title: Correlation and simple linear regression.
abstract: This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.
authors.affiliation: Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Lynn E
authors.initials: LE
authors.lastname: Eberly
mesh_terms: D000704:Analysis of Variance; D006801:Humans; D016014:Linear Models; D008545:Melanoma / Q000235:genetics; D012107:Research Design; D014158:Transcription, Genetic