(3) The error variance estimated from the misspecified model is a biased estimator of the true error variance g 2 The conventionally estimated variance of a2 is a biased estimator of the variance of the true estimator b2 B 2 .E[var(a2)]=var(b2)+ 2 21 ' Var(a2)will overestimate the true variance of b2, that is, it will have a positive bias. (4) The usual confidence interval and hypothesis-testing procedures are unreliable. The confidence interval will be wider（3）The error variance estimated from the misspecified model is a biased estimator of the true error variance σ2 ——The conventionally estimated variance of a2 is a biased estimator of the variance of the true estimator b2 ∵ E[var(a2 )]=var(b2 )+ ∴Var(a2 ) will overestimate the true variance of b2 , that is, it will have a positive bias. （4）The usual confidence interval and hypothesis-testing procedures are unreliable. The confidence interval will be wider.   2 2i 2 3i 2 3 (n - 2) x B x