Categorical Data: Definition, Types & Analysis

In this assignment, the Afrobarometer dataset has been used and the research question is: “Is there a relationship between trust in the police and presence of democracy (measured with dichotomous variable) that exist in Africa?”

The null hypothesis to be tested from the research question is: “There is no statistically significant relationship between trust in the police and presence of democracy (measured with dichotomous variable) that exist in Africa.”

Basically, a correlational design which is also known as ‘ex-post facto’ or ‘after the facts’ design is an ideal research design that would align with the stated research question above. The main purposes of this design include but not limited to describing the existing relationships between variables, and to determine the relationship between the independent and dependent variables. For to note, when a correlation exists, a change in one variable corresponds to a change in others. Additionally, in this design, there is no manipulation of the independent variable because the event of interest, or the dependent variable, has already occurred. It may confirm the existence of a correlation, but generally insufficient to indicate that a causal relationship exists.

The quantitative data were analyzed using both descriptive and inferential statistics. The descriptive statistics were used to describe and summarize the data in form of tables, frequencies, and percentages. The inferential statistics were used to help make inferences and draw conclusions. Statistical tests including bivariate categorical tests (Chi-Square test) were used to test the hypotheses. The bivariate table was designed to organize the significant relationship between two variables (provided below) (Frankfort-Nachmias & Leon-Guerrero, 2018).

The dependent variable that was used was “DEMOCRACY (DICHOTOMOUS)” at a nominal measure. The independent variable that was used was “TRUST POLICE” at a nominal measure.

From the cross-tabulation analysis, it is evidenced that the percentages significantly vary between the two variables, but the relationship is not identified. The Chi-Square test indicates a value of 1242.165 with an associated p (true) value of .001. Because the test is significant and below the .05 threshold, there is a need to reject the null hypothesis that there is no relationship. In other words, there is some relationship between trust in the police and the presence of democracy in Africa. Additionally, the strength of the relationship as the value of 0 indicates no relationship and a value of 1.0 indicates a perfect relationship is determined by the Cramer’s V correlation. In this scenario, the symmetric measure of Cramer’s V has a value of .162 indicating that the relationship between the two variables is weak despite being significant at the .001. From the results, the significance/strength of the effect, as well as the answer to the research question, the presence of democracy does impact the trust in the police in Africa.

References 

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: Sage Publications. 

Appendix