Data Analytics for Business Professionals Program (DABP) Advanced Analytics and Machine Learning Group Project

Fall 2018

Project Tree

Folder Name	Description
`literature`	This folder will store all relevant literature related to the project.
`raw_data`	This folder will store the raw data files needed for our group project.
`src`	This will store all source code used for the project.
`write_data`	This folder will store all data files created from the `raw_data` files.

What features influence the increase or decrease of corn acreage¹ over time?
- Our null hypothesis is that the ratio of the corn to soy prices is a key decision factor. Can we reject it?
If possible, how do weather patterns influence corn acreage over time?

United States Department of Agriculture Farm Service Agency annual crop acreage data for every state from 2011 to 2017².
National Centers for Environmental Information monthly average temperature from January 2011 to December 2017 for the contiguous United States³.

Create a linear regression model to predict corn acreage for the next year.
Create clusters based on different crops, states, or years to determine any relevant groups that may be of interest to us to understanding corn acreage growth.

¹ Hubbs, Todd. 2018. “Weekly Outlook: Corn and Soybean Acreage in 2018”. Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign. Available at: http://farmdocdaily.illinois.edu/2018/03/corn-soybean-acreage-2018.html.

³ National Oceanic and Atmospheric Administration. 2018. “Climate at a Glance”. National Centers for Environmental Information. Available here: https://www.ncdc.noaa.gov/cag/national/time-series/110/tavg/1/1/2011-2017?base_prd=true&firstbaseyear=2011&lastbaseyear=2017.