respond to this....A linear regression is the statistical model which is used to predict, estimate, and study the linear relationship between a dependent or explanatory variable (on the x-axis) and the independent variable (on the y-axis). We use the independent variable to predict the value of the dependent variable. You can have a linear regression with just one explanatory variable, known as a simple linear regression (SLR), or multiple explanatory variables in a multiple linear regression (MLR). This all ties together to help us predict future outcomes and evaluate them. This data could help with a business's operations, research and development, or a vast variety of other things. With my current employer there are a number of metrics and stats that could benefit from the use of a linear regression. I have seen examples from our sales force and production planners that used linear regressions, off the top of my head I don't recall what the exact variables that they used were. I also recall a time with previous employer where a linear regression was used to look at the weight of truck (with raw product to be unloaded) vs. the unload time of that truck. This gave us an estimate of what unload times would look like for trucks of varying weights