This project requires each student to perform data analysis tasks/research of a marketing data set selected by the student using SAS Studio tool.

 The final project requires each student to perform data analysis tasks/research of a marketing data set selected by the student using the SAS Studio tool. Each student will produce a Project Proposal 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 must be obtained from an external publicly available source. That you will provide a direct link to. 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

·         Descriptive analysis: summary/descriptive 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. 5 to 10 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_YourFirstName_Project_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 your 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.

DETAILED INSTRUCTIONS 

You will need to turn in a 1-page paper (SINGLE spaced) proposal (Word or PDF) called “YourLastName_YorFirstName_project_proposal”. The proposal should have the following 5 sections:

·         Background: 1 paragraph description of the overall problem you will solve

·         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.”

 You will need  turn in your paper (DOUBLE spaced, font size 12, Word or PDF) called “YourLastName_YourFirstName_Final_Project”. I have offered one way to organize your paper below, but feel free to do what works best for you. You need to make sure that the organization is easy to follow.

 ·         Introduction/background—A brief (approximately one page) general description of the problem, including:

o   Why the problem is of interest—you might refer to previous studies using this, or similar data sets.

o   A brief summary of the methods utilized—tell me what methods you have utilized, e.g., “I perform a significance hypothesis testing to examine the differences of cereals across the shelf on which they are displayed.” Detailed information about the methods should be left for a later section.

o   The main results of your analysis.

·         Data/Data Preprocessing:

   Information about the data set (e.g, the source of the data, how many observations, number of variables, etc.)

o   If you make any change to the raw data set, you should describe how you change it and why you change it as part of data preprocessing (e.g. you delete the observations with missing values, you select random samples in the data set, etc.)