BMW Price vs Mileage (2010–2024): Unveiling Value Retention Patterns

Overview

This analysis examines whether the mileage of BMW vehicles significantly influences their market price between 2010 and 2024. The goal was to understand depreciation trends and assess whether usage (in kilometers driven) materially affects resale or market valuation.

Methodology

We used a simple linear regression model to quantify the relationship between Price_USD (dependent variable) and Mileage_KM (independent variable).

Model Output:

$$\text{Price} = -0.0019 \times \text{Mileage} + 75225.35$$

• Slope: -0.0019 (negative, but near zero)

• Intercept: 75,225.35 USD

• R² = 1.79 × 10⁻⁵

Interpretation

The regression results indicate an extremely weak correlation between mileage and price.

• The slope is almost zero, suggesting that as mileage increases, the price changes very little.

• The R² value (~0.000018) indicates that mileage accounts for less than 0.002% of the variation in BMW prices.

• Visually, the scatter plot displays a dense cloud with no clear downward trend,  confirming the absence of a meaningful linear relationship.

Key Insights

1. Minimal Depreciation Effect: BMW’s market prices seem resilient to mileage, reflecting brand prestige, high-quality engineering, and luxury perception.

2. Market Positioning: Buyers may value design, performance, and model year more than mileage, consistent with premium consumer behavior.

3. Policy Implication: The result challenges conventional assumptions about vehicle depreciation; policymakers may need to reassess vehicle valuation criteria for taxation and insurance in luxury segments.

4. Investment View: For consumers, this highlights BMW’s strong value retention, particularly relevant for secondary markets in Europe and Africa.

Acknowledgments

• Data Source: BMW Sales Data (2010–2024), processed within the DatalytIQs Academy Analytics Framework.

• Analysis & Visualization Tools: Python, pandas, matplotlib, numpy, scipy.stats.

• Contributors:

  • Collins Odhiambo Owino — Lead Analyst & Author, DatalytIQs Academy

  • Kaggle Open Data Contributors — Dataset inspiration and structure

  • BMW Group Market Reports — Reference for brand pricing context

Author’s Note

Written by Collins Odhiambo Owino
Founder & Lead Researcher, DatalytIQs Academy
Empowering learners and professionals in Mathematics, Economics, and Finance through data-driven insight.