To understand a linear model, such as y = mx + b, you need to know that the dependent variable like y varies linearly with an independent variable like x. In real life, you can model almost anything linearly, such as modelling a person's math's score as a linear function of the number of hours studied, family socioeconomic status and number of accelerated classes.

In the earlier math example, the number of hours studied makes the biggest difference in math scores, followed by number of accelerated classes, followed by socioeconomic status ( yes ! ). This coefficient m in the equation above measures the magnitude of the variable.

Another concept in linear regression is the notion of significance or p-value. A low p-value of 5% or even 1% means that there is a large confidence that the coefficient is significantly higher than zero. A coefficient can be significant and yet be of