Frequency data, having no underlying metric, are frequently encountered in real-life situations. The analysis of such data is usually difficult as nominal data are inherently less informative than quantitative data and decisions are taken erroneously using such results.          The objective of the research was to study the significant effect of gender, faculties and interaction using categorical data in a two-way cross classification.           Materials and Methods. The study applied a cross sectional study with a total sample size of 434. Multistage sampling was adopted. Categorical analysis of variance (CATANOVA) technique was used for analysis. This is suitable as it uses a two-way ANOVA with quantal responses as equivalent of a three-way contingency table in which one of the classifications is treated as responses to the other two. The study considered frequency data involving response scores of students using a scale of good, fair and poor.          Results.  Numerical results revealed poor level of student’s knowledge and control practices of hepatitis B virus infection. And it is significantly (p>0.05) the same in the study Universities. Moreover, gender and faculties, as well as interaction have no significant (p>0.05) effect on student’s knowledge and control practices of hepatitis B virus infection.