SAS-Grain-Prices

Final project for BIOS 7400 with Xiao Song at the University of Georgia (USA), Spring 2022. Simple analysis in SAS v9.4 of grain price trends.

Image is sourced from Wikimedia.

File Structure

• code: contains SAS code files used for cleaning and analyzing data.
• data: contains all data used for this analysis.
  • SAS: contains cleaned .sas7bdat dataset files.
  • raw: contains raw text and Excel data downloaded from the internet.
• figs: contains all images which will be displayed in either READMEs or the final paper.
• manuscript: contains .tex and associated files which constitute the final paper.

Objectives

The goals for this project are as follows.

• Introduce the datasets and provide brief background on research questions of interest (write the introduction section).
• Import the datasets and transform into the correct rectangular form for merging, if necessary. Name and label all variables.
• Merge the datasets by year.
• Manipulate, transform, and clean the merged dataset as necessary for analysis.
• Justify the data management process (write the methods section).
• Analyze the cleaned data to produce analytical results.
• Produce figures and tables that are clear and meaningful.
• Summarize the results of the analysis (write the results section).
• Briefly interpret the results and connect to the research questions (write the discussion section).
• Ensure all SAS code is documented and maintainable.

Data sources

This project uses three separate data sources.

1. USDA feed grains database: can be accessed on the USDA website. I downloaded all data from the database, which you can replicate using this direct download link.
2. NASA land-ocean temperature index data: can be accessed on NASA's GISTEMP website. The direct download link is here.
3. US presidential party by year dataset: downloaded from an article in The Guardian.

Language

Data cleaning and analysis will be performed using SAS v9.4. I do not own a SAS license, so I will be using SAS on Demand for Academics.

Licenses

Text and figures: All prose and images are licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

Code: All code is licensed under the GNU Affero General Public License v3.0.

Acknowledgements

• The assignment instructions for this project were created by Xiao Song at the University of Georgia.
• I first worked on the USDA feed grains database for a project for John Wagaman's MATH 375 class at Western Carolina University. This project would not have been possible without several hours of his time in 2019. Indeed, I likely would not be in grad school for data analysis without John's advice.
• Technically, the University of Georgia Graduate School paid me to do this work, as they provide my funding.