This chapter on biostatistics introduces foundational concepts crucial for interpreting data in the biological sciences. Originating from the Latin word “statista,” statistics encompasses not only the collection but also the analysis and interpretation of data, serving as a scientific toolbox for discerning patterns within diverse fields. Biostatistics, a specialized branch, focuses on analyzing data related to various organisms, providing quantitative insights that support decision-making in research. The chapter emphasizes the importance of understanding populations and samples. A population refers to the entirety of individuals or data points relevant to a study, while a sample is a representative subset of that population, chosen for practical reasons, such as time and cost constraints. Thus, sampling is a critical process that ensures the selected subset accurately reflects the characteristics of the larger group. Through descriptive and inferential biostatistics, researchers can estimate central tendencies and variability, and make predictions based on sample data. The chapter outlines essential steps in statistical analysis, including study design, hypothesis generation, data collection, and the application of techniques. It also highlights various sampling methods, with random sampling often regarded as the ideal choice for its fairness in representation. Overall, this chapter aims to equip students with the analytical tools necessary for conducting chromosome analysis and encourages further exploration of biostatistical methodologies applicable in broader biological research settings.