ii. Correlation vs Causation:

• Just because 2 variables are highly correlated or exhibit a strong linear relationship, does not mean that there is a causal relationship between the explanatory variable and the response variable.

example: Annual snowfall in Amherst, MA vs US unemployment rate 1973 to 1982

Simple linear regression results: unemployment (%) = 0.37645632 + 0.09544667 snowfall (in) Sample size: 10 R (correlation coefficient) = 0.9835 R-sq = 0.9673073