This chapter provides an overview of the processes that are commonly used for analyzing data. Our intention is to explain what these processes achieve and why they are done. Analyzing data goes through four stages. For each stage, we explain the most important concept and then explain the practical steps that are involved. This begins with the data themselves as variables. Next, we move on to describing the data, their variance and covariance, with linear models. Next, we cover interpreting effects and focus on effect sizes. We end with a discussion of inferences about the population and how the presence of uncertainty has to be taken into account in reaching conclusions.