Learner.org Math Resources

Learner.org has an interesting series called: Math Illuminated

There are also a wide variety of other materials available, tailored to specific age groups:
http://www.learner.org/resources/browse.html?discipline=5&grade=0&imageField2.x=3&imageField2.y=11

About Learner.org

Annenberg Learner uses media and telecommunications to advance excellent teaching in American schools. This mandate is carried out chiefly by the funding and broad distribution of educational video programs with coordinated Web and print materials for the professional development of K-12 teachers. It is part of The Annenberg Foundation and advances the Foundation's goal of encouraging the development of more effective ways to share ideas and knowledge.

RStudio - Shiny

http://www.rstudio.com/shiny/

Shiny makes it super simple for R users like you to turn analyses into interactive web applications that anyone can use. Let your users choose input parameters using friendly controls like sliders, drop-downs, and text fields. Easily incorporate any number of outputs like plots, tables, and summaries.

No HTML or JavaScript knowledge is necessary. If you have some experience with R, you're just minutes away from combining the statistical power of R with the simplicity of a web page.

Blaze - next generation NumPy

https://speakerdeck.com/sdiehl/blaze-next-generation-numpy

Why One Statistician Buys Lottery Tickets

David Wood's discussion of the probabilities of buying lottery tickets is an entertaining read:

http://simplexify.net/blog/2012/5/6/i-am-a-statistician-and-i-buy-lottery-tickets.html

"The decision of whether to buy a lottery ticket shouldn’t be based on the probability of winning, or the expected return of a ticket, but on the entertainment value that comes from imagining a different life. If that entertainment value compares favourably with other activities with a similar price, then go for it. Plus, it has the added bonus that you might actually win; one-in-a-million events happen every day. Someone eventually wins the big prize, and you have to be in to win" - David Woods

Julia Language

Here's an interesting language for mathematical endeavors
http://julialang.org/

hat'tip to Paul Snively@psnively


From the Julia blog:

Julia is a dynamic language in the tradition of Lisp, Perl, Python and Ruby. It aims to advance expressiveness and convenience for scientific and technical computing beyond that of environments like Matlab and NumPy, while simultaneously closing the performance gap with compiled languages like C, C++, Fortran and Java.
Most high-performance dynamic language implementations have taken an existing interpreted language and worked to accelerate its execution. In creating Julia, we have reconsidered the basic language design, taking into account the capabilities of modern JIT compilers and the specific needs of technical computing. Our design includes:

• Multiple dispatch as the core language paradigm.
• Exposing a sophisticated type system including parametric dependent types.
• Dynamic type inference to generate fast code from programs with no declarations.
• Aggressive specialization of generated code for types encountered at run-time.

Julia feels light and natural for data exploration and algorithm prototyping, but has performance that lets you deploy your prototypes.

Funny: If the IRS had discovered the quadratic formula . . .

http://www.cs.amherst.edu/~djv/irs.pdf

Allen Downey

Allen Downey is a professor of Computer Science at Olin College in Needham MA
http://sites.google.com/site/allendowney/

He writes an interesting blog focused on probability and statistics problems: 
http://allendowney.blogspot.com

He's also the author of a book:
Probability and Statistics for Programmers
which is published by O'Reilly
http://greenteapress.com/thinkstats/

and also available under the Creative Commons 3.0 license as a PDF: http://greenteapress.com/thinkstats/thinkstats.pdf