The purpose of this talk is to introduce basic statistical issues arising when collecting and analyzing functional magnetic resonance imaging (fMRI) data. After simplistic explanation of what fMRI data represent, a simple fMRI experiment is described and essential quantification problem is introduced. The General Linear Model (GLM), hypothesis testing and p-values are discussed with respect to functional MRI data framework. Discussion about characteristics of parameters estimates, contrasts and Type I and Type II errors concludes the talk.