OK, so my intentions for this blog were to primarily focus on software development, but so far I've only posted articles on probabilities - the Monty Hall Problem and the Birthday Paradox. Probability theory, however, has many direct applications in computer science. The Birthday Paradox for example, can be used to showcase the basic principles of hashing algorithms. The Monty Hall problem is a great way to understand the concept of an expected value - a value you'd expect to see after running a process over and over. Expected values are used to define the average case complexities of algorithmsAnyway, this Scientific American article offers some speculations about why most of us don't intuitively understand probabilities, and perhaps sheds some light on why problems like those mentioned above can be so bewildering. The article's argument boils down to the idea that we live in the "now", that our brains are hardwired to easily handle only a small number of event occurrences. When we come up against large sets of values, we have a tendency to focus in on its subsets or singular values, which obscures the connections that exist between the set's members.
A very interesting (and short) read...
