An implementation in Python, Monte Carlo simulations encompass a broad range of algorithms that make use of statistical sampling to obtain useful information about something which is random in nature. A perfect example of this is the simulation of stock prices using stochastic models, which often require the numerical solution…

When people hear the name “Albert Einstein”, the first thing that comes to mind is the equation E = mc². Of course, this was made very popular back in the 1900s as it related to many more discoveries that would be made in that century, most notably things like nuclear…

Done from scratch using less than 200 lines of code. The other day I was working with some Python and functions, and it occurred to me that it would be a fun task to program a Connect-4 game from scratch using a few functions and a data structure known as…

A guide using simple Python code. In my previous story (https://oscarnieves100.medium.com/simulating-correlated-random-variables-in-python-c3947f2dbb10) I discussed how to simulate correlated random numbers from a normal probability distribution. We focused on a normal distribution because it is well known, and standard methods of sampling exist. But what if you wanted to create your own…

In my previous Medium story (https://oscarnieves100.medium.com/simulating-normal-random-numbers-in-python-18a2a21a1329) I discussed how to simulate normal random numbers with specific mean and variance properties by using something called the Box-Muller method. …

Using the Box-Muller method In my previous Medium story: https://oscarnieves100.medium.com/how-to-simulate-random-numbers-dad35905ecdb I discussed how to simulate random numbers in Python by using a little mathematical method known as “the inverse sampling theorem”. In it, I demonstrated how using nothing but uniformly distributed random numbers in the interval [0, 1] we could…

A gentle introduction Random numbers are used in a lot of applications. They are more predominantly used in areas like statistics, probability theory, data science, signal processing, statistical physics, machine learning, actuarial science, quantitative finance, and more. …

Overview Students of science and engineering often only learn a bit of Excel in the context of doing simple data analysis, plotting and calculations involving single cells or scalar values (e.g. basic statistics). However, there are many ways in which Excel can be used for a lot of other calculations, including…

And understand it properly. Statistics is a huge field of study. Most people only come across some statistics in school, and perhaps at university. Unless you have done a dedicated degree in data science, mathematics/statistics, quantitative finance or actuarial science; chances are you probably know very little. …