Analyzing buying trends of these new international items

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Reference no: EM132293945

A grocery store introducing items from Italy is interested in analyzing buying trends of these new “international” items, namely prosciutto, peroni, risotto, and gelato. The file GroceryStore provides data on a collection of transactions in item-list format.

a. Using a minimum support of 100 transactions and a minimum confidence of 50%, use XLMiner to generate a list of association rules. How many rules satisfy this criterion?

b. Using a minimum support of 250 transactions and a minimum confidence of 50%, use XLMiner to generate a list of association rules. How many rules satisfy this criterion? Why may the grocery store want to increase the minimum support required for their analysis? What is the risk of increasing the minimum support required?

c. Using the list of rules from part b, consider the rule with the largest lift ratio that involves an Italian item. Interpret what this rule is saying about the relationship between the antecedent item set and consequent item set.

d. Interpret the support count of the item set involved in the rule with the largest lift ratio that involves an Italian item.

e. InterprettheconfidenceoftherulewiththelargestliftratiothatinvolvesanItalianitem. f. Interpret the lift ratio of the rule with the largest lift ratio that involves an Italian item.

g. What insight can the grocery store obtain about its purchasers of the Italian fare? h. How would you characterize this cluster?

i. Examine the smallest cluster. What makes this cluster unique? j. By examining the dendrogram on the HC_Dendrogram worksheet and the sequence

of clustering stages in HC_Output, what number of clusters seems to be the most natural fit based on the distance? What is the increase in distance if 7 clusters were used instead of 8 clusters?

k. How many clusters do you recommend? Why?

Reference no: EM132293945

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