# GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
MATHEMATICAL STATISTICS II/İST2002
 Course Title: MATHEMATICAL STATISTICS II Credits 4 ECTS 7 Course Semester 4 Type of The Course Compulsory
COURSE INFORMATION
-- (CATALOG CONTENT)
-- (TEXTBOOK)
-- (SUPPLEMENTARY TEXTBOOK)
-- (PREREQUISITES AND CO-REQUISITES)
-- LANGUAGE OF INSTRUCTION
Turkish
-- COURSE OBJECTIVES
-- COURSE LEARNING OUTCOMES
Point estimation theory
Estimation methods
Properties of Estimators
Interval estimation theory
Hypothesis testing and theory

-- MODE OF DELIVERY
The mode of delivery is face to face
 --WEEKLY SCHEDULE 1. Week Point estimation methods: Moments Estimation Method 2. Week Point estimation methods: Maximum likelihood Estimation Method 3. Week Point estimation methods: Bayesian Estimation Method 4. Week Properties of estimators: Unbiasedness, Consistency and Efficiency 5. Week Properties of estimators: Unbiasedness, Consistency and Efficiency 6. Week Properties of estimators: Fisher Information Matrix, Rao-Cramer inequality and applications 7. Week Properties of estimators: Sufficiency, Rao-Blackwell theorem and applications 8. Week Testing Hypothesis: Neyman-Pearson Theorem, Critical Region, Mid-term examination 9. Week Testing Hypothesis: Power of test, type I and type II error 10. Week Testing Hypothesis: Likelihood Ratio Test 11. Week Testing Hypothesis: Likelihood Ratio Test and applications 12. Week Confidence Intervals: confidence intervals by pivotal method and applications 13. Week Confidence Intervals: Classical Confidence Intervals 14. Week Confidence Intervals: Classical Confidence Intervals and applications 15. Week Final Exam 16. Week
-- TEACHING and LEARNING METHODS
-- ASSESSMENT CRITERIA
 Quantity Total Weighting (%) Midterm Exams 1 30 Assignment 5 10 Application 0 0 Projects 0 0 Practice 0 0 Quiz 0 0 Percent of In-term Studies 40 Percentage of Final Exam to Total Score 60