Includes bibliographical references and index.

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

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 variables and 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

College of Education Bachelor of Secondary Education major in Mathematics

In English