Question

18. 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?

Only solve E F G

Answer 1

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?

Minimum Support Transaction = 100

Minimum Confidence = 50%

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?

Minimum Support Transaction = 250

Minimum Confidence = 50%

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.

Customers who purchases “hummus” tend to buy “peroni”.

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

Support for A & C is 252, so customers purchased hummus and peroni 252 times.

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

The highest lift ratio for Italian item is 82.62%. Hummus was purchased 305 times, and Peroni was purchased 252 times.

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

The lift ratio is 1.3798. Therefore, customer buy hummus is 37.98% likely to buy Peroni along with hummus.

g. What insight can the grocery store obtain about its purchasers of the Italian fare?

Customers has tendency to buy products with certain other products, such as hummus and peroni. According to the results, the store can understand the customers needs, which what products are bought along together.