COURSE UNIT TITLE

: DATA ANALYSIS IN PHYSICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
FIZ 3120 DATA ANALYSIS IN PHYSICS ELECTIVE 2 2 0 7

Offered By

Physics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR MUHAMMED DENIZ

Offered to

Physics

Course Objective

Learn how to do experimental data analysis, learn the concept of experimental error and how to do fitting to the distributions to measure the physical quantities, learn data analysis programs and techniques used in Physics in general.

Learning Outcomes of the Course Unit

1   Learning basic Unix commands and skills of how to use Linux operating system
2   Learning programming languages such as Fortran and C
3   Learning data analysis techniques
4   Learning basic concept of error analysis
5   Ability to interpret the scientific data

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Basic Unix Commands and general overview of Linux Operating system - I
2 Basic Unix Commands and general overview of Linux Operating system - II
3 General overview of PAW and basic principles, Vectors Tutorial and examples
4 Vector arithmetic operations w/o Sigma Operations
5 Histograms - Tutorial and examples
6 MIDTERM - I
7 Histogram Operations
8 Fitting the contents of vectors and Histograms
9 Functions in PAW
10 HBOOK
11 MIDTERM - II
12 Ntuples - Tutorial and examples
13 Ntuple Operations
14 Ntuple cut definition and drawing

Recomended or Required Reading

Textbook(s):
1. PAW CERN Programs Tutorial Book
2. ROOT CERN Programs Tutorial Book
3. Introduction to Command Line, The Fat-Free guide to Unix and Linux Commands, Nicholas Marsh

Supplementary Book(s):
1. Gerhard Bohm, Günter Zech (2010), Introduction to Statistics and Data Analysis for Physicists, Wiley, New York.
2. Les Kirkup (2002). Data Analysis with Excel: An Introduction for Physical Scientist, Cambridge University Press, London.

Materials: 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 1 MIDTERM EXAM 1
2 MTE 2 MIDTERM EXAM 2
3 LAB LABORATORY
4 FIN FINAL EXAM
5 FCGR FINAL COURSE GRADE (RESIT) MTE1 * 50 / 300 + MTE2 * 50 / 300 + LAB * 50 / 300 + FIN * 0.50
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE1 * 50 / 300 + MTE2 * 50 / 300 + LAB * 50 / 300 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

1. Midterm exams and assignments are taken as the achievements of students for the semester.
2. Final exam will be added to the success of the study of midterms and assignments, thereby the student's success will be determined

Language of Instruction

Turkish

Course Policies and Rules

1. 70% of the participation of classes is mandatory.
2. Students, who do not participate in Midterm exams and not do regular assignments, are not allowed to enter the final exam.
3. Every trial of cheating will be punished according to disciplinary proceedings.
4. Faculty reserves the right to make practical exam. This exam will be taken from the notes will be added to the midterm and final exam grades.

Contact Details for the Lecturer(s)

muhammed.deniz@deu.edu.tr

Office Hours

Monday at 09: 00 - 12: 00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Tutorials 12 2 24
Preparations before/after weekly lectures 24 4 96
Preparation for midterm exam 2 4 8
Preparation for final exam 1 4 4
Preparing assignments 10 2 20
Midterm 2 3 6
Final 1 3 3
TOTAL WORKLOAD (hours) 185

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.12555
LO.22555
LO.32555
LO.45555
LO.55555