📊Linear Regression (Slope & Intercept)
The slope and intercept of a linear regression line (ŷ = mx + b) describe the best-fit straight line through a scatter of data points, minimising the sum of squared vertical residuals (OLS).
- 1m = Σ(xi−x̄)(yi−ȳ) / Σ(xi−x̄)²
- 2b = ȳ − m × x̄
- 3Slope m has units of y/x
- 4Use for prediction: plug x into equation to get ŷ
Height vs weight → slope = 0.65 kg/cm=Each cm of height adds 0.65 kg to predicted weightSlope interpretation depends on units
⭐
Fun Fact
Francis Galton coined 'regression' in 1886 after noticing tall parents' children tend to be shorter — regression toward the mean is a statistical phenomenon, not a biological one.
References
🔒
100% Ücretsiz
Kayıt yok
✓
Hassas
Doğrulanmış formüller
⚡
Anında
Anında sonuçlar
📱
Mobil uyumlu
Tüm cihazlar