Corbanez97 / statistical-inference-snia

Statistics and Data Analysis - Theory and Practical Applications

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A Course in Statistics and Data Analysis

An introductory course in statistics and data analysis. From theory to practical applications.

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Table of Contents

General Information

This is an introductory course in statistics and data analysis. All you need to follow this course is calculus, linear algebra, and some knowledge of Python.

The Practical Data Analysis.ipynb notebook contains a compendium of information on statistics. From basic definitions to complex theorems. This main notebook is divided into lessons. If needed, another notebook or document will be listed for further studies (Sampler.ipynb and usefull_proofs.xopp for instance).

Furthermore, there are some practice exercises for each lesson. The solutions for these exercises are presented in the Assigment1.ipynb and Supernovae.ipynb.

Technologies Used

  • Python 3.10
  • Jupyter Notebooks

Features

This repository currently has:

  • Statistics studies notebook;
  • Exercises with solutions;
  • Module with basic functions created from scratch;
  • Inverse Transform Sampler.

Screenshots

Central Limit

Interpolation

Setup

Modules required for this course are listed in the requirements.txt file. To set up your machine, execute the following in the command line:

pip install -r requirements.txt

Acknowledgements

This is based on the course created by Prof. Sandro Vitenti. This is simply a guideline of studies.

Contact

Created by Lucas Corbanez - feel free to contact me!

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Statistics and Data Analysis - Theory and Practical Applications


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Language:Jupyter Notebook 99.3%Language:Python 0.7%