As the name of repository suggest, this repository contains notebook files that displays the code and its result of statistical simulation.
There are 2 notebooks here:
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one of them is about how to find the maximum likelihood estimate. https://nbviewer.jupyter.org/github/Nevermetyou65/When-I-code-to-do-statistics-for-the-first-time/blob/main/Simulation%20Maximum%20likelihood.ipynb
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another one shows you how to determine the estimate, credible interval and conducting hypotheses testing in Bayasian way. https://nbviewer.jupyter.org/github/Nevermetyou65/When-I-code-to-do-statistics-for-the-first-time/blob/main/Simulation%20Bayesian%20%28basic%29.ipynb
As part of my hobbies, I just try to simulate things instead of doing it mathematically. So, what in repository is nothing new to the world. But this is my own way of encouraging myself to study both coding and statistics in the same time.:yum:
Originally, the content in the notebook -also the method that I used- is a part of my homework assignment when I was studying statistical inference class, at chulalongkorn university. The creator of the problem exercises and the algorithm you see in the notebooks is Asst. Prof. Anupap Somboonsavatdee who showed me how to code the simulation in R and taught me what statistic really is.
The code is entirely written in Python 3.8.5 and the main packages I utilized are:
- numpy 1.19.2
- scipy 1.5.2
- matplotlib 3.3.2