- I built a simple linear regression model to understand if Universal Healthcare Index predicts suicides.
- My independent variable is Universal Healthcare Index (scale from 1 to 100). The variable name in my data is called "Trans_uhc". In order to meet the normality assumption, I used a sqrt(max(x) - x)) transformation to normalize a negative skew.
- My dependent variable is suicides per 100k population. In order to meet the normality assumption, I used the sqrt(y) transformation to normalize a positive skew.
Simple Linear Regression Output
As you can see from the above output, my predictor variable is significant. However, how would I interpret this outcome? For example, if the data was not transformed, I would be able to interpret the linear relationship as "when Universal Healthcare Index increases by 1 point, suicides/100k people decrease by .18879." However, I cannot do that because of the transformation.
Any help would be greatly appreciated. Thank you!