![]() However, we only calculate a regression line if one of the variables helps to explain or predict the other variable. This line can be calculated through a process called linear regression. If we think that the points show a linear relationship, we would like to draw a line on the scatter plot. The linear relationship is strong if the points are close to a straight line, except in the case of a horizontal line where there is no relationship. In this chapter, we are interested in scatter plots that show a linear pattern. The following scatterplot examples illustrate these concepts. When you look at a scatter plot, you want to notice the overall pattern and any deviations from the pattern. Consider a scatter plot where all the points fall on a horizontal line providing a "perfect fit." The horizontal line would in fact show no relationship. For a linear relationship there is an exception. You can determine the strength of the relationship by looking at the scatter plot and seeing how close the points are to a line, a power function, an exponential function, or to some other type of function. The independent variable or attribute is plotted on the X-axis, while the dependent variable is plotted on the Y-axis. It represents data points on a two-dimensional plane or on a Cartesian system. High values of one variable occurring with low values of the other variable. Scatter plots are the graphs that present the relationship between two variables in a data-set. ![]()
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