THE BIVARIATE ANALYSIS BETWEEN THE VARIABLES THAT DEFINE THE INVESTIGATED TOURIST POPULATION IN THE CENTER DEVELOPMENT REGION AND THE OTHER IMPORTANT TOURIST VARIABLES

In the marketing research the instances when we need to examine the relationship between two variables are frequent. Knowing the relationship between the two variables involves the use of tests that can be parametric and nonparametric. This paper includes the non-parametric tests used in the bivariate analysis. The used tests are: chi square test, the Mann-Whitney test, the Kolmogorov-Smirnov test. Besides these tests, this paper also includes measuring the association between nominal variables using the C contingency coefficient and Cramer's V coefficient and between two metric variables, using the Pearson’s linear correlation coefficient.variables, Chi square test, U test, Kolmogorov-Smirnov test, Cramer's V contingency coefficient, Pearson's linear correlation coefficient,

UNEMPLOYMENT ISSUES IN BARAOLT REGION

Many methods of multivariate analysis are based on metric variables. In the case of questionnaire-based surveys qualitative data usually prevail, measured nominally or ordinal. This paper contains the discriminant analysis from data recorded from a sample of 100 respondents, with regard to: whether they have a job or not, number of family members and the importance of having a job according to the specialization graduated.variable, ANOVA, level of significance, the discriminant function, Wilks