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Titlebook: Energy Risk Modeling; Applied Modeling Met Nigel Costa Lewis Book 2005 Palgrave Macmillan, a division of Macmillan Publishers Limited 2005

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發(fā)表于 2025-3-26 21:11:28 | 只看該作者
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發(fā)表于 2025-3-27 03:40:39 | 只看該作者
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發(fā)表于 2025-3-27 09:46:10 | 只看該作者
https://doi.org/10.1007/978-94-007-6113-1tions of the model. If the assumed underlying statistical assumptions are invalid the inference based on it will be unreliable. The primary objective of this chapter is to outline the key assumptions of the linear regression model and provide some elementary techniques for validating or refuting these assumptions given a specific data set.
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發(fā)表于 2025-3-27 14:18:56 | 只看該作者
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發(fā)表于 2025-3-27 20:13:04 | 只看該作者
A Primer in Applied Regression Analysisrgy) examples before we move onto discuss more energy-specific applications of regression in the remaining chapters of this book. The emphasis of this chapter is therefore on you the reader becoming comfortable with the ideas surrounding regression and replicating for yourself the examples given in .
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發(fā)表于 2025-3-27 22:09:09 | 只看該作者
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發(fā)表于 2025-3-28 11:42:45 | 只看該作者
Static charging by spray electrification, population values or it may indicate that the conjecture is untenable. Hypothesis testing is a formal mechanism by which we can make and test inferential statements about the characteristics of a population. It uses the information contained in a sample to assess the validity of a conjecture about a specific population parameter.
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