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)