Cosmetic Sales Pattern Analysis & Course Recommendation
Budget: $30 – $250 USD
Page
4
of 4
Assignment 3
Instruction:
You can use this WORD file as an answer sheet. Attach required output below each question. R
codes can be attached to each question for partial credits if your results are not correct. Once you
have completed, please upload the PDF version of this answer sheet to the course site.
Name the word file as: YourName.doc Assignment policy (Syllabus): Each assignment carries the same weight towards the overall
grade. You need to work independently on your home assignments. I will not check your
homework before your turn it in. You can ask clarifying questions about what the homework
asks, and underlying material, but not the correct solution or whether your answer is okay. Office
hours are intended for answering questions about class materials, instead of showing solutions to
homework questions. You are expected to use your own critical thinking, and apply course
materials to solve the homework problems. Late assignments will be assessed a 30% penalty
(subtracted from that assignment’s score). Once the solution is posted, no credit will be given for
assignments. Scores for assignments are finalized one week after the grades are posted.
Thereafter there will be no changes and no re-grading.
Dataset: Cosmetics.csv
A large national drugstore chain wants to better understand customer buying patterns across its cosmetics
products. Managers believe that analyzing associations among product purchases will help them:
• Decide how to group products in point-of-sale displays
• Provide guidance to sales personnel in suggesting cross-sales
• Pilot a real-time electronic recommender system at checkout to encourage additional purchases
The dataset Cosmetics.csv contains purchase records in binary matrix form. Each row corresponds to a
single transaction, and each column corresponds to a product. A value of 1 indicates the product was
purchased in that transaction, while a 0 indicates it was not. For example, if the entry under “Bag” is 0
and the entry under “Blush” is 1, the customer did not buy a bag but did buy blush in that transaction.
The store has asked you to analyze this data using association rule mining to uncover cross-purchase
patterns.
4
of 4
Assignment 3
Instruction:
You can use this WORD file as an answer sheet. Attach required output below each question. R
codes can be attached to each question for partial credits if your results are not correct. Once you
have completed, please upload the PDF version of this answer sheet to the course site.
Name the word file as: YourName.doc Assignment policy (Syllabus): Each assignment carries the same weight towards the overall
grade. You need to work independently on your home assignments. I will not check your
homework before your turn it in. You can ask clarifying questions about what the homework
asks, and underlying material, but not the correct solution or whether your answer is okay. Office
hours are intended for answering questions about class materials, instead of showing solutions to
homework questions. You are expected to use your own critical thinking, and apply course
materials to solve the homework problems. Late assignments will be assessed a 30% penalty
(subtracted from that assignment’s score). Once the solution is posted, no credit will be given for
assignments. Scores for assignments are finalized one week after the grades are posted.
Thereafter there will be no changes and no re-grading.
Dataset: Cosmetics.csv
A large national drugstore chain wants to better understand customer buying patterns across its cosmetics
products. Managers believe that analyzing associations among product purchases will help them:
• Decide how to group products in point-of-sale displays
• Provide guidance to sales personnel in suggesting cross-sales
• Pilot a real-time electronic recommender system at checkout to encourage additional purchases
The dataset Cosmetics.csv contains purchase records in binary matrix form. Each row corresponds to a
single transaction, and each column corresponds to a product. A value of 1 indicates the product was
purchased in that transaction, while a 0 indicates it was not. For example, if the entry under “Bag” is 0
and the entry under “Blush” is 1, the customer did not buy a bag but did buy blush in that transaction.
The store has asked you to analyze this data using association rule mining to uncover cross-purchase
patterns.