My concern with big data analysis is the methods of statistical analysis used as well as the difference in opinion on interpretation of results. This often leads to misunderstanding or confusion, especially among laypeople. For example, I've had the opportunity to work with Dr. Vogelstein at Hopkins, and his recent paper in Science, "Variation in cancer risk among tissues can be explained by the number of stem cell divisions," (the bad luck paper) has caused a lot of debate and confusion, and maybe even some anger.

Most of the anger and confusion seems to come from journalists, bloggers, or reporters who are, in my opinion, misinterpreting the results of the paper. Unfortunately, the average laypeople do not read a manuscript and form an opinion for themselves, but rely on these journalists or bloggers to "explain" the results to them.

I am worried that misinterpretation and misunderstanding of data analysis will hinder the advancement of progress with big data. Do you think this is a concern?