STATISTICAL ANALYSIS OF THE INTERACTION BETWEEN GENDER ATTITUDE AND PERCEPTION OF HAPPINESS: AN APPLICATION ON UNIVERSITY STUDENTS

Gender attitude is the concept defines the roles and behaviors that society and cultural structure expect from women and men throughout their lives. Gender equality emphasizes that women and men should have equal rights and opportunities and should not be gender-dependent. On the other hand, gender inequality can be defined as inequality in accessing resources and opportunities by sex. The effects of gender inequality can be observed in couples' relationships and social events in daily life. It is not possible to deny the role of gender inequality on people’s and society’s happiness level since it is one of the most important dynamics of social life. In this study, the relationship between gender attitudes and happiness perceptions of individuals were analyzed by using micro data. Within the scope of the study “Attitude Scale Regarding Gender Roles”, which is validated and reliable in the literature, was applied to a randomly selected sample. The sample was designed using both multistage sampling and stratified sampling techniques together. Stratification was planned on the basis of faculties. The prepared questionnaire was applied to a random sample of 3403 university students. The data collected were analyzed by homogeneity analysis and two-step cluster analysis, which are some of the Optimal Scaled Multivariate Analysis techniques. According to the results, it was observed that individuals whose gender attitude is relatively egalitarian are moderately happy and also, are the happiest with themselves. In addition, it is remarkable that the categories of success and love are closely located. Individuals with relatively more traditional attitude describe themselves as very happy. Additively it was determined that their source of happiness is their families, while the concept that makes them most happy is “health”. The findings are corroborated with the two-step cluster analysis results.