Here's the AP Statistics course page for instructors: https://apcentral.collegeboard.org/courses/ap-statistics
https://en.wikipedia.org/wiki/AP_Statistics It's probably worth mentioning nbgrader for grading notebooks and nbval for testing notebooks: https://github.com/jupyter/nbgrader https://github.com/computationalmodelling/nbval On Friday, February 23, 2018, Wes Turner <wes.tur...@gmail.com> wrote: > > > On Friday, February 23, 2018, Blake <blakeel...@gmail.com> wrote: > >> The programs / code examples you all have proposed look great. >> >> Perry, I think your idea to teach Bayesian statistics to 6-8th graders >> sounds great! >> >> Just wanted to chime in on a different angle of this: the relevance of >> the problem(s) that you address. >> >> Here is a video of one of my former high school teachers explaining how >> he teaches reasoning, skepticism, and using probability in the real world. >> https://www.youtube.com/watch?v=z2HWE6qQ2kI >> >> He gives an example of using Bayes Rule which could be a great example >> for you to use, Perry. And he shows how you can intuitively, visually >> understand what Bayes Rule tells us for that example, without having to go >> through the calculations. >> >> >> At the end of that video, he gives a curriculum overview for a year-long >> course he has developed, called "Human Reasoning", which is about thinking >> in the real world. I would love to see more people teach the way he does! >> >> >> Curious if people have other examples of this kind of thing, or have >> ideas of how to use computer simulations specifically for teaching this >> real-world-focused perspective on mathematics. >> > > https://www.khanacademy.org/math/statistics-probability > > https://github.com/jupyter/jupyter/wiki/a-gallery-of- > interesting-jupyter-notebooks#machine-learning-statistics-and-probability > > http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian- > Methods-for-Hackers/ > > > >> >> >> -- >> Blake Elias >> >> On Fri, Feb 23, 2018 at 2:44 PM, Wes Turner <wes.tur...@gmail.com> wrote: >> >>> "Seeing Theory: A visual introduction to probability and statistics" >>> http://students.brown.edu/seeing-theory/ >>> https://github.com/seeingtheory/Seeing-Theory >>> >>> These are JavaScript widgets, so not Python but great visual examples >>> that could be implemented with ipywidgets and some JS. >>> >>> explorable.es has a whole catalog of these: >>> http://explorabl.es/math/ >>> >>> Think Stats 2nd edition is free: >>> http://greenteapress.com/wp/think-stats-2e/ >>> >>> The source is also free: >>> https://github.com/AllenDowney/ThinkStats2 >>> https://github.com/AllenDowney/ThinkStats2/blob/master/code/ >>> chap01ex.ipynb >>> https://nbviewer.jupyter.org/github/AllenDowney/ThinkStats2/ >>> tree/master/code/ >>> >>> >>> On Friday, February 23, 2018, kirby urner <kirby.ur...@gmail.com> wrote: >>> >>>> I'm a big fan of Galton Boards: >>>> >>>> https://youtu.be/3m4bxse2JEQ (lots more on Youtube) >>>> >>>> Python + Dice idea = Simple Code >>>> >>>> http://www.pythonforbeginners.com/code-snippets-source-code/ >>>> game-rolling-the-dice/ >>>> >>>> I'd introduce the idea that 1 die = Uniform Probability but 2+ dice = >>>> Binomial distribution (because there are more ways to roll some numbers, >>>> e.g. 7 than others, e.g. 12). >>>> >>>> A Python generator for Pascal's Triangle (= Binomial Distribution): >>>> >>>> def pascal(): >>>> row = [1] >>>> while True: >>>> yield row >>>> row = [i+j for i,j in zip([0]+row, row+[0])] >>>> >>>> >>>> gen = pascal() >>>> >>>> for _ in range(10): >>>> print(next(gen)) >>>> >>>> [1] >>>> [1, 1] >>>> [1, 2, 1] >>>> [1, 3, 3, 1] >>>> [1, 4, 6, 4, 1] >>>> [1, 5, 10, 10, 5, 1] >>>> [1, 6, 15, 20, 15, 6, 1] >>>> [1, 7, 21, 35, 35, 21, 7, 1] >>>> [1, 8, 28, 56, 70, 56, 28, 8, 1] >>>> [1, 9, 36, 84, 126, 126, 84, 36, 9, 1] >>>> >>>> Kirby >>>> >>>> >>>> On Tue, Feb 20, 2018 at 6:12 PM, Perry Grossman < >>>> perrygrossman2...@gmail.com> wrote: >>>> >>>>> 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 >>>>> >>>>> 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-s >>>>>> chool-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 >>>>>> *************************************** >>>>>> >>>>> >>>>> _______________________________________________ >>>>> Edu-sig mailing list >>>>> Edu-sig@python.org >>>>> https://mail.python.org/mailman/listinfo/edu-sig >>>>> >>>>> >>>> >>> _______________________________________________ >>> Edu-sig mailing list >>> Edu-sig@python.org >>> https://mail.python.org/mailman/listinfo/edu-sig >>> >>> >>
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