Oscillatory brain activity reflects the dynamic coordination of neural processes. Understanding these oscillations requires methods beyond the time domain to reveal their frequency-domain information. This chapter introduces spectral analysis as the foundation for studying EEG oscillations. Beginning with the mathematical description of oscillatory processes, we build intuition around the core concepts of amplitude, frequency, and phase. We then show how the dot product provides the mathematical, geometric, and intuitive basis for Fourier analysis. The discrete Fourier transform (DFT) is presented as a practical tool for decomposing EEG time series into the frequency domain, enabling precise characterization of oscillatory activity. Finally, we discuss the limitations of Fourier analysis and outline ways to address them. Rather than thoroughly presenting advanced methods in frequency analysis, this chapter aims to equip readers with the conceptual and analytical framework needed to begin studying EEG time series from a frequency-domain perspective.