Misc. Lectures Online

I highly recommend the following lectures for anyone interested in social science research using quantitative methods:

• The late Sam Roweis (a brilliant educator who died unexpectedly several years ago) gives a superb introduction to machine learning and probabilistic graphical models here, complete with lecture slides. In case you aren't aware, probabilistic graphical models are in effect a unifying approach to a wide range of statistical models, from hidden Markov models to hierarchical Bayesian models.
• Salman Khan, the MIT graduate who started the eponymous Khan Academy, offers a superb series of lectures on probability, available here. Probability is actually the foundation for quantitative research in the social sciences, since much of the goal of inference is to quantify uncertainty through the use of probability distributions such as the Gaussian, Poisson, Gamma, and so forth.
• Although for programmers in python, the computer scientist Allen Downey gives a thorough, intuitive, and entertaining overview of Bayesian analysis, which you can view in its entirety here.