The article finds that in linear and quadratic regression models with correlated errors, equally spaced designs are often very efficient, even for highly correlated observations. D-optimal designs for weighted least squares analysis are determined, showing that the equally spaced design is close to optimal in many cases. For estimating the slope in linear regression, D-optimal designs for weighted least squares are compared to those for ordinary least squares, with the former generally yielding better efficiency.