The cyber landscape is inherently complex. Although cyber-attacks of varying magnitude are frequently observed every day, many cyber-related crimes still go underreported. The data collected from these observations may be insufficient, incomplete, or even overwhelming. Using statistical methods, more useful information may be inferred from this type of data. This chapter introduces fundamental topics on statistical methods that relate to cyber research. Statistical methods play several essential roles in cyber research. Statistical methods ensure data are correctly collected and summarized to answer a specific question of interest. Through descriptive statistics, raw observation data can be transformed into common knowledge. Reasoning with large data sets can be overwhelming. With inferential statistics, the characteristics of more massive data sets can be gained from smaller data samples. In order to cope with cyber-related threats, which are often unknown, the concept of resilience is adapted and applied to cyber research. Through these methods, research in cyber resilience benefits from research in statistical methods. The application of statistical methods to modeling, analyzing, interpreting, and presenting information from diverse channels of cyber research hopes to aid in overcoming new cyber threats.