survey methods and statistical modeling

One of the professors at the department where I work (Joop Hox) told me at our first meeting ever that good survey methodologists know their way around in the world of statistics. I think this saying should also go in the reverse order by the way, but I did take his advice seriously, and I am getting more and more interested in statistics, and specifically statistical modeling.
A good statistical model in my view should be able to answer a specific (complicated) research questions about our social world, in a relatively straightforward way. This implies answering the question of causality (see previous post) is very important in all statistical models, and second, that the statistical model should summarize our social reality in a simple way.

Proving causality can be hard and depends mainly on a good research design. Summarizing our social reality in a not too simplified way is hard, but graphics can do wonders. The video below is very old (well, 5 years), and most of you have perhaps seen it, but it is a good illustration of what I think good researchers should try to achieve (including the Swedish overenthusiastic accent).

Because of the advent of Internet and abundance of IT-application, the amount of data that we have available for marketing and research is booming. The great challenge for statisticians (and here come the survey methodologists into play)in the next years is how to handle all this data, make them insightful, and use them to answer questions we weren't able to asnwer before. A great blog post on this topic was posted last year on www.radar.oreilly.com. Highly advised.

update 11-08-2016: update of the link above: http://www.simplilearn.com/resources-to-learn-data-science-online-article