Regression & Linear Modeling - Info and Reading Options
By Jason W. Osborne

“Regression & Linear Modeling” Metadata:
- Title: Regression & Linear Modeling
- Author: Jason W. Osborne
“Regression & Linear Modeling” Subjects and Themes:
- Subjects: ➤ Regression analysis - Linear models - Analysis of variance - Mathematical statistics - Statistical methods - Linear models (statistics) - Linear models (Statistics)
Edition Identifiers:
- The Open Library ID: OL19636454W
AI-generated Review of “Regression & Linear Modeling”:
"Regression & Linear Modeling" Description:
The Open Library:
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.
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