Abstract
The previous chapter developed the regression results involving linear functions of the dependent variable, \( \hat \beta\), Ŷ, and e. All were shown to be normally distributed random variables if Y was normally distributed.
This chapter develops the distributional results for all quadratic functions of Y. The distribution of quadratic forms is used to develop tests of hypotheses, confidence interval estimates, and joint confidence regions for β.
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© 1998 Springer-Verlag New York, Inc.
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(1998). Analysis of Variance and Quadratic Forms. In: Rawlings, J.O., Pantula, S.G., Dickey, D.A. (eds) Applied Regression Analysis. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/0-387-22753-9_4
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DOI: https://doi.org/10.1007/0-387-22753-9_4
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98454-4
Online ISBN: 978-0-387-22753-5
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