As the recent articles on the predictions of the elections seem to bring to the forefront, the requisite knowledge of stats in our pundit class seem to be beyond abysmal. The fact that they can ignore the results from experienced professionals either betrays their ignorance or implies an underlying agenda. I would like to hope, in the spirit of informing their audience, that it is the former, but I suspect it is the latter.
As this example points out, a basic understanding of Statistics (or Stats as I prefer) is a necessity in today's society. What I am talking about is everything from the basic understanding of the differences between measures of central tendency (mean, median, mode) and various measures of divergence (standard deviation, variance, range, inter-quartile range) to sophisticated predictive algorithms and clustering and why this knowledge is important.
One of my objectives with this blog is to try to simplify and clarify some of the basic concepts of stats and try to bring some of the more advanced issues down to the level of the lay person. Now, I am not purporting to simplify this to the extent the reader will be able to perform the more complex analyses required to generate competent predictions of elections or the weather or the stock market; but, maybe help to understand how these come about, be more confident in the results, and know how and what to challenge when you see some statistical result quoted in the media or by the government or corporation public affairs.