Assignment Paper

HW9: Chapter 14 Association Rules
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Instructions:
1. All HWs require self-study (from the books and the Internet). Please be prepared to learn
new knowledge when doing the HWs. But, those that are not taught in the class will not be
tested in quizzes and final.
Problem 1
Cosmetics Purchases. The data shown in Table 14.11 and the output in Figure 14.4
are based on a subset of a dataset on cosmetic purchases (Cosmetics.xlsx) at a large
chain drugstore. The store wants to analyze associations among purchases of these items for
purposes of point-of-sale display, guidance to sales personnel in promoting cross sales, and
guidance for piloting an eventual time-of-purchase electronic recommender system to boost
cross sales. Consider first only the data shown in Table 14.11, given in binary matrix form.
a. Select several values in the matrix and explain their meaning.
b. Consider the results of the association rules analysis shown in Figure 14.4.
i. For the first row, explain the “Conf. %” output and how it is calculated.
ii. For the first row, explain the “Support for A,” “Support for C,” and “Support
for A & C” output and how it is calculated.
iii. For the first row, explain the “Lift Ratio” and how it is calculated.
iv. For the first row, explain the rule that is represented there in words.
Now, use the complete dataset on the cosmetics purchases (in the file Cosmetics.xlsx).
v. Using XLMiner, apply association rules to these data (use the default
parameters).
vi. Interpret the first three rules in the output in words.
vii. Reviewing the first couple of dozen rules, comment on their redundancy and
how you would assess their utility.
2
TABLE 14.11 EXCERPT FROM DATA ON COSMETICS PURCHASES IN BINARY MATRIX
FORM
Trans. # Bag Blush NailPolish Brushes Concealer Eyebrow Pencils Bronzer
1 0 1 1 1 1 0 1
2 0 0 1 0 1 0 1
3 0 1 0 0 1 1 1
4 0 0 1 1 1 0 1
5 0 1 0 0 1 0 1
6 0 0 0 0 1 0 0
7 0 1 1 1 1 0 1
8 0 0 1 1 0 0 1
9 0 0 0 0 1 0 0
10 1 1 1 1 0 0 0
11 0 0 1 0 0 0 1
12 0 0 1 1 1 0 1