When I wanted to study statistics, I used to do courses and learnt the formal way. But after spending hours and hours of watching lectures and solving exercises, all I am left with are the pieces of scribbles in notebooks. So, I tried to apply those concepts in real datasets and scenerios.
IPython notebooks are the perfect tool to writedown notes and play around with codes at the same time. So, this repository is my humble attempt to note down my understanding of the statistical concepts while applying them on realworld datasets.
The way this repository is organized is the topics are put into separate folders. Each folder contains all the notebooks, related files and documents for a particular topic.
I highly recommend you to clone the repository and run the notebooks yourself rather than just passively reading.
Steps to run the notebooks:
- Clone the repository
- Create a Python environment using Conda or Python venv
- Install Jupyter notebook
- Install the requirements from requirements.txt file
- Download the datasets from the links provided
- Open the notebook and run the cells
Or you can upload the notebooks to Google Colab and run there.
Currently, the following concepts are provided:
- Summary Statistics
- Hypothesis Testing
more to come as I learn more and more topics.
Datasets used in this repository are publically available datasets under public domain licenses as of the time I implemented the notebook.