In this program
- Least squares estimation of slope
- Intercept
- Interpretation of coefficients and R²
- Inference for regression parameters
- Prediction intervals
- Confidence bands
- Assumptions: linearity, homoscedasticity, normality of errors
Simple linear regression
Assumptions: linearity, homoscedasticity, normality of errors
Regression analysis · STEM / applied
Topic
Assumptions: linearity, homoscedasticity, normality of errors
Undergraduate Regression analysis — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).