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Course Description Course Name : Mathematical Statistics II Course Code : IEM 733 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. GÜLSEN KIRAL Learning Outcomes of the Course : Resolves the theoretical structure of important discrete and continuous probability distributions Applies the knowledge of basic sciences Determines the theoretical mathematical structure of frequency distrubitions Uses the estimation methods effectively Finds solutions to the problems by using a multivariate normal distribution Has the necessary skills to analyze the data, evaluate, test and design Has the ability to review the strengths and weaknessesof mathematical structure of statistical distributions Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The aim of the course is to ensure that students are able to create the relationship between the structure and applications of mathematical statistics . The mathematical structure of the basic concepts of statisticsis is taught in detail throughout the course. Course Contents : The course covers Central Limit Theorem, parameter estimation, point estimation, features of point estimation, unbiased, consistency, sufficiency, estimation methods, least squares, the many similarities and moments, Multivariate Normal Distribution (marginal, conditional), Quadratic Form. Language of Instruction : Turkish Work Place : graduate classrooms (1. Blok) comp. room (1. Blok)   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Continuous Probability Distributions Reading the relevant parts in the book Lecture 2 Sampling Distributions Reading the relevant parts in the book Lecture 3 Functions of Random Variables Reading the relevant parts in the book Lecture 4 Statistical forecasting and decision-making theory Reading the relevant parts in the book Lecture 5 Point estimation, maximum likelihood estimation method Reading the relevant parts in the book Lecture 6 Estimation by the method of moments, the mean squared error Reading the relevant parts in the book Lecture 7 Review 8 Midterm exam 9 Estimators properties, drift, convergent and sufficient estimators Reading the relevant parts in the book Lecture 10 Interval estimation, confidence interval for the mean and variance of the community Reading the relevant parts in the book Lecture 11 Confidence interval for the difference in means and proportions, the confidence interval for the variance Reading the relevant parts in the book Lecture 12 Homework preentations 13 Test theory, testing simple and compound hypothesis Reading the relevant parts in the book Lecture 14 Type I and II error test, the power function Reading the relevant parts in the book Lecture 15 Likelihood test, chi-square test Reading the relevant parts in the book Lecture 16/17 Final Exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)     Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 50     Homeworks/Projects/Others 3 50 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Explains Econometric concepts 1 2 Equipped with the foundations of Economics, develops Economic models 1 3 Models problems using the knowledge of Mathematics, Statistics, and Econometrics 3 4 Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems 3 5 Collects, edits, and analyzes data 3 6 Uses advanced software packages concerning Econometrics, Statistics, and Operation Research 2 7 Develops the ability to use different resources in an area which has not been studied in the scope of academic rules, synthesizes the information gathered, and gives effective presentations 4 8 Speaks Turkish and at least one other foreign language in accordance with the requirements of academic and business life. 5 9 Questions traditional approaches and their implementation and develops alternative study programs when required 4 10 Recognizes and implements social, scientific, and professional ethic values 4 11 Gives a consistent estimate for the model and analyzes and interprets its results 2 12 Takes responsibility individually and/or as a member of a team; leads a team and works effectively 2 13 Defines the concepts of statistics, operations research and mathematics. 2 14 Knowing the necessity of life-long learning, follows the latest developments in the field of study and improves himself continiously 1 15 Follows the current issues, and interprets the data about economic and social events. 1 16 Understands and interprets the feelings, thoughts and behaviours of people and expresses himself/herself orally and in written form efficiently 2 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 3 42 Assesment Related Works     Homeworks, Projects, Others 3 14 42     Mid-term Exams (Written, Oral, etc.) 1 8 8     Final Exam 1 8 8 Total Workload: 142 Total Workload / 25 (h): 5.68 ECTS Credit: 6