Words: 2000

 

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Question 1

The Trader Joe’s grocery chain is considering a redesign of its supply chain. Trader Joe’s uses frequent truck shipments from its distribution centers to supply its retail stores. To keep costs low, retail stores are typically located near a distribution center. The file Trader Joes contains data on the location of each of Trader Joe’s retail stores. They would like to use k-means clustering with k = 8 to estimate the preferred locations for a proposal to use eight distribution centers to support the retail stores.

 

1. Conduct a k-means clustering analysis with k = 8 and determine which store locations are grouped into each cluster. Before you run the clustering analysis, you should remove the Store variable from the data set because this is just a variable that identifies each observation and should not be used in the clustering. You should also normalize the Latitude and Longitude variables before conducting the analysis to ensure that the values are scaled to have a mean of 0 and a standard deviation of [10 points]

 

2. Create a graph of the physical store locations designated by cluster (such as using different colors for the points to designate the different clusters). The graph should distinguish which stores are grouped together. Make sure that you follow the principles of creating effective graphs that we discussed a few weeks [10 points]

 

3. Conceptually, what are the drawbacks to using this clustering approach to assign retail stores to distribution centers? [10 points]

 

Question 2

Apple tracks online transactions at its I Store and is interested in learning about the purchase patterns of its customers to provide recommendations as a customer browses its website. A sample of the shopping cart data resides in the Apple Cart Binary file provided. This file also identifies 15 association rules (antecedents and consequents) to be analyzed. Compute the confidence and lift ratio for each of the 15 association rules in the data file. Rank the association rules in decreasing order by lift ratio. Which association rule has the highest lift ratio? Interpret what the rule with the largest lift ratio says about the relationship between the antecedent and consequent. [30 points]