A live demonstration of how a typical set of educational data can be examined using quantitative statistical software was conducted. The topic of tutorial support was chosen. Setting up a hypothetical research scenario, the researcher created 300 cases from random data generation adjusted to correct obvious error. Each case represented a student who was required to take a literacy test; depending test results, the student was recommended to access a quantity of tutorial support hours. Use of tutorial hours was recorded. At the end of the semester, each took a communications test. Eleven variables were identified. The quantitative statistical analysis software used was SPSS (Statistical Package for the Social Sciences) Version 10. To get a sense of the literacy test marks and factors that impacted on marks achieved, the researcher ran "Explore" to get a table to show the shape of the distribution of marks by faculty and got a histogram and boxplot. An independent samples t-test was run to obtain a probability statement about the difference in means between genders. A one-way ANOVA (analysis of variance) showed the significance of means among faculties. SPSS calculated the Pearson Correlation on variables to produce tables that quantify the strength of the relationship between variables. The SPSS-prepared Matrix Scatterplot was used in regression analysis to predict a variable from one or more predictor variables. (YLB)