Statistics is the science and art of describing data and drawing inferences from them. In summarizing data for statistical purposes, our focus is usually on some characteristic that varies in a population. We refer to such characteristics as variables; height and weight are variables in a human population. Certain parameters are used to summarize such variables. There are measures of central location—principally the mean, median, and mode—that describe in various ways the center of the data; these are discussed in Section 1.2. There are measures of variability or dispersion—most notably the variance and standard deviation—that describe how widely data vary around their central value; these are described in Section 1.3. Finally, there are measures of correlation—particularly the Pearson product-moment correlation coefficient—that describe the extent to which pairs of characteristics (such as height and weight) are related in members of the population; this coefficient is described for measured data in Section 1.4. Methods for expressing association in binary data (i.e., data that can take only two values, such as 1 or 0) are described in Section 1.5.