Alexandra Brandriet (Miami University, USA)
Bivariate correlations, t-tests, and ANOVAs are parametric procedures used in many quantitative studies in chemistry education research (CER). Despite the popularity of and familiarity with these tests, they can easily be misused. Therefore, while these statistical tests can yield crucial information for analyses, it is important to design CER studies appropriately. This presentation will highlight the underlying assumptions that ground each of these tests, how to interpret statistical output, and the types of inferences that can be established. Contrasts will be drawn between appropriate uses and common mistakes that researchers might make with regards to study design, data collection, and reporting results.