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Linear Regression
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Linear Regression
An Introduction to Statistical Models

  • Peter Martin - University College London, UK, Lecturer in Applied Statistics in the Department of Applied Health Research at University College London.
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March 2022 | 200 pages | SAGE Publications Ltd
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

 
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
 
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