Scatter plots are very often encountered, as they are the most common plot to visualize the relation between two variables. If we want to have a quick look at the data of these two variables and see if there is any relation between them (that is, correlation), we will draw a quick scatter plot. For a scatter plot to exist, we must have one variable that can be systematically changed by, for example, experimenter, so we can inspect the possibilities of influencing another variable.
That's why, in this recipe, we will learn how to understand the scatter plots.
We want to see, for example, how two events are affected by each other or if they are affected at all. This visualization is especially useful on large sets of data, where we cannot make any conclusions by looking at the data in the native form, when it is just numbers.
Correlation between values, if there is any, can be positive and negative. Positive correlation is for increasing X values...
