How does a quadratic model differ from linear model?

In a linear model, the plotted data follows a straight line. Every data point may not fall on the line, but a line best approximates the overall shape of the data. You can describe every linear model with an equation of the following form:

y = mx + b

In this equation, the letter "m" describes the angle, or "slope," of the line. The "x" describes any chosen value on the horizontal axis, while the "y" describes the number on the vertical axis that corresponds to the chosen "x" value.

In a quadratic model, the data best fits a different type of curve that mathematicians call quadratic. Quadratic models have a curved shape that resembles the letter "u." You can describe all quadratic models with an equation of the form:

Y = ax^2 + bx + c

As with linear models, the "x" corresponds to a chosen value on the horizontal axis and "y" gives the correlating value on the vertical axis. The letters "a," "b" and "c" represent any number, i.e., they will vary from equation to equation