# Overview

• 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 # Help Needed

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!

• What is the max of x? The actual number, I mean. – BigBendRegion Jan 13 at 11:22
• @BigBendRegion max(x) = max(Universal Healthcare Index) = 88 – maudib528 Jan 13 at 13:54
• stats.stackexchange.com/search?q=interpret+regression+root – whuber Jan 13 at 14:42
• The questions suggested do not provide an answer for this case – David Jan 13 at 15:02
• @David Agreed. Thanks! – maudib528 Jan 13 at 15:04