uniform distribution is a probability distribution in which all outcomes or events are equally likely to occur. In other words, every possible outcome has the same probability of occurring. In Python, you can use the numpy library to generate random numbers following a uniform distribution. For example:
he binomial distribution is a discrete probability distribution that describes the number of successes in a fixed number of independent Bernoulli trials, each with the same probability of success. In other words, it models the number of successes (e.g., heads in a series of coin flips) in a fixed number of independent experiments, where each…
Gaussian distribution, also known as a normal distribution, is a continuous probability distribution that is symmetric around its mean, forming a bell-shaped curve. It is a fundamental concept in statistics and probability theory. The shape of the distribution is characterized by its mean (average) and standard deviation. The probability density function (PDF) of a Gaussian…
