SAS PROJECT
Budget: $30 – $250 USD
General Instructions
Select a data set: You may select any data set for your project. Identify and perform SAS analyzes on the dataset.
Some examples of data projects:
CDC – Health Data.
Sports Data – Football, Basketball, Baseball, etc. Weather Data – Hurricanes, Tornadoes, Wild Fires, etc.
Company Data – One of your current employer’s datasets (de-identified).
Dataset of interest from kaggle.com
Any data, any topic is acceptable. For large datasets, I would suggest that you work with a small portion of your dataset (less than 10000 rows) for performance reasons as you are building your code, and then when you have developed and tested your code, try it on a larger number of rows and work up to the full dataset.
SAS and Analytics: Using functionality from each of the lessons from our SAS course, please perform data cleaning on the dataset and use your cleaned dataset in a statistical analysis using some of the SAS statistical procedures you have learned (freq, univariate, means, reg). You must decide the best SAS procedures to use based upon the variables in the data.
Business Perspective: Overall - what are the results? Based upon your findings, what would be your advice to an organization? What would be your next steps for further analysis?
Submission
Students will submit the project as two deliverables:
Deliverable 1: Clean and combine individual datasets into one working dataset for your statistical analysis.
Deliverable 2: Complete any additional data preparation/analysis needed and perform a statistical analysis using your cleaned and prepared data.
The final report should be written in Microsoft Word with an Executive Summary. In addition to your final report, include the following items:
SAS Syntax (code) – All code for these analyses.
Output from running the code.
Explanation of your procedures.
This project should be a demonstration of your ability to apply what we’ve learned to another domain. You can be as creative as you’d like, as time allows. There is no need to go overboard.
Select a data set: You may select any data set for your project. Identify and perform SAS analyzes on the dataset.
Some examples of data projects:
CDC – Health Data.
Sports Data – Football, Basketball, Baseball, etc. Weather Data – Hurricanes, Tornadoes, Wild Fires, etc.
Company Data – One of your current employer’s datasets (de-identified).
Dataset of interest from kaggle.com
Any data, any topic is acceptable. For large datasets, I would suggest that you work with a small portion of your dataset (less than 10000 rows) for performance reasons as you are building your code, and then when you have developed and tested your code, try it on a larger number of rows and work up to the full dataset.
SAS and Analytics: Using functionality from each of the lessons from our SAS course, please perform data cleaning on the dataset and use your cleaned dataset in a statistical analysis using some of the SAS statistical procedures you have learned (freq, univariate, means, reg). You must decide the best SAS procedures to use based upon the variables in the data.
Business Perspective: Overall - what are the results? Based upon your findings, what would be your advice to an organization? What would be your next steps for further analysis?
Submission
Students will submit the project as two deliverables:
Deliverable 1: Clean and combine individual datasets into one working dataset for your statistical analysis.
Deliverable 2: Complete any additional data preparation/analysis needed and perform a statistical analysis using your cleaned and prepared data.
The final report should be written in Microsoft Word with an Executive Summary. In addition to your final report, include the following items:
SAS Syntax (code) – All code for these analyses.
Output from running the code.
Explanation of your procedures.
This project should be a demonstration of your ability to apply what we’ve learned to another domain. You can be as creative as you’d like, as time allows. There is no need to go overboard.