Title: Forecasting the Recovery: A Capstone Analysis of US Housing Data (2005-2013): Business Statistics and Analysis Capstone Project

 

Introduction: From Data to Dollars

For my Business Statistics and Analysis Capstone, I tackled the complex dynamics of the US housing market using HUD's THADS data (2005–2013). The goal wasn't just to report what happened, but to build a robust model capable of forecasting future market values. This project showcases the power of statistical rigor in transforming messy, skewed real-world data into actionable predictive insights.

Key Analysis Highlights

  1. Measuring the Crisis Impact on Rent: I used paired t-tests (2007 vs. 2009) on Fair Market Rent (FMR) and found that the 2008 Subprime Crisis did not decrease rents; instead, the crisis accelerated the rise in mean FMR, as foreclosures moved people into the rental market. This finding directly challenges assumptions about market deflation.

  2. Modeling Market Value Drivers: I developed a Multiple Linear Regression model for single-family home values, employing log transformations (LN(VALUE), LN(FMR), LN(UTILITY) to correct for extreme skewness. The model confirmed that local FMR is the single strongest predictor of a home’s value, and quantified the penalty associated with a unit being vacant (approx 11.5% reduction).

  3. Building a Time-Lagged Forecasting Engine: The final step involved building a predictive model using 2011 features (Predictors_2011) to forecast 2013 values (VALUE_2013). This required merging datasets on the CONTROL variable and obtaining a set of beta coefficients.

  4. Validation and Risk Quantification: I validated the model's performance on a 1,000-unit holdout sample. The final measure of accuracy, the Mean Absolute Deviation (MAD), was calculated at $136,966. This single metric quantifies the average forecasting error, allowing a business analyst to understand the financial risk when utilizing the model for strategic planning.

Conclusion

This capstone demonstrated end-to-end analytical capability: from cleaning and transforming complex real-estate data to running predictive validation. The result is a statistically grounded, highly interpretable model that quantifies market drivers and provides a measure of confidence for future forecasts.

Comments

Post a Comment

Popular posts from this blog

Google Analytics Case Study Project.

Image
   Welcome to My Data Analytics Portfolio. I am Mr Matthew Ternenge Beeun, an aspiring data analyst with a passion for transforming raw data into actionable insights. This portfolio showcases my work on the Bellabeat case study, where I applied SQL, R, and Tableau to clean, analyze, and visualize user behavior data from smart wellness devices. The goal of this project was to uncover patterns that could inform Bellabeat’s business strategy and marketing decisions. Below, you’ll find my datasets, code files, visualizations, and stakeholder report—all organized for clarity and impact. Table of Contents 1. Project Overview 2. Data Cleaning (SQL) 3. Visualizations. (Tableau) 4. Stakeholder Report (R Markdown) 5. Downloadable Files 6. External Links(Github, Kaggle) 1. Project Overview Bellabeat Case Study This portfolio project explores user behavior data from Bellabeat, a wellness tech company that manufactures smart devices for tracking fitness, activity, sleep, and health metr...
Read more

Google Data Analytics Project 2: Bike Share Case Study Project

Image
  Transforming Data into Strategy: How I Converted Cyclistic 's Casual Riders into Members. Published on:  18th October, 2025 Tags: #DataAnalytics #CaseStudy #RStudio #Tableau #Cyclistic #MarketingStrategy Introduction: The Business Problem As a Data Analyst for the fictional bike-share company Cyclistic , my core mission was simple: How do annual members and casual riders use Cyclistic bikes differently, and how can we use that insight to convert casual riders into annual members? This project moved through the entire data analysis process—from Ask to Act—culminating in clear, data-backed marketing recommendations for the Director of Marketing. 1. Ask & Prepare: Defining the Challenge The business objective was to drive membership growth. We started with 12 months of Cyclistic trip data (publicly available historical data) and prepared it for analysis. Below are the datasets that are made available for this project:   Initial Challenge: The data was inconsistent, ...
Read more

Teach your Child Coding

Image
  Why Every Child Needs a Coding Adventure: A Guide for Modern Parents ​In today’s fast-paced world, we often hear the term "digital native" applied to our children. They can swipe, tap, and navigate a smartphone before they can even tie their shoelaces. But there is a profound difference between being a passive consumer of technology and being an active creator of it. ​At Bummptech Global Concept , we believe that learning to code is about much more than just computers—it’s about giving your child the tools to build their own future. ​The New Universal Language ​Just as we learn to read and write to navigate society, coding has become the "new literacy." It is the language of the modern world. Whether a child grows up to be a software engineer, a doctor, a designer, or a businessman, the ability to understand how digital systems work will be their greatest competitive advantage. ​4 Reasons to Start the Coding Journey Early ​1. From Consumption to Creation ​M...
Read more