Final answer:
To determine the best fit equation for a scatter plot, one must identify if a linear pattern exists in the data. If so, linear regression and the computation of a least squares line of best fit can be assessed using the r squared value to gauge fit accuracy.
Step-by-step explanation:
To determine which equation from the options provided best fits the data on a scatter plot, you should look for the pattern that the data points suggest. First, describe the pattern in the scatter plot to see if the data suggests a linear relationship. If the scatter plot displays a linear pattern, then the X and Y variables would be good candidates for linear regression.
To fit a linear equation to the data, one could use techniques like the method of least squares to calculate the line of best fit, also known as the regression line. This line minimizes the distances of the data points from the line, thereby showing the trend that the data points follow.
An important measure to consider when assessing the fit of the line is the r squared (r²) value, which indicates the proportion of variance in the dependent variable that's predictable from the independent variable. A higher r² value suggests a better fit.