"A regression model that uses the equation for a straight line." (Glenn J Myatt, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining", 2006)
"A quantitative model building tool that relates one or more independent variables (Xs) to a single dependent variable (Y)." (Lynne Hambleton, "Treasure Chest of Six Sigma Growth Methods, Tools, and Best Practices", 2007)
"A regression that deals with a straight-line relationship between variables. It is in the form of Y = a + bX, whereas nonlinear regression involves curvilinear relationships, such as exponential and quadratic functions." (Jae K Shim & Joel G Siegel, "Budgeting Basics and Beyond", 2008)
"In statistics, a method of modeling the relationship between dependent and independent variables. Linear regression creates a model by fitting a straight line to the values in a dataset." (Meta S Brown, "Data Mining For Dummies", 2014)
"Linear regression is a statistical technique for modeling the relationship between a single variable and one or more other variables. In a machine learning context, linear regression refers to a regression model based on this statistical technique." (Alex Thomas, "Natural Language Processing with Spark NLP", 2020)
"is an area of unsupervised machine learning that uses linear predictor functions to understand the relationship between a scalar dependent variable and one or more explanatory variables." (Accenture)
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