By Jeff Leek, Johns Hopkins University.

In my previous post I pointed out a major problem with big data is that applied statistics have been left out. But many cool ideas in applied statistics are really relevant for big data analysis. So I thought I'd try to answer the second question in my previous post: "When thinking about the big data era, what are some statistical ideas we've already figured out?" Because the internet loves top 10 lists I came up with 10, but there are more if people find this interesting. Obviously mileage may vary with these recommendations, but I think they are generally not a bad idea.

Original: simplystatistics.org/2014/05/22/10-things-statistics-taught-us-about-big-data-analysis/ Jeff Leek , is a professor at Johns Hopkins, where he does statistical research, writes data analysis software, curates and creates data sets, writes a blog about statistics, and work with amazing students who go do awesome things.