We used our first lecture to look at case studies in four main areas: exploratory data analysis, classification, regression, and working with network data.

We discussed a few examples, including using aggregate search activity to predict consumer behavior, exploring browsing logs to understand how Internet usage varies across demographic groups, and analyzing the structure of information cascades to understand how content spreads online.

During this discussion, we touched on how easy it is to find spurious correlations, cheat at prediction, and be fooled by randomness.