One of my earliest code from scratch efforts was as an undergraduate engineering student at The University of Texas, Austin.
I was taking probability and statistics. Personal computers were VERY rare. I used campus computers OR a programmable calculator.
I loved my HP Programmable calculator.
I will confess that I struggled to appreciate the more conceptual points of probability and statistics - WAIT! I still struggle with them! But at least those struggles are at deeper conceptual levels now.
If you ever hear ANYONE say that data scientists don't need to know much statistics, ... well, let me just say, IF you want to be a really good data scientist, keep fighting to understand probability and statistics MO BETTUH!
How do you start toward that goal?
I’d like to help you. First, go to my Statistics_with_Python repo on DagsHub. Find the tritium of files called named “Mean_STD_PDF_CDF_with_Python” - you can choose ipynb (notebook), html, or PDF formats.
Those files work toward integrating PDFs (Probability Distribution Functions) to calculate your own CDF.
This is what I programmed into that old and powerful HP programmable calculator, and that was one of the PIVOTAL exercises that helped me to understand probability and statistics a lot better AND to appreciate the value of code from scratch exercises.
PLEASE work through the notebook, html, or PDF yourself, and make it better for you!
I hope this helps many of you a ton!
Until next time,
Thom
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