title: Correlation and simple linear regression.
abstract: In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.
authors.affiliation: Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA. zou@bwh.harvard.edu
authors.forename: Kelly H
authors.initials: KH
authors.lastname: Zou
authors.forename: Kemal
authors.initials: K
authors.lastname: Tuncali
authors.forename: Stuart G
authors.initials: SG
authors.lastname: Silverman
mesh_terms: D005163:Factor Analysis, Statistical; D005471:Fluoroscopy / Q000706:statistics & numerical data; D006801:Humans; D016014:Linear Models; D011829:Radiation Dosage; D015642:Radiology, Interventional / Q000706:statistics & numerical data; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data