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    # Introduction to Data Analysis with Python

    ### Prabhu Ramachandran
    ### The FOSSEE Python group &
    ### Department of Aerospace Engineering
    ### IIT Bombay

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    ## Introduction

    - A world of data!

    - Can we use data to drive decisions and form opinions?

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    ## Real data is not perfect

    - Partial information
    - Uncertainty
    - Errors
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    - Important to check and clean data

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    ## Statistical approach

    - Data collection

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    - Visualization
    - Inference
    - Modeling
    - Prediction

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    ## Importance of computers

    - Datasets are large
    - Easy to process on the computer
    - Simulation!

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    ## This course

    - Use Python for data analysis
    - Exposes you to the basic tools available
    - Does not teach you statistics!
    - Will point out resources for this

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    ## Pre-requisites

    - Basic Python programming
    - `numpy`
    - Python 3.x, `Jupyter, scipy, matplotlib, pandas, statsmodels`

    - Mathematics (12th grade)
    - Introduction to statistics


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    ## Tools and Topics

    - Simple statistics with `numpy`
    - Statistical plots with `matplotlib`
    - Random variables with `scipy.stats`
    - Using `pandas` for data ingestion and analysis
    - Introduction to `statsmodel` for regression


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    ## Resources for learning

    - [Khan Academy Statistics and Probability](https://www.khanacademy.org/math/statistics-probability)
    - [Concrete introduction to Probability](http://nbviewer.jupyter.org/url/norvig.com/ipython/Probability.ipynb) by Peter Norvig

    - [Penn State Stat 414 course](https://onlinecourses.science.psu.edu/stat414)

    - [Computational and Inferential Thinking](https://www.inferentialthinking.com/) by Ani Adhikari and John De Nero

    - [Think Stats2](http://greenteapress.com/wp/think-stats-2e/) by Allen B. Downey

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    ## Summary

    - Introduction to data analysis
    - Pre-requisites for this course
    - Tools covered
    - Resources for statistics and probability

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