Correlation vs Regression: Both correlation and regression are two powerful tools of statistics and data analysis used to understand the relationships between variables.

Multiple regression equations designed to explain or predict should be validated. This tutorial shows how recalculation of the coefficient of determination on hold-out sample data or new sample data ...

Regression imputation is commonly used to compensate for item nonresponse when auxiliary data are available. It is common practice to compute survey estimators by treating imputed values as observed ...

Correlation is a statistical measure of how two securities move in relation to each other. Investors use correlation to diversify their portfolios and hedge against risk.

Negative coefficients indicate opposite direction of movement in most cases. The other key result is the correlation of the two. Regression statistics will typically include an R-squared value.

While reviewing research output in social sciences, common errors are apparent in hypothesis formulation, choice of model/s, and interpretation despite using quality data from primary survey or ...

In my opinion, reversion to the mean is one of the most powerful, but least understood, concepts in statistics. Regression to the mean explains that in many cases data will tend to even out—i.e ...