The article by Muller, A. (2002) used multiple regressions to determine the relationship education, income inequality, and mortality. A multiple linear regression is used to show the relationship between one dependent variable and several independent variables (Matthews, 2014) . The research question of the study was whether the association between income inequality and mortality in the U.S was due to different levels in formal education. The depended variable was age-adjusted mortality and the independent variables were Gini coefficient, per capita income and proportion of people above the age of eighteen years who did not have a high school diploma. The use of multiple linear regressions in the study was appropriate due to the ability to answer the research question by giving the relationship between the variables.
The display of the data was good the data did not require an explanation. For any person familiar with multiple regressions the data was self-explanatory. The graphs that were displayed were clear. The line estimated by the regression was clearly drawn. Also, the points that did not fall in the regression line were also shown. The R-squared for the regression and the regression equation were also displayed clearly. Overall the data was displayed were and did not require a lot of explanation.
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The results indicated that there was a positive association between income inequalities and age-adjusted mortality. They were supported by the results of the regression. The regression models were also statistically significant at p is less than 0.001. The results of the study stood alone because it was supported by the statistics. The use of the multiple linear regressions in the study was important. It is because it made possible to determine the relationship between more than one independent variable to the dependent variable (Olive, 2017) . The second benefit of using multiple linear regressions in the study was the ability to know abnormities. For instance, in the study by Muller, (2002) abnormalities were observed in the District of Columbia.
References
Matthews, D. E. (2014). Multiple linear regression. Wiley StatsRef: Statistics Reference Online .
Muller, A. (2002). Education, Income Inequality, And Mortality: A Multiple Regression Analysis. BMJ: British Medical Journal,324 (7328), 23-25.
Olive, D. J. (2017). Multiple Linear Regression. In Linear Regression (pp. 17-83). Springer, Cham.
