Let the independent variable be the number of years you have worked at a company and the dependent variable your yearly wage. Further, suppose that each year you receive a raise of $1500.

The relationship between years at the company and your yearly wage will be linear. If the starting...

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Let the independent variable be the number of years you have worked at a company and the dependent variable your yearly wage. Further, suppose that each year you receive a raise of $1500.

The relationship between years at the company and your yearly wage will be linear. If the starting wage was $30,000, then the relationship can be described or modeled by the function w=1500Y+30000 where W is the wage and Y is the number of years.

A given coordinate, say (3,34,500) represents that you have worked 3 full years for the company, and this year your wages will be $34,500. In the model, the 1500 represents the yearly increase in earnings, while the 30000 represents the initial value (i.e. when you are first hired.)

Note that for this example, the domain (accepted inputs for the independent variable) are non-negative integers.

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If you would prefer a continuous model (i.e. a model that accepts any real number as an input) consider the following:

Let the independent variable be rainfall in inches, and the dependent variable be the depth of a certain lake. We suppose that the area drained by the lake and the shape of the lake are such that as each inch of rain falls, the lake's depth increases by 1/2 inch.

Then the model is D=1/2R+960. Here 960 inches is the initial depth of the lake, R is the amount of rainfall in inches, and D the depth of the lake in inches.