The choice between the chi-square test and the point-biserial correlation depends on the nature of your data and the specific research question you're trying to address. These tests are used for different types of relationships and data scenarios:

In summary, if you're looking to assess the relationship between two categorical variables, the chi-square test is appropriate. If you're interested in understanding the strength and direction of the relationship between a continuous variable and a binary categorical variable, the point-biserial correlation is more suitable.

Remember that the choice of statistical test should align with your research question and the type of data you have. Additionally, it's always a good practice to consider the assumptions of the chosen test and to interpret the results in the context of your research hypothesis.

Neither is better or worse-- it all depends on which is most appropriate to answer the research question. Correlations look at the relationship between two variables, with point biserial used when 1 of those variables is continuous and the other is dichotomous (categorial, with only two options). Chi-square looks at the relationship/differences across two categorical variables without restricting the number of response options. Technically, correlation focuses on the shared pattern of change (connection in trends/similarities/relationship), while chi-square tries to determine the differences in the distributions.

Thank you so much Ma'Mon Abu Hammad for your inshightful answer.