I am thinking of doing a simplified interactive presentation on probability and Bayesian statistics for my kids' elementary school. I think it would probably be best for 6-8th graders, but there might be ways to do this for younger students. I'd like to run some Python code to show probability distributions and statistics.
I am thinking of simplified examples from these works: Maybe the dice problem, or the cookie problem here: Allen Downey - Bayesian statistics made simple - PyCon 2016 <https://youtu.be/TpgiFIGXcT4?t=1741> A friend also suggested doing an analysis of how many cards (e.g. pokemon) that one might need to buy to colleft the whole set. Any suggestions on how to make this manageable approachable for kids? Perry On Feb 20, 2018 12:02 PM, <edu-sig-requ...@python.org> wrote: > Send Edu-sig mailing list submissions to > edu-sig@python.org > > To subscribe or unsubscribe via the World Wide Web, visit > https://mail.python.org/mailman/listinfo/edu-sig > or, via email, send a message with subject or body 'help' to > edu-sig-requ...@python.org > > You can reach the person managing the list at > edu-sig-ow...@python.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Edu-sig digest..." > > > Today's Topics: > > 1. if I taught high school calculus today... (kirby urner) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Mon, 19 Feb 2018 19:50:28 -0800 > From: kirby urner <kirby.ur...@gmail.com> > To: "edu-sig@python.org" <edu-sig@python.org> > Subject: [Edu-sig] if I taught high school calculus today... > Message-ID: > <capjgg3q5xvmssiwafnsq928eiygkyi7xmmqibsi4fm9-1_h...@mail.gm > ail.com> > Content-Type: text/plain; charset="utf-8" > > I was a high school calculus teacher (also algebra, geometry, trig) first > job outta university, stuck with it for two years. > > Fast forward to almost age 60, and I'm teaching coding to middle schoolers, > thinking it's all still math. [1] > > Shouldn't take a "computer scientist" to cover this stuff... Algorithms are > algorithms after all. > > Were I to teach calculus today, in light of what I now know, I'd focus on > probability density functions right when we get to integration, as "area > under the probability curve" is precisely how we figure out chances of > something happening. > > We would use Jupyter Notebooks with SciPy, all free & open source. > > As I recall, our calc curriculum never did much to bridge to statistics, > but in SciPy / NumPy, every continuous probability distribution function > (PDF) comes with a cumulative distribution function (CDF) that's defined > exactly as a definite integral between A and B, and giving the probability > some x in distribution X falls between A and B. > > Forming a bridge twixt calculus and data science would be another strategy > for getting scientific calculators to share the road, with more relevant > free tools (always an ulterior motive for me). I don't think a TI is able > to do definite integration over a standard normal curve. > > Actually, I see I'm wrong: > http://cfcc.edu/faculty/cmoore/TINormal.htm > > Oh well, back to the drawing board. I still think a strong tie-in twixt > calc and data science makes a lot of sense at the high school level. With > or without Jupyter Notebooks. > > Kirby > > PS: right now I'm going through Allen Downey's tutorial on Bayesian stats > using the above mentioned tools, from Pycon 2016: > https://youtu.be/TpgiFIGXcT4 > I attended this conference, but didn't manage to make this tutorial. > > [1] I've shared this before, still relevant: > https://medium.com/@kirbyurner/is-code-school-the-new-high- > school-30a8874170b > > Also this blog post: > http://mybizmo.blogspot.com/2018/02/magic-squares.html > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: <http://mail.python.org/pipermail/edu-sig/attachments/201802 > 19/d9e2f965/attachment-0001.html> > > ------------------------------ > > Subject: Digest Footer > > _______________________________________________ > Edu-sig mailing list > Edu-sig@python.org > https://mail.python.org/mailman/listinfo/edu-sig > > > ------------------------------ > > End of Edu-sig Digest, Vol 174, Issue 1 > *************************************** >
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