When to Categorize Continuous Predictor in a Regression Model?

Research fields usually follow the practice of categorizing continuous predictor variables, and they are the same who mostly use ANOVA. They often do it through median splits, the high value above the median and the low values below the median. The way out of this dilemma is to be able to conclude whether to treat an independent variable as categorical or continuous. Data analysts are empowered to find real results which otherwise they might miss, is by knowing when it is appropriate, followed with the understanding of how it will affect the interpretation of parameters. Let's understand and accept the fact that general linear model is not concerned if the predictor you used is continuous or categorical. But you as a data analyst should choose the information you need from the analysis based on the coding of the predictor.