Continuous Variable: can take on any value between two specified values. Obtained by measuring. Discrete Variable: not continuous variable (cannot take on any value between two specified values).

A continuous random variable X follows a normal distribution, denoted as $X \sim \mathcal{N}(\mu,,\sigma^{2})$. The normal distribution is characterized by its bell ...

Abstract: While probability distribution functions are crucial for simulating random processes, research on these functions and their features is required. However, studies have demonstrated that in ...

The probability density function of a uniform random variable looks like a horizontal line segment over the support. This indicates that for any interval of a given length within the support, the ...