ST606 :

Elective

· The concept of Bayesian decision making , Expected loss and decision rules (nonrandomized and randomized).

· The Decision principles (conditional Bayes, frequents), inference as decision problem and optimal decision rules.

· The Bayes and minimax decision rule and admissibility of minimax. Conjugate prior families and hierarchical priors.

· The Parametric Empirical Bayes, Posterior distribution, Loss function and squared error loss.

The precautionary loss and LINEX loss and Bayes HPD confidence intervals

أ‌. (Knowledge & understand)

أ.1	The student will be able to deal with the basic elements of Statistical Decision Problem, Expected loss and decision rules (nonrandomized and randomized).
أ.2	The student will be able to study the Decision principles (conditional Bayes, frequents), inference as decision problem and optimal decision rules.
أ.3	The student will be able to understand Bayes and minimax decision rule and admissibility of minimax. Conjugate prior families and hierarchical priors.
أ.4	The student will be able to study Parametric Empirical Bayes, Posterior distribution, Loss function and squared error loss.
أ.5	The student will be able to study precautionary loss and LINEX loss and Bayes HPD confidence intervals.

ب‌. (Mental skills)

ب.1	The student can deal with the basic elements of Statistical Decision Problem, Expected loss and decision rules (nonrandomized and randomized).
ب.2	The student can study the Decision principles (conditional Bayes, frequents), inference as decision problem and optimal decision rules.
ب.3	The student can understand Bayes and minimax decision rule and admissibility of minimax. Conjugate prior families and hierarchical priors.
ب.4	The student can study Parametric Empirical Bayes, Posterior distribution, Loss function and squared error loss.
ب.5	The student can study precautionary loss and LINEX loss and Bayes HPD confidence intervals.

جـ - (Practical & professional skills)

ج.1	The ability to understand deal with the basic elements of Statistical Decision Problem, Expected loss and decision rules (nonrandomized and randomized).
ج.2	The ability to study the Decision principles (conditional Bayes, frequents), inference as decision problem and optimal decision rules.
ج.3	The ability to understand Bayes and minimax decision rule and admissibility of minimax. Conjugate prior families and hierarchical priors.
ج.4	The ability to study Parametric Empirical Bayes, Posterior distribution, Loss function and squared error loss.
ج.5	The ability to study precautionary loss and LINEX loss and Bayes HPD confidence intervals.

د - (Generic and transferable skills)

د.1	The student will be able to deal with the basic elements of Statistical Decision Problem, Expected loss and decision rules (nonrandomized and randomized).
د.2	The student will be able to study the Decision principles (conditional Bayes, frequents), inference as decision problem and optimal decision rules.
د.3	The student will be able to understand Bayes and minimax decision rule and admissibility of minimax. Conjugate prior families and hierarchical priors.
د.4	The student will be able to study Parametric Empirical Bayes, Posterior distribution, Loss function and squared error loss.
د.5	The student will be able to study precautionary loss and LINEX loss and Bayes HPD confidence intervals.

•Lectures.• Solve exercises and assignments.• Panel discussions.