A grocery store would like to gain insight into its customers' purchase to possibly improve its in-aisle product placement and cross-product promotions. The table below contains a small sample of data in which each transaction consists of the items purchased by a shopper in a single visit to the store.

Transaction	Items
1	bread, eggs, milk
2	bread, sugar
3	bread, cereal
4	bread, milk, sugar
5	cereal, milk
6	bread, cereal
7	cereal, milk
8	bread, cereal, eggs, milk
9	bread, cereal, milk
10	bread, cereal, eggs, milk

The support count of antecedent and consequent = __________.

Question 30 options:

	5
	6
	3
	2
	8
	4
	7
	1

Question 1B (2 points)

The lift ratio =

Round the final answer to two decimal places, e.g., 0.12, when necessary.

Question 1A (2 points)

The confidence =

Round the final answer to two decimal places, e.g., 0.12, when necessary.

Question 1C (1 point)

Consider the following statement:

For the sample data, the aforementioned association rule "If {cereal, eggs}, then {bread}" is more useful in identifying a customer who is likely to purchase bread than no association rule at all (e.g., random sampling).

This statement is __________.

Question 1C options:

	cannot tell whether it is true or false; more information is needed.
	true
	false