Correlation and Bivariate Regression

Correlation and regression are measures of linear association between two or more variables. They are parametric techniques that assess if the behavior of one variable (dependent variable) is influenced by a predictor variable. However, correlation is limited when it comes to identifying the causal effect of the predictor variable on the dependent one (Frankfort-Nachmias & Leon-Guerrero, 2018). One of the studies that can be conducted from the Afrobareometer data set is investigating the relationship between the Trust in Government Index and the Problems within the Public Health Clinics. For instance, people develop good trust with the sitting government based on its performance especially on public social projects that benefit the public. Such an aspect tells that the problems that face the public health care clinics would influence the trust of people towards their government. Therefore, the Trust in Government Index is the dependent variable while the problems within the public health care is the independent variable.

There was a weak negative correlation between the problems in the public health care clinics and the Trust in Government Index, R = -0.189, p < 0.05. This tells that as the problems within the public health care clinics increase, the Trust in Government Index decrease. This shows an inverse relationship between the two variables (D'Agostino, 2017). However, correlation has a weakness in that it does not satisfactory tell if the changes in the trust in government index is exclusively caused by changes in the problems within the health care facilities. With this in mind, the regression technique is suitable to identify if the variables are significantly related, linearly (Wagner 2016). .

Table 1

Bivariate Correlation 

On the other hand, the problems in the public health care clinics are a good predictor of the Trust in Government Index, F(1, 30552) = 1,132.693, p = 0.000. Typically, the problems within the public health care explains about 3.6% variation in the Trust in Government Index (Shevlin & Shevlin 2001).

Table 2

Regression Model Summary 

Table 3

ANOVA Findings 

The above results are meaningful in that they can be used in deploying social and health projects to boost the perceptions of the Africans regarding their trust with the current leadership. Tentatively, improving the health care facilities in terms of efficiency of their services would make the people have improved trust in the government.

References

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

Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Publications.

Miles, J., & Shevlin, M. (2001). Applying regression and correlation: A guide for students and researchers . Sage.

D'Agostino, R. (2017). Goodness-of-fit-techniques . Routledge.