Chi-Square Test of Independence

Chi-Square Test of Independence

The Chi-Square test of independence is used to see whether two nominal (categorical) variables

have a significant relationship (Quessy, Rivest & Toupin, 2019). The researcher wants to look

into the relationship between Country by region and Infrastructure by index. This relationship

can be investigated using the chi-square test of freedom. From the Afrobarometer data set, the

research question for the study is; is country by region related to infrastructure by index? The

study hypothesis was; H1 : There is a relationship between Country by region and Infrastructure

by index. Ho : There is no relationship between Country by region and Infrastructure by index.

Descriptive design was adopted for this study.

Likelihood Ratio 415.699 45 .000

Linear-by-Linear Association .642 1 .423

N of Valid Cases 8392

a. 0 cells (0.0%) have expected count less than 5. The minimum

expected count is 8.12.

The Chi-Square test results shows that there is a strong relationship between Country by region

and Infrastructure by index. This is supported by a P-value that is below .05. Therefore, we reject

the null hypothesis that there is no relationship between Country by region and Infrastructure by

index.

Phi values are below 1 thus showing a perfect association (Frankfort-Nachmias, & Leon-

Guerrero, 2018).

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th

Quessy J-F, Rivest L-P, Toupin M-H. (2019). Goodness-of-fit tests for the family of multivariate

Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social