1. Spurious Regressions
The problem with nonstationary or trended data is that (OLS) regression procedures can easily lead to incorrect conclusions In these cases that the regression results have very high value of R2 (sometimes even higher than 0.95) and very high values of t-ratios (sometimes even higher than 4), while the variables used in the analysis have no real interrelationships.
(2007Asteriou)

2. Example1(Spuriouse Regression)
Yt = – 0.50Xt Se
t-statistic
Prob
R-Squared
Durbin Watson
F-statistic
Prob(F-statistic)