The hotter it gets, the more ice cream sells: we all suspect as much. But by how much? If tomorrow the thermometer reads 27 degrees, how many ice creams should we get ready? And, moving onto our own ground: if we raise the campaign budget, how many extra conversions can we expect?
Concepts such as the mean or the standard deviation describe one variable at a time. Questions like these, instead, require us to look at two variables together: that is the job of correlation and simple linear regression, two of the most widely used (and most misunderstood) tools in data analysis.
Continue reading “Correlation and Simple Linear Regression: the Line, Pearson’s r and R²”