Discriminants of the Low-and-High Statistics Anxiety Among College Students

Abstract

Discriminant function analysis was used to determine important non-cognitive factors that differentiated between low-and-high anxiety students in statistics. The participants were 246 college students enrolled ion introductory statistics courses at a state university in Texas. Students responded to two scales: the Statistical Anxiety Rating Scale and Attitudes Toward Statistics. They also indicated their previous mathematics experiences, perceived statistical abilities, and satisfaction with their current statistics course. Findings showed that the discriminant model accounted for 63% of the between-group variance and discriminated with 88% overall accuracy. Perceived statistical ability was the most influential variable that separated the groups.