《回归与线性建模：最佳实践与现代方法（真EPUB版）》

English | ISBN: 1506302769 | 2016 | 488 pages | True EPUB | 19 MB

In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

在轻松的语气下，《回归与线性建模》提供了一种易于理解的概念性的广义线性模型（GLM）覆盖。读者将熟悉普通最小二乘法（OLS）回归、二元和多分类逻辑回归、有序回归、泊松回归及对数线性模型的应用。作者贾森·W. 奥斯本在整个文本中多次回到某些主题，比如测试假设、检查数据质量以及在不同的线性模型类型下适当时建模非线性和非加性的效应。

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