Normal probability plots with confidence for the residuals in linear regression |
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| Authors: | W Chantarangsi W Liu F Bretz S Kiatsupaibul A J Hayter |
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| Institution: | 1. Faculty of Science and Technology, Nakhon Pathom Rajabhat University, Nakhon Pathom, Thailand;2. S3RI and School of Mathematics, University of Southampton, Southampton, UK;3. Novartis Pharma AG, Basel, Switzerland;4. Department of Statistics, Chulalongkorn University, Bangkok, Thailand;5. Department of Business Information and Analytics, University of Denver, Denver, Colorado, USA |
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| Abstract: | Normal probability plots for a simple random sample and normal probability plots for residuals from linear regression are not treated differently in statistical text books. In the statistical literature, 1 ? α simultaneous probability intervals for augmenting a normal probability plot for a simple random sample are available. The first purpose of this article is to demonstrate that the tests associated with the 1 ? α simultaneous probability intervals for a simple random sample may have a size substantially different from α when applied to the residuals from linear regression. This leads to the second purpose of this article: construction of four normal probability plot-based tests for residuals, which have size α exactly. We then compare the powers of these four graphical tests and a non-graphical test for residuals in order to assess the power performances of the graphical tests and to identify the ones that have better power. Finally, an example is provided to illustrate the methods. |
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| Keywords: | Graphical tests Linear regression model Normal distribution Normal probability plot Power Residuals Simultaneous inference |
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