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Syllabus Advanced Data Analysis - 77742
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Last update 16-08-2018
HU Credits: 4

Degree/Cycle: 2nd degree (Master)

Responsible Department: Physics

Semester: 1st Semester

Teaching Languages: English

Campus: E. Safra

Course/Module Coordinator: Dr. Assaf Horesh

Coordinator Email:

Coordinator Office Hours: by appointment

Teaching Staff:
Dr. Assaf Horesh

Course/Module description:
The class will teach advanced methods of analyzing experimental and observational data and will introduce the relevant statistical and numerical tools

Course/Module aims:
To teach advanced methods of data analysis

Learning outcomes - On successful completion of this module, students should be able to:
1. Calculation of prob. distributions and fitting to experimental data including noise and systematics
2. Fitting and analsis of BIG DATA
3. Applying Baysian analysis
4. Using Monte-Carlo integration
5. Analyze dynamical multi-scale time series
6. Multi dimensional stochasic optimization

Attendance requirements(%):

Teaching arrangement and method of instruction: Lectures

Course/Module Content:
Intro to data analysis
Probability distributions
Generating functions, moments, and central moments
Covariance and correlation matrices
Fitting and hypothesis testing
Bootstrap and Jackknife methods
Bayesian statistics
Monte-Carlo methods
Dealing with statistical and systematic uncertainties
Advanced and numerical methods

Required Reading:

Additional Reading Material:

Course/Module evaluation:
End of year written/oral examination 0 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 100 %
Assignments 0 %
Reports 0 %
Research project 0 %
Quizzes 0 %
Other 0 %

Additional information:
open for third year students, by approval
Students needing academic accommodations based on a disability should contact the Center for Diagnosis and Support of Students with Learning Disabilities, or the Office for Students with Disabilities, as early as possible, to discuss and coordinate accommodations, based on relevant documentation.
For further information, please visit the site of the Dean of Students Office.