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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS PHY 5105 DATA ANALYSIS TECHNIQUES FOR HIGH ENERGY PHYSICS-I ELECTIVE 3 0 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR MUHAMMED DENIZ

Offered to

PHYSICS PHYSICS

Course Objective

Learning data analysis programs and techniques in Particle/High Energy Physics

Learning Outcomes of the Course Unit

1   Programming languages such as Fortran and C 2   Data analysis techniques with Physics Analysis Workstation (PAW) package 3   Basic concept of error analysis 4   Vector/Histogram/Ntuple structure 5   How to apply cuts and selection rules to the data 6   Learn the basic Unix commands and the use of the Linux operating system,

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 General overview of PAW and basic principles 2 Vectors Tutorial and examples 3 Vector arithmetic operations w/o Sigma Operations 4 Histograms Tutorial and examples 5 Histogram Operations 6 1. Midterm 7 Fitting the contents of vectors and Histograms 8 Functions in PAW 9 HBOOK 10 Ntuples Tutorial and examples 11 2. Midterm 12 Ntuple Operations 13 Ntuple cut definition 14 Ntuple drawing

Recomended or Required Reading

PAW CERN Programs Tutorial Book Supplementary Book(s): http://paw.web.cern.ch/paw/

Planned Learning Activities and Teaching Methods

1. Method of Expression 2. Question & Answer Techniques 3. Discussion 4. Homework

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 ASG 1 ASSIGNMENT 1 3 ASG 2 ASSIGNMENT 2 4 FIN FINAL EXAM 5 FCG FINAL COURSE GRADE MTE * 0.25 + ASG1 +ASG 2/2 * 0.25 + FIN * 0.50 6 RST RESIT 7 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG 1 +ASG2/2 * 0.25 + RST * 0.50

Further Notes About Assessment Methods

Attandance, homeworks and exams

Assessment Criteria

1. Midterms, assignments, homeworks and laboratory activities are considered as success criteria for the semester. 2. Final exam grade will be added to the semester grade to determine the success.

Language of Instruction

English

Course Policies and Rules

1. 70% of the participation of classes is mandatory. 2. Students, who do not participate in Midterm exams and regularly do the assignments, not allowed entering the final exam.

Contact Details for the Lecturer(s)

muhammed.deniz@deu.edu.tr

Office Hours

Monday at 13: 30 - 15: 30

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 3 36 Tutorials 3 3 9 Preparations before/after weekly lectures 12 5 60 Preparation for midterm exam 2 5 10 Preparation for final exam 1 5 5 Preparing assignments 6 5 30 Midterm 2 3 6 Final 1 3 3 Quiz etc. 6 3 18 TOTAL WORKLOAD (hours) 177

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 2 2 5 5 5 5 4 5 5 5 LO.2 2 2 5 5 5 4 4 3 4 3 LO.3 2 3 5 5 5 4 4 3 4 5 LO.4 5 5 5 5 5 4 4 3 4 5 LO.5 3 3 5 5 5 4 4 3 4 5 LO.6 5 5 5 5 5 5 5 5 5 5