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Gain insights into probability rules, model-building, random variables, distributions, expectations, and statistical analysis. Covering various topics like Bayes' Rule, moments, densities, joint variables, and hypothesis testing.
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8/30/2012 Goals: • Rules of Probability • Counting • Equally likely • Some examples
9/4/2012 Goals • Conditional Probability • Model-building
9/6/2012 • Independence • Definition • Model-building • Examples
9/11/2012 • Bayes’ Rule • Implicit conditional probabilities • Random variables (if possible)
9/13/2012 • Discrete random variables • Examples • Uniform • Geometric • Binomial • Bernoulli • Probability mass functions • Expectations
9/27/2012 • Expectations and variances • Direct computations • Moment generating functions (not in book)
9/18/2012 • Expectations • Means • Variances • Moment generating functions • Several random variables • Binomial • Geometric • Bernoulli • Poisson • Uniform
9/20/2012 • Review
9/28/2012 • Expectations and Variances • Bernoulli • Binomial • Law of large numbers
10/2/2012 • Moment generating function • Bernoulli • Binomial • Geometric • Negative Binomial • Poisson • Begin continuous random variables
10/4/2012 • Continuous random variables • Properties of densities • Exponential random variables
10/9/2012 • Poisson connection to exponential random variables • Gaussian random variables
10/11/2012 • Gaussian random variables • Limit theorems
10/18/2012 • Joint random variables • Joint probability mass function • Conditioning • Marginals
10/23/2012 • More joint random variables • Joint probability mass function • Conditioning • Marginals
11/1/2012 • More on transformations of random variables • Joint Gaussians
11/6/2012 • Statistical analysis of data • Sample mean, sample variance, population variance • Histograms and frequency plots
11/13/2012 • Estimation of parameters • Bernoulli • Exponential • Gaussian
11/15/2012 • Hypothesis testing (9-5)