Marketing Analytics Fall 2021

Marketing Analytics Fall 2021 Final Project
Writing is an important part of any analysis work. Learning to convey your findings – both visually
(e.g., graphs) and with words – is important.
The final project requires each student to perform data analysis tasks/research of a marketing
data set selected by the student using SAS Studio tool. Each student will produce a Project
Proposal, a Project Presentation, and a Final Project Paper (which is a written report detailing the
analysis techniques and the findings of the project) with a SAS syntax file.
Data Set: The data set may be your own or may be obtained from an external source. The data set
must be related to marketing (e.g. consumers, profits, sales, costs, etc.) and there must be enough
data to perform necessary analyses. Here are some links where you may find good datasets:
• https://toolbox.google.com/datasetsearch
• https://aws.amazon.com/fr/datasets/
• https://www.kaggle.com/datasets
• http://archive.ics.uci.edu/ml/index.php
Analyses: You must use SAS Studio that we learn and practice in this course to conduct all your
analyses. In your analyses, you should cover at least three of the analyses topics we talk about in
this course. However, covering 4 to 5 topics is recommended in order to gain excellent points in
Completeness and Thoroughness (Please see GRADING at the last page). They include:
• Data preprocessing: how to clean, aggregate, match the raw data sets and how to
transform, clean different variables
• Descriiptive analysis: summary/descriiptive statistics for your data
• Data visualization: different tables, charts, graphs to help audience better understand your
analyses and your findings
• Statistical analysis: hypothesis testing with assumptions and limitations, testing for
differences between groups and for predictive relationships
• Predictive analysis: predictive models (such as linear regression) with their assumptions and
limitations
Paper: The paper should not be too lengthy but needs to be long enough so that I understand what
the data and analyses are, the conclusions you make, and know how you arrived at the conclusions.
6 to 12 pages (DOUBLE spaced, font size 12, excluding visualizations, dataset, code/spreadsheets
and other attachments or reference material) should be enough.
SAS syntax file: When you submit your final project paper, you should also submit a SAS syntax file
called “YourLastName_sassyntax” separately, which include the codes/syntax you generate/use to
conduct your project. If you fail to submit this file or the syntax could not reflect the work you have
done for your project paper, you may receive a failing score for your project.
Citation format: You must include proper citation in both final project presentation and paper. You
are allowed to use the citation formatting that you prefer for this project. Your paper will be
checked by NYU Turnitin tool for plagiarism. If you fail to use proper citation, or the paper you
submit contain more than 30% exact wording from other sources, you may receive a failing score
for your project.
1. Final Project Proposal – Due Date: Wednesday, 11/10/2020, 6pm
You will need to turn in a 1-page paper (SINGLE spaced) proposal (Word/PDF) called
“YourLastName_proposal”. The proposal should have the following 5 headers:
• Background: 1 paragraph giving the overall problem
• Purpose: 1 paragraph that begins: “In this paper, …” (Provide the goals of what you will
accomplish in the paper and how.)
• Data: 1 paragraph telling the data source, and important features of the data (links to the
data set, sample size, who was sampled, year collected, covariates you will use)
• Analysis plan: 1-2 paragraphs with your analysis plan.
• Discussion: 1 paragraph on how your results will help answer the question/problem you
posed in “purpose.”
please divide into 5 paragraph base on the bullet point and chose a topic that data is easily obtain.Thanks