Everything's Significant When You Have Lots of Data
Dave Giles (noreply@blogger.com)
Well........, not really! It might seem that way on the face of it, but that's because you're probably using a totally inappropriate measure of what's (statistically) significant, and what's not. I talked a bit about this issue in a previous pos t , where I said: "Granger ( 1998 , 2003 ) has reminded us that if the sample size is sufficiently large, then it's virtually impossible not to reject almost any hypothesis. So, if the sample is very large and the p -values associated with the estimated