Introduction to Categorical Data Analysis
Name
Institution
Categorical variables present emphasis on the existing association between aspects that are being assessed in the study (Klingenberg, 2016). Chi-square analysis is the most preferred statistical test when assessing the existing association between variables. The dataset that will be considered in this case is the Afrobarometer dataset. The variables that have been identified include region and satisfaction with democracy.
Research question
Is there a statistically significant association between region and satisfaction with democracy?
Null hypothesis
Ho: There is no statistically significant association between region and satisfaction with democracy.
Research design
A cross-sectional research design would be essential in helping understand the relationship between the variables. Region and level of satisfaction with democracy can be obtained at one point when interacting with the participant; hence this design will be appropriate in finding quality data that can help answer the research question (Frankfort-Nachmias & Leon-Guerrero, 2018).
Dependent variable
The dependent variable is satisfaction with democracy. Satisfaction with democracy is a categorical variable that is measured on an ordinal scale.
Independent variable
The independent variable is country by region. The region is categorical that is measured on a nominal scale.
Analysis
Chi-Square Tests | |||
Value | df | Asymptotic Significance (2-sided) | |
Pearson Chi-Square | 1072.780a | 12 | .000 |
Likelihood Ratio | 1158.493 | 12 | .000 |
Linear-by-Linear Association | 59.300 | 1 | .000 |
N of Valid Cases | 48946 | ||
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 107.77. |
A chi-square test for association was conducted to determine whether there was a significant association between region and satisfaction with democracy. The findings showed that at 95%, there was x2(12) = 1072.78, p<0.001. Thus we reject the null hypothesis and conclude that there was a statistically significant association between region and satisfaction with democracy.
The effect size in this is (x2/n)1/2
= 1072/48946
= 0.148
The effect size is 0.148
Explaining the findings to lay audience
The findings from the analysis have shown that satisfaction with democracy is related across the different regions that were being assessed. Individuals from different regions tend to have similar outcomes regarding their perception of satisfaction with democracy.
References
Klingenberg, B. (2016). The Chi-squared test. Retrieved from https://istats.shinyapps.io/ChiSquaredTest/
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: Sage Publications.
Visvalingam, M. (2020). Chi-square as an alternative to ratios for statistical mapping and analysis.
Barceló, J. A. (2018). Chi‐Square Analysis. The Encyclopedia of Archaeological Sciences, 1-5.