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Course Description Course Name : Statistics I Course Code : EM 201 Course Type : Compulsory Level of Course : First Cycle Year of Study : 2 Course Semester : Fall (16 Weeks) ECTS : 3 Name of Lecturer(s) : Asst.Prof.Dr. EBRU ÖZGÜR GÜLER Asst.Prof.Dr. HÜSEYİN GÜLER Learning Outcomes of the Course : Summarizes raw data with the frequency table Describes data with graphical methods Finds the location of data with central tendency measures Determines the spread of data with measures of dispersion Distinguish between permutation and combination Describes the basic probability rules and computes the probability of an event Distinguish between discrete and continuous random variables Finds the probability and distribution functions of a random variable Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : It is aimed to report raw or grouped data with descriptive statistics. It is also aimed to investigate the calculation of a probability and basic probability concepts, discrete and continuous random variables. Course Contents : This course covers how to calculate and interprete appropriate descriptive statistics for grouped and ungrouped (raw) data. Other topics are basic probability rules, random variable concept and the distinction between discrete and continuous random variables. 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 basic concepts Lecture, problem session 2 Editing and analyzing data Homework #1: Creating the frequency table from a raw data Lecture, problem session 3 Computing and comparing central tendency measures for grouped and ungrouped data Related chapter from the reference book Lecture, problem session 4 Computing and comparing dispersion measures for grouped and ungrouped data Homework #2: Computing tendancy and dispersion measures for raw and grouped data Lecture, problem session 5 Set theory and the notion of sample space Related chapter from the reference book Lecture, problem session 6 Permutation and combination Related chapter from the reference book Lecture, problem session 7 Introduction to probability: Probability axioms, computing a probability, conditional probability, independent events and Bayes´ theorem Related chapter from the reference book Lecture, problem session 8 Midterm 9 Random variables and distributions of discrete random variables Related chapter from the reference book Lecture, problem session 10 Distributions of continuous random variables Related chapter from the reference book Lecture, problem session 11 Computing the expected value and variance of a random variable Related chapter from the reference book Lecture, problem session 12 Basic properties of Bernoulli and binomial distributions Related chapter from the reference book Lecture, problem session 13 Basic properties of geometrical and Poisson distributions Related chapter from the reference book Lecture, problem session 14 Basic properties of uniform distribution and comprehensive applications for 5 discrete distributions Related chapter from the reference book Lecture, problem session 15 General review and applications A general review of topics Problem session and discussion 16/17 Final Exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  AKDENİZ, F. (2012), Olasılık ve İstatistik. Akademisyen Yayınevi, 18. Baskı.  TURANLI, M. ve GÜRİŞ, S. (2010), Temel İstatistik. Der yayınevi, 3. 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 uses modern communication tools, methods and processes, collects and interprets data from different sources using 4 2 understands and explains the role of the public and private sector in the economy, the market economy and the function of the public sector 1 3 uses the information of profesional field about basic computer knowledge and skills 3 4 Collect quantitative and statistical data, makes analysis and interpretation 5 5 understands and interprets corecctly the feelenings, thoughts and behaviors of other people, express Themselves in written and oral form. 0 6 Aware of the social, scientific and ethical values ??and acts accordingly 0 7 Questions the traditional approach and methods of application,and he to develops and implements new ways of working if he considers it is necesaary 3 8 Individually and / or in a team, take responsibility, leadership, and effectively works 1 9 In recognition of the need for lifelong learning and constantly renews itself keeps track of the latest developments. 1 10 3 11 UseTurkish in academic life and work in accordance with the requirements of the uses of life. 1 12 Use different resources in accordance with the academic rules, synthesize the information gathered, and present them effectively in an area which has not been studied 3 13 Use Turkish and at least one foreign language in accordance with the prerequisities of academic and business context 1 14 Develop scientific and ethical values in the fields of statistics-and scientific data collection 5 * 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 1 14 Assesment Related Works     Homeworks, Projects, Others 2 2 4     Mid-term Exams (Written, Oral, etc.) 1 6 6     Final Exam 1 8 8 Total Workload: 74 Total Workload / 25 (h): 2.96 ECTS Credit: 3