General model fitting with zfit and hepstats

Statistical inference using likelihood based methods is a key step in most HEP analyses. This talk will introduced general likelihood fitting using zfit for model building and minimization as well as hepstats for interval estimations and targets a wide audience.
The talk will be based on notebooks and start from simple unbinned and binned fits using examples that incorporate other Python and Scikit-HEP libraries to showcase the usage in an analysis flow.
It continues to more elaborate topics covering simultaneous fits, multidimensional PDFs and custom PDFs and statistical methods such as limit setting.