This paper begins with an overview of quantum mechanics, and then recounts a relatively recent algebraic extension of the Boolean algebra of probabilistic events to “conditional events” (order pairs ...

The probability that a tennis player wins the first set of a match is \(\frac{3}{5}\). If she wins the first set, the probability that she wins the second set is \(\frac{9}{10}\). If she loses the ...

We elaborate on an alternative representation of conditional probability to the usual tree diagram. We term the representation “turtleback diagram” for its resemblance to the pattern on turtle shells.

We investigated the effects of probability on visual search. Previous work has shown that people can utilize spatial and sequential probability information to improve target detection. We hypothesized ...

The iQRM Warm-Ups are short, half hour sessions that review the basics covered in iQRM. This is a tour of the foundational math without application. The seminar covers probability, the normal ...

You'll need to set up some parameters for the model to work with. These include the number of samples, learning rate, data type, and more. Define the conditional events and end states for your model.

Author: Chris Boucher (March 2011). This app displays an intricate Venn diagram, containing various combinations of set intersections, unions and complements. Users can shade the area they choose by ...

The probability that a tennis player wins the first set of a match is \(\frac{3}{5}\). If she wins the first set, the probability that she wins the second set is \(\frac{9}{10}\). If she loses the ...