[ml] Machine Learning Lecture Wed 5/5: A Brief Tour of Statistics

[Thomas Lotze]

Hey all!  Next week, I'm going to try to give a brief tour of statistics:
how to think like a statistician, what statisticians are trying to do, and
some big statistical ideas relevant to machine learning.  I'm hoping to give
people a good understanding of statistical thinking, and hopefully spawn
some ideas on future talks.  We'll meet at 8 PM in the same place we've been
meeting (the classroom in the back corner)

I'm planning on starting fairly promptly (8:05) regardless of how many
people are here, because there's a lot I'm hoping to talk about -- so please
arrive as close to 8 PM as possible!

The topics I'm planning on covering are:

   - Basic statistics and probability: random numbers and distributions
   - Some good distributions to know: binomial, poisson, normal
   - Estimating distribution parameters
   - Unbiased estimators and the bias/variance tradeoff
   - Confidence intervals, Testing and p-values
   - Maximum Likelihood Estimators
   - Another look at Regression
   - Logistic Regression
   - Why statisticians love the normal distribution
   - Why Taleb Naseem hates the normal distribution
   - Bootstrapping techniques
   - A statistical perspective on Induction
   - What Bayesian Statistics is basically about

But if you have anything else you're interested in, let me know!

Cheers,
Thomas
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