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Movie box office data that is current and very comprehensive. Several different trends are easy to track including exponential, and log functions. Great for using with students to create regression models, making predictions based on the models, checking the results and re-analyzing. Also, when a movie doesn't follow the predictions there are often easy to understand reasons for why the movies behave differently (a holiday weekend may cause the movie to gross more on a given weekend than predicted, etc.)

Want to let students explore with real data then welcome to FRED® (Federal Reserve Economic Data), a database of 25,176 U.S. economic time series. With FRED® you can download data in Microsoft Excel and text formats and view charts of data series. Students can explore data, create models & hypothesis, and test their models as the year progresses. If their models aren't working they can go back to their original data set and make changes based on what they've learned and see how those predictions work on new data. The best part is the variety of data that is available.  We plan to continually improve FRED® and encourage you to send feedback through our contact form.

From the abstract (full text requires subscription): "Many organisms can predict future events from the statistics of past experience, but humans also excel at making predictions by pure reasoning: integrating multiple sources of information, guided by abstract knowledge, to form rational expectations about novel situations, never directly experienced. Here, we show that this reasoning is surprisingly rich, powerful, and coherent even in preverbal infants. When 12-month-old infants view complex displays of multiple moving objects, they form time-varying expectations about future events that are a systematic and rational function of several stimulus variables. Infants' looking times are consistent with a Bayesian ideal observer embodying abstract principles of object motion. The model explains infants' statistical expectations and classic qualitative findings about object cognition in younger babies, not originally viewed as probabilistic inferences."

Northwestern University scientists created a model to explore food web dynamics towards species conservation. "The goal of this project, funded by the National Science Foundation's Division of Mathematical Sciences, is to develop mathematical methods to study dynamical processes in complex networks. Although the specific application mentioned here may be useful in management of ecosystems, the mathematical foundation underlying the analysis is much more universal. The broad concept is innovative in the area of complex networks because it concludes that large-scale failures can be avoided by focusing on preventing the waves of failure that follow the initial event."

Scheduled for December, Predictive Interface and Units, Social Networks and Data Science, and Data Manipulation and Visualization

"If a 6-month-old can distinguish between 20 dots and 10 dots, she's more likely to be a good at math in preschool. That's the conclusion of a new study, which finds that part of our proficiency at addition and subtraction may simply be something we're born with."