What is a best fit line? How is a best fit line useful? A. It is a line that connects the leftmost and rightmost data points on a scatterplot. C. It is a line that connects the bottommost and topmost data points on a scatterplot. How is a best fit line useful? A. It is useful to make predictions within the bounds of the data points. B. It is useful to identify causation among variables. C. It is useful to make predictions about a population that is different from we drawn between any two data points on a scatterplot. D. It is useful to make predictions beyond the bounds of the data points. Domple data were drawn.

The concept of the best fit line, also known as the regression line, originated with the method of least squares, developed by mathematicians like Carl Friedrich Gauss and Adrien-Marie Legendre in the 19th century. This method simplifies complex data relationships into a straight line that minimizes the distance between the line and all data points. Pretty cool, right? It’s like finding the average groove for your favorite tracks! As for its usefulness, the best fit line is a super handy tool in various fields, especially in statistics and data analysis. It helps us make informed predictions based on trends observed in the data. For instance, businesses can use it to forecast sales trends, healthcare professionals might predict patient outcomes, and scientists often rely on it to discover relationships between different variables. Essentially, it's like having a crystal ball, but based on good ole data!