Among the many difficulties beleaguering the communication research methods instructor is the problem of contextualizing abstract ideas. Comprehension of variable operationalization, the utility of the measures of central tendency, measures of dispersion, and the visual distribution of data sets are difficult, since students have not handled data. Students are also intimidated by statistical concepts, and erect barriers to their own methodological understanding (Denham, 1997). As a result, the process of conceptualizing a data set is frequently experienced as a cryptic and arcane procedure. Educators should provide examples that go beyond demonstrations of relevance and invite students to interact with course content (Kramer & Pier, 1999; Sowey, 2001). Wulff and Wulff (2004) report interactive examples are essential to achieving student learning outcomes. Inviting students to apply concepts is essential for establishing personal relevance of statistical concepts (Maier & Curtin, 2005). Making methodology and the process of "doing methods" concrete is important since concepts are abstract and applications are not necessarily apparent. This article makes several unique contributions to communication literature. First, compounding the difficulties associated with teaching research methods is the relative dearth of published materials related to the subject. When searching through 10 recent issues of "Communication Teacher," eight activities are suggested for research methods. Of these, three (see Morrow, Kelly, & Skolits, 2013; Nelson & Fife, 2013; Rockwell, 2012) provide suggestions suitable for teaching quantitative methods. Previous publications focus on communicating abstract methodological concepts (see Andrews, 2013; Griffin & Cohen, 2012; Kelly & Davis, 2011; Tolman, 2013; Zaslow, 2012) rather than experiential activities and data collection. The activity outlined in this article combines discussion of statistical concepts with application to real scenarios. After completion, students should understand several foundational research concepts. Ultimately, students will tangibly experience variable operationalization and learn how simple calculations (mean, median, mode, range, and standard deviation) provide meaningful information to researchers.