Ebook: Linear Regression: An Introduction to Statistical Models
Author: Peter Martin
- Genre: Science (General) // Science of Science
- Series: The SAGE Quantitative Research Kit
- Year: 2022
- Publisher: SAGE Publications
- City: Los Angeles
- Language: English
- pdf
Part of The SAGE Quantitative Research Kit, this text helps you make the crucial steps towards mastering multivariate analysis of social science data, introducing the fundamental linear and non-linear regression models used in quantitative research. Peter Martin covers both the theory and application of statistical models, and illustrates them with illuminating graphs, discussing:
· Linear regression, including dummy variablesand predictor transformations for curvilinear relationships
· Binary, ordinal and multinomial logistic regression models for categorical data
· Models for count data, including Poisson, negative binomial, and zero-inflated regression
· Checking model assumptions and the dangers of overfitting
· Linear regression, including dummy variablesand predictor transformations for curvilinear relationships
· Binary, ordinal and multinomial logistic regression models for categorical data
· Models for count data, including Poisson, negative binomial, and zero-inflated regression
· Checking model assumptions and the dangers of overfitting
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