In the context of statistical modeling, a model is a set of distributions. It is said to be parametric when it is completely determined by a finite set of parameters. For example in the case of a linear model In this case the regression line that fits the data is completely determined by its parameters and a noise term. We say that the vector space of the model parameters is finite-dimensional. On the.. Read More

## What is the difference between correlation and regression ?

We are assuming here that the “regression” in the question is of a linear form. Correlation is the measure of how strong a linear relationship between two variables is. There are several correlation coefficient standards (Pearson, Spearman, etc). The correlation coefficient ranges between -1.0 and 1.0. Zero correlation means there is no linear relationship between the variables. The greater the correlation coefficient, the stronger the relationship, meaning that when one variable goes up,.. Read More