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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: An Introduction to Statistical Models

What is a statistical model

Simple linear regression

Assumptions and transformations

Multiple linear regression: A model for multivariate relationships

Multiple linear regression: Inference, assumptions, and standardization

Where to go from here