A full exploratory and statistical analysis project built around the Ames Housing dataset, a well-known dataset in data science and machine learning. It demonstrates end-to-end data wrangling, visualization, and statistical modeling techniques.

Project Workflow

Data Cleaning

• Handling missing values and outliers.
• Encoding categorical variables for analysis.

Exploratory Data Analysis (EDA)

• Univariate, bivariate, and multivariate plots.
• Distribution of sale prices, neighborhood comparisons, and quality ratings.

Feature Engineering

• Transformations (e.g., log of sale price).
• Derived features to improve model performance.

Statistical Testing

• Hypothesis tests confirming neighborhood effects on prices.
• Regression analysis to identify key predictors.