I gathered a small data set of the amount of liquor consumption (wine and liquor) and the death rate due to Cirrhosis. I analyzed the correlation between the variables and did a multiple regression to find the predictability of the Cirrhosis death rate. I tried several different combinations of variables to find the regression with the most accuracy and significance. the best output i got was with Cirrhosis death rate as the dependent variable, and wine consumption, liquor consumption, and population as the independent variables. It produced an R square of .78 and an F statistic of 50.84, with all P-values close to zero. Something that i did not expect was that wine consumption had a stronger correlation (in the correlation output and scatter plot) and more significant t-stat to Cirrhosis death rate than liquor consumption did. My y-intercept formula produced was y = 10.6829 + .3489×1 + 2.0171×2 + .1765×3.