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Essential Statistics for Data Science

Welcome to "Essential Statistics for Data Science" – a collection of notes on fundamental statistics for experimental sciences and data science enthusiasts. These notes are particularly beneficial for those embarking on a career in data science. The content of these notes has evolved through teaching, discussions, and supervision of experiments.

Books Used

The following four books have been extensively referenced and used during the creation of these lecture notes:

  1. Introductory Statistics

    • Author: S. M. Ross
    • Year: 2017
    • Publisher: Academic Press

  2. Introduction to Probability and Statistics for Engineers and Scientists

    • Author: S. M. Ross
    • Year: 2020
    • Publisher: Academic Press

  3. Probability and Statistics for Engineers and Scientists

    • Authors: R. E. Walpole, R. H. Myers, S. L. Myers, K. Ye
    • Year: 1993
    • Publisher: Macmillan New York

  4. Introductory Statistics

    • Authors: N. A. Weiss, C. A. Weiss
    • Year: 2017
    • Publisher: Pearson London

Workflow Details

The workflow consists of the following steps:

  1. Set up Git repository: This step checks out the repository on the GitHub Actions runner.

  2. Compile LaTeX document: The LaTeX document (specified as main.tex in the workflow) is compiled into a PDF using the GitHub Action for LaTeX. The resulting PDF is then saved as an artifact.

  3. Upload PDF file: The compiled PDF file is uploaded as an artifact, making it accessible for further use or manual download.

Usage

LaTeX to PDF Conversion with GitHub Actions

This repository includes an automated workflow that converts a LaTeX document to a PDF using GitHub Actions. The workflow is triggered on each push to the main branch, ensuring that the PDF is always up-to-date with the latest changes to the LaTeX document.

To compile the LaTeX document and generate the PDF locally, you can follow these steps:

  1. Clone the repository:

    git clone [repository-url]

  2. cd [EssentialStatistics]