Linear regression is basically a way to figure out the relationship between two (or more) things so you can make predictions. In simple terms, you're looking at how one variable (the dependent variable) changes when another variable (the independent variable) does. The dependent variable is what you're trying to measure or predict, and the independent variable is what you think influences it. You'd use linear regression when you want to see trends, patterns, or make decisions based on past data. For example, in my mobile bartending business, I could use linear regression to look at how the number of guests at an event (independent variable) impacts the amount of alcohol needed (dependent variable). By analyzing past events, I might notice that as guest count goes up, liquor consumption increases at a steady rate. Knowing this helps me budget more accurately, suggest realistic liquor quantities to clients, and cut down on waste. It's a practical way to use data to plan smarter and keep clients happy