When data sets have a positive or negative correlation, the trend of the data can be modeled using a line of fit, also called a trend line. This line is drawn on a scatter plot near most of the data points, which appear evenly distributed above and below the line.

The scatter plot above shows the mean weights of kittens from the same litter in relation to their age. In this case, a line of fit could be drawn quite seamlessly. When drawing such a line of fit, the following characteristics should be considered.

• The data needs to have either a positive or negative correlation.
• While a line of fit is not unique and does not create an exact distribution, ideally, about half of the points should be above the line and about half below the line.
• An equation of the line can be found using two of its points. These points do not necessarily belong to the bivariate data set.

Ultimately, a line of fit can be used to make predictions and generalize the trends of data sets. Additionally, when a line of fit is determined using strict mathematical methods, it is commonly referred to as a line of best fit.