Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Statistics and distributions, sampling and statistics Review of the literature
2 Sampling distribution function and some related statistics, sampling density function, sampling percentage Review of the previous lesson and the literature
3 Skor function and fisher information. Data reductions Review of the previous lesson and the literature
4 Completeness, likelihood principle Review of the previous lesson and the literature
5 Parameter estimation methods (ML, moments, OLS, Bayes) Review of the previous lesson and the literature
6 Hypothesis testing, simple and compound hypothesis, test function Review of the previous lesson and the literature
7 Likelihood ratio test Review of the previous lesson and the literature
8 Mid-term exam Review of the previous lesson and the literature
9 Neymann-Pearson lemmaı , application of Neymann-Pearson lemma Review of the previous lesson and the literature
10 Bayes tests, power functions, UMPT, p-value Review of the previous lesson and the literature
11 Application of Hypothesis testing Review of the previous lesson and the literature
12 Application of Hypothesis testing Review of the previous lesson and the literature
13 Confidence intervals, point estimation Review of the previous lesson and the literature
14 Bayes confidence intervals, approximate confidence intervals Review of the previous lesson and the literature
15 Confidence intervals using Pivot Review of the previous lesson and the literature
16-17 Final exam Review of the previous lesson and the literature

Recommended or Required Reading
Textbook
Additional Resources