![]() Specifically it assumes that y can be calculated from a linear combination of the input variables. In its most basic sense, linear regression is a statistical model that assumes a linear relationship between the input variables (x) and a single output variable (y). Unfortunately that makes learning about linear regression confusing for a beginner, because a lot of prior knowledge is often assumed, and multiple names are used interchangeably. Having been around for more than 200 years, and has been studied from every possible angle. This is a beginner-level introduction to the technique to give you enough background to be able to use it to solve business problems, and understand how best to interpret the findings from data science projects you delegate to your team. You do not need to know a lot about statistics or mathematics to use linear regression. When it makes sense to use Python’s SKLearn library instead (+ free script).How to use a linear regression calculator in Excel / Google Sheets (+ free template). ![]() What the linear regression equation is, and what assumptions we’re making in using it.Whether linear regression counts as machine learning or if it’s just plain statistics.What the difference is between logistic and linear regression.The benefits of adding more variables with multiple linear regression. ![]()
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