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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 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
PCA
Bootstrap and Jackknife methods
Bayesian statistics
Monte-Carlo methods
Dealing with statistical and systematic uncertainties
Advanced and numerical methods
Required Reading:
None
Additional Reading Material:
None
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
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