Normal Errors

W. D. Brinda
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W. D. Brinda: Yale University, Statistics and Data Science

Chapter Chapter 6 in Visualizing Linear Models, 2021, pp 113-132 from Springer

Abstract: Abstract Throughout this chapter, we will continue analyzing the linear model from Chap. 4 , but we will assume in particular that 𝜖 ∼ N ( 0 , σ 2 𝕀 ) $${\boldsymbol {\epsilon }} \sim N({\mathbf {0}}, \sigma ^2 {\mathbb {I}})$$ for an unknown σ 2. The figures in Chap. 4 already indicated iid Normal errors, although the results we derived in that chapter did not require such strong assumptions about the distribution of the errors. With the new Normality assumption, our earlier results remain valid of course, but we will also be able to do a good deal more in terms of inference.

Date: 2021
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DOI: 10.1007/978-3-030-64167-2_6

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