Statistical Data Analysis

6 EC

Semester 1, period 1

5354STDA6Y

Owner Master Physics and Astronomy (joint degree)
Coordinator dr. H.L. Snoek
Part of Master Astronomy and Astrophysics, track GRAPPA/Astro, year 1Master Physics and Astronomy, track GRAPPA, year 1

Course manual 2017/2018

Study materials

Other

  • Lecture notes.

Objectives

The purpose of this course is to present the basic mathematical and computational tools needed for the statistical analysis of experimental data. The methods will be practiced by writing and running short computer programs.

Teaching methods

  • Supervision/feedback meeting

Tutorial.

Learning activities

Activity

Number of hours

Hoorcollege

3

Tentamen

3

Werkcollege

 53

Zelfstudie

109

Attendance

Requirements concerning attendance (OER-B).

  • In addition to, or instead of, classes in the form of lectures, the elements of the master’s examination programme often include a practical component as defined in article 1.2 of part A. The course catalogue contains information on the types of classes in each part of the programme. Attendance during practical components is mandatory.

    • Additional requirements for this course:

    Afwezigheid dient gemeld te worden bij de coördinator.

    Assessment

    Item and weight Details

    Final grade

    1 (100%)

    Tentamen

    Een rekenmachine en een schone syllabus (zonder aantekeningen) mogen worden gebruikt tijdens het tentamen.

    Assignments

    There are 7 computer exercises. The students have to hand in a short report and the analysis code. Both are assessed.

    Root1: First analysis of a dataset. Simple exercise to learn the programming environment.
    Root2: Error Calculation. Compute errors using covariant matrix.
    Root3: Law of large numbers. Evaluate difference between mean and median.
    Root4: Central limit theorem. Calculate statistical properties (average/RMS/SD).
    Root5: Cosmic rays. Monte Carlo techniques at work.
    Root6: Maximum Likelihood. Perform a maximum likelihood fit.
    Root7: Bump hunting. Hypothesis testing/p-value.

    Fraud and plagiarism

    The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

    Course structure

    Weeknummer Onderwerpen Studiestof Deadline
    1 Introductie/Probability Ch1/Ch2 ROOT1
    2 Random variables Ch3. ROOT2
    3 Distributions/Gaussian distributions Ch4/5 ROOT3
    4 Monte Carlo simulations Ch6 ROOT4
    5 Parameter estimation Ch7 ROOT5
    6 Maximum likelihood method and Hypothesis testing ch8/ch9 ROOT6
    7 Hypothesis testing and recap ch9 ROOT7
    8 tentamen syllabus  

    Timetable

    The schedule for this course is published on DataNose.

    Contact information

    Coordinator

    • dr. H.L. Snoek

    dr. A.H. Heijboer