Nate Silver’s unprecedented accurate prediction of state-by-state election results in the most recent presidential race was a watershed moment for the public awareness of statistics. While data gathering and analysis has become a massive industry in the past decade, it hasn’t always been as well covered in the press or publicly accessible as it is now. With more and more of our daily interactions being mediated through computers and the internet, it is easier than ever to gather detailed quantitative data and do statistical analysis on that data derive valuable information and predictions from it.

Knowledge of statistics and quantitative analysis techniques is more valuable than ever. From biostatisticians to politicians and economists, people in every field are using statistics to further their careers and knowledge. These sites are some of the most useful, informative, and comprehensive on the web covering stats and quantitative analysis.

Comprehensive Statistics Sites

These sites give a good overview of how statistics can be useful and interesting in a range of different fields, from science to politics.

Big Data & Machine Learning

Big Data and Machine Learning are two of the hottest topics in the tech startup community now. Massive companies like Google, Apple, and Amazon are finding more ways to gather user data and monetize it by selling advertisements based on demographic info, or even selling the data itself. Smaller companies are also getting in on the action as it becomes more and more clear that consumer data is one of the most valuable commodities around.

Biostatistics

Biostatistics is the use of statistical models to learn about diseases, epidemiology, the effectiveness of medicine, and other biological and medical applications.

Socioeconomic & Political Analysis

By gathering long term voting and census data and taking surveys, it is possible to get statistically significant data about the demographic composition of neighborhoods, cities, and whole countries.

R Programming

R is a programming language used often for building statistical models and visualizing large datasets to make them easier to draw conclusions from. There’s a robust community of R programmers online, making it easy to learn the language and find answers to even obscure questions about implementations of R.

Data Visualization

Not all data visualization is statistical in nature, but since statisticians often use large, complexly interrelated data sets, it is valuable to be able to generate graphs and other visualizations that are easier to understand for the statisticians themselves and for the public.

Sports Stats

Any true baseball fan can tell you the RBI of their favorite players, but professional stats hounds take sports statistics to a whole different level.