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Course Description Course Name : Data Analyzing Methods in High Energy Physics I Course Code : FK-527 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Prof.Dr. AYŞE POLATÖZ Learning Outcomes of the Course : Understands the basic terms in experimental high energy physics Learns the packet programs used in data analysis Learns the analysis methods Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : To provide learning of packet programs and data analysis techniques used in experimental High Energy Physics. Course Contents : Probability distributions, error estimation, ROOT, PHYTIA, GEANT Applications Language of Instruction : Turkish Work Place : Lecture hall of faculty   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Basic Terms: Probability, probability distributions, histogram, frequency distributions, average value, standard deviation. Research the related topic Lecture, discussion 2 Error estimation: Random and systematic errors, permutation and combination. Research the related topic Lecture, discussion 3 Error estimation: Binom, Gaussian and Poisson distributions. Research the related topic Lecture, discussion 4 Problem solving Research the related topic Lecture, discussion 5 The packet programs used in data analysis-1:introduction to ROOT Research the related topic Lecture, discussion 6 The packet programs used in data analysis-1: ROOT- continue Research the related topic Lecture, discussion 7 The packet programs used in data analysis-1: ROOT applications Research the related topic Lecture, discussion 8 The packet programs used in data analysis-2: usage of PHYTIA Research the related topic Lecture, discussion 9 Mid-term Exam Mid-term Exam LMid-term Exam 10 The packet programs used in data analysis-2: PHYTIA applications Research the related topic Lecture, discussion 11 The packet programs used in data analysis-2: PHYTIA applications Research the related topic Lecture, discussion 12 TThe packet programs used in data analysis-3:İntroduction to GEANT Research the related topic Lecture, discussion 13 The packet programs used in data analysis-3: GEANT-continue Research the related topic Lecture, discussion 14 The packet programs used in data analysis-3: GEANT applications Research the related topic Lecture, discussion 15 Problem solving Homework Lecture, discussion 16/17 Final Exam Final Exam Final Exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Hastie, Tibshirani, Friedman, The Elements of Statistical Learning, Springer (2001)  N.C. Barford, Experimental Measurements: Precision, Error and Truth, John Wiley & Sons (1985)  http://root.cern.ch/ ; http://wwwasd.web.cern.ch/wwwasd/geant/  http://home.thep.lu.se/~torbjorn/pythiaaux/ Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 70     Homeworks/Projects/Others 1 30 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 Develop and deepen the knowledge as a specialist in physics or different areas based on the Physics Bachelor´s qualification level. 3 2 Comprehend the importance of multidisciplinary studies related to Physics. 3 3 Use his/her advanced theoretical and practical knowledge in Physics efficiently. 3 4 Integrate and interpret the knowledge from different disciplines with the help of his professional knowledge in Physics and conceptualize new perspectives. 3 5 Solve the problems in Physics by using research methods. 3 6 Carry out a study requiring expertise in physics independently. 3 7 Develop and provide new strategic approaches by taking responsibilty while solving the unexpected problems in Physics . 3 8 Take the responsibility of being the leader while solving the problems related to physical environments. 3 9 Evaluate the knowledge and skills gained in Physics by having a critical view and directs his/her learning. 3 10 Systematically transfer the current developments in the field of physics and his/her work to the person in physics field or outside of the field by supporting qualitative and quantitative data. 3 11 Take action to change the norms of social relations and critically examine these relationships, and develop them if necessary. 3 12 Make communication in oral and written by using at least one foreign language in the level of European Language Portfolio B2 level. 2 13 Use information and communication technologies in advanced level and use the software related with physics area. 3 14 Oversee social, scientific, cultural and ethical values in order to collect, implement, interpret data in Physics. 3 15 Develop strategies, policies and implementation plans in the issues related to the field of physics and evaluate the results obtained within the framework of quality processes. 3 16 Use the knowledge, problem solving, and / or practical skills obtained in the Physics Field in interdisciplinary studies. 3 * 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 1 15 15     Mid-term Exams (Written, Oral, etc.) 1 20 20     Final Exam 1 20 20 Total Workload: 139 Total Workload / 25 (h): 5.56 ECTS Credit: 6