This chapter provides an in-depth exploration of three key characteristics of a data distribution: skewness, kurtosis, and modality. It begins by highlighting the importance of understanding a distribution’s symmetry, number of peaks, and tail behaviour as alternative ways to gain insights into complex phenomena when the exact distribution is unknown. The concept of skewness is introduced to measure the asymmetry of a distribution, with examples illustrating how data can be skewed positively or negatively. The chapter then delves into kurtosis, which focuses on the behaviour of the tails of a distribution, offering insights into the probability of extreme values. Finally, the concept of modality is explored, categorising distributions based on the number of peaks they exhibit, such as unimodal, bimodal, and multimodal.