Overview
In this project, you will use R to solve counting and probability problems. To gain the most benefit from this project, avoid calculating numeric values and entering them into R. Instead, use R to do all necessary calculations. This project analyzes trends in U.S. housing prices and affordability using open-source data. The goal
is to answer seven analytical questions using charts, graphs, and written explanations, culminating in a 2-3-slide presentation and a 1-2 page report.
Data Sources
Instructions
To complete this assignment, you will produce and submit two files: A report (PPT) containing answers and visual results following the use of R scripts, along with a Doc file addressing the questions. To successfully complete this project, carefully follow all instructions. Pay special attention to formatting guidelines.
Submission Guidelines
To build an R script inside of RStudio.
Make use of the included files as directed in the instructions.
-US_Housing_Prices & Affordability – final_housing_prices_affordability
Complete all assigned tasks on the instruction sheet.
Use the testing script to verify your script for accuracy, including all specified variable names.
Review all work prior to Canvas upload. Specifically, do the following tasks:
Use R to complete the following tasks and create visualizations:
Regional Comparison Analyst: Analyze state/city and regional differences; create
bar charts/heat maps; write findings.
Analytical Questions
Answer the following two questions and write them into the Doc file:
1.Which states or cities have the highest median home prices?
2.How do housing prices differ across regions (e.g., Northeast vs. Midwest)?
o The R script file named Lastname_Project_Script.PDF
o The report named Lastname_Project_Report.Doc
Requirements: 2-3-slide presentation and a 1-2 page report
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