darshanbeniwal / Exploring_Astro_Data_w_Py_GLA_IUCAA_2023

This repository contains files related to the Python programming workshop conducted for astrophysics and cosmology work at GLA-Mathura. The repository includes sample codes, datasets, and presentations used during the workshop. These materials can be useful for beginners who want to learn Python programming for astrophysics and cosmology work.

[Three Days Workshop on Python Programming in Astronomy, Astrophysics & Cosmology]

Organized by Centre for Cosmology, Astrophysics and Space Science, CCASS, GLA Mathura

Funded by Inter-University Centre for Astronomy and Astrophysics (IUCAA)

I was among the invited speakers, along with Prof S. N. Hasan , Prof Priya Hasan, and Dr. Akshay Rana and in this repository, I have included all the files, including the data file and Python notebook, that were covered in two lecture+Hands-on sessions by me.

• Lecture-Sessions

  • Introduction to Statistics
  • Maximum Likelihood Estimator (MLE)
  • Minimum Chi-square Test
  • Bayesian Statistics

• Hands-on Sessions

  • Linear Model Fitting with Mock Data Using Basic Code: A Tutorial
  • Linear Model Fitting with Mock Data Using lmfit

References for Further Reading

• Basics of Statistics

  • Introduction To Error Analysis by J. R. Taylor 🔗
  • Data analysis: a Bayesian tutorial by Devinderjit Sivia and John Skilling 🔗
  • Data Reduction and Error Analysis for the Physical Sciences by P. R. Bevington and D. K. Robinson 🔗

• Statistical Cosmology

  • Statistical methods in cosmology by L. Verde 🔗
  • Statistical methods for cosmological parameter selection and estimation by A. R. Liddle 🔗
  • Bayesian Methods in Cosmology by R. Trotta 🔗

Contact Email: [e-mail]

Copyright

© Darshan Kumar Beniwal, University of Delhi, 2023, Presented at Centre for Cosmology, Astrophysics and Space Science, GLA Mathura.