Least-squares estimators are unbiased
Proposition taught in Linear regression, part of Statistical inference
Least-squares estimators are unbiased
| Type | Proposition |
| Taught in | Linear regression |
| Part | Statistical inference |
If \mathbb{E} Y_i=\beta_0+\beta_1x_i for every i, then \mathbb{E}\widehat\beta_1=\beta_1 and \mathbb{E}\widehat\beta_0=\beta_0. No assumption about the error distribution is needed.
Used in
- Taught in Linear regression, where the derivation and examples are.
- All 5 questions on Linear regression
See also
Least-squares line · Simple linear regression · Sampling distribution of the regression estimators · Slope t pivot · Coefficient of determination · Prediction interval