What are statistics and why do we need them? This chapter introduces descriptive statistics and then creates a bridge from describing data concisely to answering questions using hypothesis testing and inferential statistics. The chapter leads the reader to an understanding of how descriptive statistics summarize and communicate meaning, based on data, and how they underpin inferential statistics. Research study examples, figures, and tables throughout the chapter explain the topics addressed by applying the ideas discussed. The chapter begins with the basics of descriptive statistics – normal distributions, options for displaying frequencies, measures of central tendency and variability, and correlations. The transition to inferential statistics covers standardization and the z-score, sampling, confidence intervals, and basics of hypothesis testing including Type I and II errors. We then introduce inferential statistics using three methods – t-tests, one-way analysis of variance (ANOVA), and chi-square tests.