which outlier detection technique? I'm new to data science. I have a question on anomaly detection techniques.

There are several anomaly detection techniques such as statistical, density based, depth based, clustering, etc..

Given a dataset, what are the criteria or how should I choose which one of the techniques above (not the algorithms inside the techniques). In general why choose a particular technique.
You first need to specify if you are going to work on anomaly detection or novelty detection.

The difference between them is that in anomaly detection, your data contains anomalies, but in novelty detection, your data contains only valid data.

After that you need to choose the algorithms depending on what you have chosen before, there are some algorithms that work only with one type, and there are algorithms that work with both types.