Applied Statistics - Week 7

Monday the 10th - Friday the 14th of January 2022

The following is a description of what we will go through during this week of the course. The chapter references and computer exercises are considered read, understood, and solved by the beginning of the following class, where I'll shortly go through the exercise solution.

General notes, links, and comments:


  • Monday:
    The subject of the day will be fitting, moving towards advanced cases of fitting. As stated, fitting is a bit of an artform, and there is little literature on the subject - only (bitter?) experience! I've tried my best in the reading list below.
    Reading:
  • Possibly Barlow page 184, section 10.2.2.
  • Possibly Cowan page 65.
  • Possibly Bevington chapters 6-8 (best of the three!).
    Lecture(s):
  • Advanced Fitting
    Zoom:
  • Link to lecture. Recording of Lecture video.
  • Link to exercises.
    Computer Exercise(s):
  • Advanced fitting: FitAndTestingDistributions_original.ipynb

    Tuesday:
    The day will focus on calibration, which is a subtle subject, yet fairly straight forward, once you get the hang of the idea. The associated exercise is inspired by typical data analysis work.

    Reading:
  • No reading - logic and reason suffices.
    Lecture(s):
  • Calibration
  • Trial Factor
    Zoom:
  • Link to lecture. Recording of Lecture video.
  • Link to exercises.
    Computer Exercise(s):
  • Calibration: Calibration_original.ipynb
  • Calibration data file: data_calib.txt

    Friday:
    The lecture will be a relatively thorough walk through the Problem Set. I'll go each problem, and discuss the solution. From this, we hope that our grading becomes clear.
    In the exercises, we'll try a simple example of doing integration in many dimensions using simple simulation. First, it is the estimate of pi, followed by the rational numbers in front of (hyper) volumes of balls in many dimensions!
    Reading:
  • A good introduction is in actually Wikipedia on Monte Carlo simulations.
    Lecture(s):
  • Problem Set - Solutions, Comments, and Scores.
    Zoom:
  • Link to lecture. Recording of Lecture video 1 and Lecture video 2.
  • Link to exercises.
    Computer Exercise(s):
  • Estimating pi and hypersphere size from simulation: PiEstimate_original.ipynb
    Last updated: 14th of January 2022.