In the recent months while taking a course in statistics and signal processing I built a handful of visualizations in order demonstrate some of the basic but important concepts I (re)learned.<p>I already posted a link to the fourier transform visualization a month ago. [1] Since then I worked on some more tools some of you might find helpful or interesting:<p>- visual proof of Bayes Theorem<p>- visualization how parameters of a gaussian distribution can be estimated<p>- interactive binary hypothesis test<p>- effect of a function on a random variable<p>The tools are not meant to give a fullblown introduction on the topics but more to deepen your intuition while learning from other sources or at least having already heard about the underlying concepts. But the visual and interactive concept of the tools might even allow to discover the core ideas and relations by yourself.<p>The section "Other Educational Tools" is older stuff that I included because it might be interesting as well.<p>All the code is on Github but it's really hacked together and not polished to be read by others. [2]<p>[1]: <a href="https://news.ycombinator.com/item?id=29455894" rel="nofollow">https://news.ycombinator.com/item?id=29455894</a><p>[2]: <a href="https://github.com/laszlokorte" rel="nofollow">https://github.com/laszlokorte</a>
Thanks for sharing these!<p>IMO, they'd be much more helpful/accessible with some default examples. For example, the graph algorithm and logic expression tools just drop you into a blank canvas.