Electroencephalography (EEG) is used to measure weak electrical potentials generated on the scalp by the brain’s activity. However, EEG recordings have several sources of measurement variability due to interindividual differences and the specifics of measurement. Therefore, the application of statistical inference has a crucial role in EEG data analysis to detect experimental effects. In this chapter, we provide an introductory overview of the role of statistical inference in an EEG study. We discuss the sources of uncertainty in EEG measurements and how EEG analyses are organized to reduce measurement-related error. Finally, we highlight the importance of reducing measurement error, both during acquisition and analysis, and the value of well-defined hypotheses specific to the EEG experiment.