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Course Description Course Name : Statistical Methods Course Code : TEM203 Course Type : Compulsory Level of Course : First Cycle Year of Study : 2 Course Semester : Fall (16 Weeks) ECTS : 3 Name of Lecturer(s) : Assoc.Prof.Dr. GÜZİN YÜKSEL Learning Outcomes of the Course : Chooses research question and the method Collects and arranges data Analyzes the data Determines central tendency and measure of deviation. Makes the hypothesis testing. Applies probability and sampling distribution at engineering problems. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The aim of this course is to teach basic concepts, principles, techniques of science of statistics and the terminology that is required for them; to earn the competency/ability to appropriately use and interpret statistical concepts, principles and techniques. Course Contents : Basic Concepts,Types Of Data, Data Sources, Data Collection Techniques, Sampling Techniques, Frequency Distributions, Measure of Central Tendencies, Measure of Variability, Measure of Skewness and Measure of Kurtosis, Probability and Special Probability Distributions, Normal Distribution, Confidence intervals, Hypothesis testing, Regression Language of Instruction : Turkish Work Place : Faculty of Engineering Classrooms   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Basic Concepts Reading the source Lecture 2 Types Of Data, Data Sources Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 3 Data Collection Techniques Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 4 Sampling Techniques Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 5 Frequency Distributions Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 6 Measure of Central Tendencies Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 7 Measure of Variability, Measure of Skewness and Measure of Kurtosis Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 8 Midterm Review the topics discussed in the lecture notes and sources Written exam 9 Probability and Special Probability Distributions Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 10 Special Probability Distributions Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 11 Normal Distribution Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 12 Confidence intervals Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 13 Hypothesis testing Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 14 Regression Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 15 Regression Reading the source, problem solving Lecture,Solving problems, Discussion, presentation 16/17 Final Exam Review the topics discussed in the lecture notes and sources Written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Fikri Akdeniz ,2010, Olasılık ve İstatistik, Nobel Kitabevi, Adana.  Yaşar Baykul, 1997, İstatistik Metodlar ve Uygulamalar, Anı yayıncılık, Ankara. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 100     Homeworks/Projects/Others 0 0 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 information and communication technologies and softwares at a required level 3 2 Has the professional and ethical responsibility. 3 3 Uses the knowledge obtained from the basic sciences and engineering in the field of textile engineering 4 4 Does process analysis, Identifies problems, interprets and evaluates data in the field of textile engineering 4 5 Selects and uses modern techniques and tools for engineering applications 1 6 Has the skills of designing experiments, data collection, cognitive analysis and interpretation of the results 5 7 Works effectively both individually and as a team member and takes responsibility 4 8 Searches literature, has access to information, uses databases and other sources of information 3 9 Recognizes the need of lifelong learning; follows developments in science and technology and renews self continuosly 1 10 Has effective oral and written communication skills. 2 11 Follows developments in the field in a foreign language, has good communication skills with colleagues. 2 12 Has the necessary awareness on the fields of occupational health and safety, legal side of engineering applications and environmental health. 0 13 Has required competence in project management, entrepreneurship and innovation. 1 14 Has sufficient background in the fields of Mathematics, Science and Textile Engineering 4 * 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 2 28     Out of Class Study (Preliminary Work, Practice) 14 2 28 Assesment Related Works     Homeworks, Projects, Others 0 0 0     Mid-term Exams (Written, Oral, etc.) 1 5 5     Final Exam 1 5 5 Total Workload: 66 Total Workload / 25 (h): 2.64 ECTS Credit: 3