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Course Description Course Name : Mathematical Statistics 1 Course Code : EM 207 Course Type : Compulsory Level of Course : First Cycle Year of Study : 2 Course Semester : Fall (16 Weeks) ECTS : 5 Name of Lecturer(s) : Asst.Prof.Dr. EBRU ÖZGÜR GÜLER Asst.Prof.Dr. GÜLSEN KIRAL Asst.Prof.Dr. HÜSEYİN GÜLER Learning Outcomes of the Course : Describes basic probability concepts Discriminates between discrete and continuous random variables Obtains single and bivariate probability and distribution functions Knows the properties of random variables Describes expected values, variance and moment topics Discrimantes common discrete random variables Calculates probability functions, expected values, variance and moments for common discrete random variables Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : Describing, incorporating and analyzing fundamental topics of probability and statistics using mathematics is aimed in this course. Course Contents : Contents of this course cover reviewing basic statistical topics, discriminating discrete and contionus random variables, obtaining probability, density, and distribution functions for random variables. Properties of random variables, expected values, variance and moments and distinctive features of some common discrete random variables are also given. Language of Instruction : Turkish Work Place : Classroom   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Motivation: Information about references and describing fundemantal concepts Lecture, problem session 2 Investigation of basic probability statements and the probability function Related chapter from the reference book Lecture, problem session 3 Usage of conditional probability and Bayes´ theorem Related chapter from the reference book Lecture, problem session 4 The concept of independency, repeated independent trials Related chapter from the reference book Lecture, problem session 5 Probability and probability density functions of random variables Related chapter from the reference book Lecture, problem session 6 Independence of random variables, conditional probability functions Related chapter from the reference book Lecture, problem session 7 Functions of single and bivariate random variables, calculation of expected value and variance Quiz before the midterm exam Lecture, problem session 8 Midterm 9 Moments: Moments about origin and mean, and their properties Related chapter from the reference book Lecture, problem session 10 Moment generating function, its properties, and practical usages Related chapter from the reference book Lecture, problem session 11 Discrete distributions: Properties of Bernoulli and binomial distributions Related chapter from the reference book Lecture, problem session 12 Discrete distributions (cont): Properties of generalized binomial and geometrical distributions Related chapter from the reference book Lecture, problem session 13 Discrete distributions (cont): Properties of Pascal, hypergoemetric, and Poisson distributions Related chapter from the reference book Lecture, problem session 14 Relationships between discrete random variables and examples to discriminate discrete random variables Related chapter from the reference book Lecture, problem session 15 General review and examples Quiz before the final exam Problem session 16/17 Final Exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  MATEMATİKSEL İSTATİSTİK, Prof. Dr. Mustafa AYTAÇ, Ezgi Kitabevi, Bursa 2012, Genişletilmiş 4. Baskı. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 90     Homeworks/Projects/Others 2 10 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 Models problems with Mathematics, Statistics, and Econometrics 4 2 Explains Econometric concepts 3 3 Estimates the model consistently and analyzes & interprets its results 4 4 Acquires basic Mathematics, Statistics and Operation Research concepts 4 5 Equipped with the foundations of Economics, and develops Economic models 0 6 Describes the necessary concepts of Business 0 7 Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems 4 8 Collects, edits, and analyzes data 5 9 Uses a package program of Econometrics, Statistics, and Operation Research 3 10 Effectively works, take responsibility, and the leadership individually or as a member of a team 2 11 Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study 3 12 Develops the ability of using different resources in the form of academic rules, synthesis the information gathered, and effective presentation in an area which has not been studied 3 13 Uses Turkish and at least one other foreign language, academically and in the business context 1 14 Good understanding, interpretation, efficient written and oral expression of the people involved 1 15 Questions traditional approaches and their implementation while developing alternative study programs when required 2 16 Recognizes and implements social, scientific, and professional ethic values 1 17 Follows actuality, and interprets the data about economic and social events 2 18 Improves himself/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development 0 * 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 4 56 Assesment Related Works     Homeworks, Projects, Others 2 4 8     Mid-term Exams (Written, Oral, etc.) 1 6 6     Final Exam 1 8 8 Total Workload: 120 Total Workload / 25 (h): 4.8 ECTS Credit: 5