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Jack Williamsen Office of Institutional Effectiveness St. Norbert College De Pere, Wisconsin Using the Humble Crosstab to Partner with Parametrics Slide 2 Sidebar: Some info about St. Norbert & the sample used in this presentation St. Norbert College (SNC) is a Catholic Liberal Arts College near Green Bay, WI with an undergraduate population of ~ 2000 students. The two largest undergraduate majors are Business Administration and Education. Data in this presentation come from a larger study of the role of gender in the educational experiences of SNC men and women conducted by the Office of Institutional Effectiveness. Slide 3 Do parametrics need a partner? Parametric statistics (e.g., means, Pearson r) are central to many quantitative analyses of information. They convey useful information in a compact package. But Terminating a quantitative analysis after computing summary statistics is like setting a book aside after reading the dust jacket You know something, but there is more to learn useful knowledge that could deepen understanding or lead to more precise real-world action. Slide 4 Crosstabs to the Rescue Crosstabs provide a convenient, useful method to explore the continuous distribution(s) of variables summarized by means and correlations. Although parametric tools (such as the SD) offer insight into distributions. Crosstabs convey information in tables that are understandable by non-statisticians. And they lend themselves to transformation into graphic visuals for the numerically-challenged. Slide 5 This presentation uses three examples: Example 1: The correlation between HSGPA & 1 st semester freshman GPA (= 0.62) is dissected using a dual quintile (HSGPA quintiles by 1 st sem. Fr. GPA quintiles) table. Example 2: Robust mean GPA differences (~0.30) between men and women students are analyzed using SPSS EXPLOREs seven percentile categories. Example 3: Unusually high retention of business majors (vs. all other majors) is explored across the GPA spectrum using quintiles. Slide 6 Example 1: How to dissect a Correlation The correlation (0.62) between HSGPA and 1 st sem Fr. GPA is both typical and an indicator of a less-than-perfect ordering of case-by-case GPA pairs. We can literally see the nature of this imperfection by: (1) identifying quintile break points for HSGPA and for Fr. GPA. (See Appendix for methods.) Then (2) use Transform > Recode [GPA] into another variable [quintile] to create two categorical GPAs Finally (3), cross-tab the two quintiled GPAs in SPSS, using Row Percent to fill in the resulting table. Slide 7 Example 1: Notes Although quintiles are used in this example, any slice & dice set of categories can be used. The table in the next slide is data-dense. Readers may need some initial guidance (e.g., Read table from rows, left to right) and/or an illustration: The table shows, for example, that 54% of freshmen with HSGPA < = 2.84 have 1 st semester GPAs Appendix: SPSS methods for creating categories from continuous variables (Analyze > Frequencies > Statistics > Percentile Values) offers a number of user-selected options for generating categories, including percentiles. (Transform > Visual Binning) is also versatile, and provides a visual representation of the distribution of the variable of interest. Make cuts any way you wish. (Analyze > Descriptive Statistics >Explore > Statistics > Percentiles) provides a fixed set of percentile breaks. See Example 2 for an illustration.