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 ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...

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 normal distribution is a continuous probability distribution that is symmetrical, bell-shaped, and centred around its mean. It is one of the most important distributions in statistics because many ...