The lectures notes are available as single files mapped to the lecture sessions below or as a complete document (PDF - 1.45MB).
| LEC # | TOPICS | LECTURE NOTES |
|---|---|---|
| 1 |
Estimation Theory Introduction | (PDF) |
| 2 | Some Probability Distributions | (PDF) |
| 3 | Method of Moments | (PDF) |
| 4 | Maximum Likelihood Estimators | (PDF) |
| 5 | Consistency of MLE Asymptotic Normality of MLE, Fisher Information | (PDF) |
| 6 | Rao-Crámer Inequality | (PDF) |
| 7 | Efficient Estimators | (PDF) |
| 8 | Gamma Distribution Beta Distribution | (PDF) |
| 9 | Prior and Posterior Distributions | (PDF) |
| 10 | Bayes Estimators Conjugate Prior Distributions | (PDF) |
| 11 | Sufficient Statistic | (PDF) |
| 12 | Jointly Sufficient Statistics Improving Estimators Using Sufficient Statistics, Rao-Blackwell Theorem | (PDF) |
| 13 | Minimal Jointly Sufficient Statistics χ2 Distribution | (PDF) |
| 14 | Estimates of Parameters of Normal Distribution | (PDF) |
| 15 | Orthogonal Transformation of Standard Normal Sample | (PDF) |
| 16 | Fisher and Student Distributions | (PDF) |
| 17 | Confidence Intervals for Parameters of Normal Distribution | (PDF) |
| 18 |
Testing Hypotheses Testing Simple Hypotheses Bayes Decision Rules | (PDF) |
| 19 | Most Powerful Test for Two Simple Hypotheses | (PDF) |
| 20 | Randomized Most Powerful Test Composite Hypotheses. Uniformly Most Powerful Test | (PDF) |
| 21 | Monotone Likelihood Ratio One Sided Hypotheses | (PDF) |
| 22 | One Sided Hypotheses (cont.) | (PDF) |
| 23 | Pearson's Theorem | (PDF) |
| 24 | Goodness-of-Fit Test Goodness-of-Fit Test for Continuous Distribution | (PDF) |
| 25 | Goodness-of-Fit Test for Composite Hypotheses | (PDF) |
| 26 | Test of Independence | (PDF) |
| 27 | Test of Homogeneity | (PDF) |
| 28 | Kolmogorov-Smirnov Test | (PDF) |
| 29 |
Simple Linear Regression Method of Least Squares Simple Linear Regression | (PDF) |
| 30 | Joint Distribution of the Estimates | (PDF) |
| 31 | Statistical Inference in Simple Linear Regression | (PDF) |
| 32 | Classification Problem | (PDF) |