2.4 Data analysis
We performed univariate and bivariate analyses of the acquired data. In univariate analysis, frequency tables, bar graphs, and pie charts were generated by SPSS, which reflects the distribution of observations based on several options for a variable. Bivariate analysis was performed to compare two variables using statistical tests depending on the nature of the data. The chi-square test was the statistical test of choice in the comparison of two categorical variables coupled with close inspection of the p value to the proposed 5% type 1 error to determine the significance of the variables compared. Several tests were conducted as part of the statistical inferences to determine the most reasonable direction of the suggested hypothesis at the start of the research. Moreover, descriptive statistics were calculated to emphasize the distribution, location, and spread of the data. The data were found to be skewed to the right because of outliers. Therefore, the median was reported as a measure of central tendency. Furthermore, the interquartile range was delineated to describe the variability of the data.
When calculating the most common depressive symptoms among our study participants, the frequencies of symptoms 1-4 were obtained by adding the “most” and “occasionally” responses, whereas the frequencies of symptoms 5-6 were calculated by adding the “rarely” and “sometimes” responses. It is important to note that the total for the occupation demographic was lower because only employed participants who chose to specify their occupation were counted, and the total for the openness about mental health was lower because it is an optional question since only those who had mental illness could choose to answer this question.