Sure! Let's consider a real-world example of a company's revenue over time. The independent variable is time, measured in months, and the dependent variable is the company's revenue, measured in thousands of dollars.

Suppose we have data that shows the company's revenue after 4 months is $100,000 and after 6 months it is $120,000. Using this data, we can calculate the slope of the line as (120,000 - 100,000) / (6 - 4) = 20,000 / 2 = 10,000.

This means that for every month that passes, the company's revenue increases by $10,000. The y-intercept can be calculated by finding the value of the dependent variable when the independent variable is 0, which in this case would be $0 since the company didn't exist before it started generating revenue.

The x-intercept can be calculated by finding the value of the independent variable when the dependent variable is 0, which in this case is undefined since the company's revenue can never be negative.
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