MATLAB® software is required to run the .m files in this section.
The notes for Lectures 9 and 12 are not available.
| 1 | Course Introduction (PDF) | | | 2 | Descriptive Statistics (PDF) | | | 3 | Probablility (PDF) | virtual.m (M) | | 4 | Joint Probability, Independence, Repeated Trials (PDF) | | | 5 | Combinatorial Methods for Deriving Probabilities (PDF) | combinatorial_example.pdf (PDF)
balls.m (M) | | 6 | Conditional Probability and Baye's Theorem (PDF) | | | 7 | Random Variables and Probability Distributions (PDF) | | | 8 | Expectation, Functions of a Random Variable (PDF) | | | 9 | Risk | | | 10 | Some Common Probability Distributions (PDF) | cdffit.m (M) | | 11 | Multivariate Probability (PDF) | | | 12 | Functions of Many Random Variables | | | 13 | Populations and Samples (PDF) | | | 14 | Estimation (PDF) | | | 15 | Confidence Intervals (PDF) | | | 16 | Testing Hypotheses about a Single Population (PDF) | | | 17 | Testing Hypotheses about Two Populations (PDF) | | | 18 | Small Sample Statistics (PDF) | | | 19 | Analysis of Variance (PDF) | | | 20 | Analysis of Variance (contd.) (PDF) | | | 21 | Multifactor Analysis of Variance (PDF) | | | 22 | Linear Regression (PDF) | | | 23 | Analyzing Regression Results (PDF) | |
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