Stat 311: Introductory Probability (Banner Course Number: 31100)
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No Information available.Outline:
| Approximate Hours |
||
|---|---|---|
| 1 | A. | Introduction |
| 2 | B. | Sample spaces and probability axioms |
| 5 | C. | Equally likely outcomes, combinatorics, binomial probabilities |
| 3 | D. | Conditional probability, Bayes theorem and independence |
| 1 | E. | Continuous sample spaces |
| 5 | F. | Random variables, density and distribution functions, uniform and exponential r.v.'s |
| 2 | G. | Expected values. Mean and variance |
| 2 | H. | Random variables in two dimensions |
| 1 | I. | Expected values; covariances |
| 3 | J. | Conditional distributions and independence |
| 2 | K. | Poisson distribution |
| 3 | L. | Normal distribution and central limit theorem |
| 1 | M. | Chebychev inequality, law of large numbers |
| 12 | N. | Short introduction to statistics |
