Simple Linear Regression: A layman's explanation

Machine learning and statistics have many applications in business and the social sciences. However, the theory is often intimidating and not easily understood. In this series of articles, I aim to demystify the concepts behind the common tools used in data science and machine learning, starting with linear regression. Linear regression is a statistical method that allows us to describe relationships between variables (distinct things that can be measured or recorded, such as height, weight, and hair colour). It is an extension of the General Linear Model, a framework to describe how a variable of interest can be modelled using other predictor variables. In simple linear regression (SLR), we focus on the relationship between two continuous variables, x and y (hence, simple).