A Simple Django Web App Django is a popular web framework for python. Like other web frameworks, the purpose of Django is to help you build websites without the challenge of building everything from scratch. The purpose of this post is to get a minimally, just about useful, app working rather than demonstrating all of… Read More »
Markov chains are a way of stochastically modelling a series of events where the outcome probability of an event depends only only on the event that preceded it. This post gives an overview of some of the theory of Markov chains and gives a simple example implementation using python. Using Markov Chains to Model The… Read More »
Monto Carlo simulation is a technique for approximating future behaviour based on randomly sampled numbers. By sampling from different probability distributions it is possible to use Monte Carlo simulation for a range of different situations including physical systems, computer games or finance. This post gives a simple example of Monte Carlo simulation to give some… Read More »
Monte Carlo integration uses random numbers to approximate the solutions to integrals. While not as sophisticated as some other numerical integration techniques, Monte Carlo integration is still a valuable tool to have in your toolbox. Monte Carlo integration is one type of Monte Carlo method – a family of techniques which use randomly generated numbers… Read More »
Confidence intervals are the range often provided alongside other statistics. As their name suggests, they somehow convey a degree of uncertainty in the statistic quoted, but what actually are confidence intervals? And how can we get an intuitive understanding of them? This post goes into some of the theory behind confidence intervals and points you… Read More »