Software engineering (SE) research currently witnesses a shift in data analysis practices. The flaws of simple, frequentist tools like t-tests threaten the validity of conclusions drawn from quantitative data, especially in observational studies. To address these flaws, SE researchers adopt methods for statistical causal inference (SCI) which are successfully applied in scientific disciplines like medical research, sociology, and econometrics. However, these methods exhibit a steep learning curve which hinders their adoption both in SE and requirements engineering (RE) research. This tutorial aims to gently introduce SCI to RE researchers in order to keep up with methodological advances of the SE field. The tutorial introduces the fundamentals of SCI with applications and examples particular to RE. Participating in the tutorial will equip RE researchers to keep up with the advanced data analysis practices observed in SE research.