1. StatisticsIn probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is f(x)=12πσ2exp⁡(−(x−μ)22σ2). The parameter ⁠μ⁠ is the mean or expectation of the distribution (and also its median and mode), while the parameter σ2 is the variance. The standard deviation of the distribution is the positive value ⁠σ⁠ (sigma). A random variable with a Gaussian distribution is said to be normally distributed and is called a normal deviate. Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known. Their importance is partly due to the central limit theorem. It states that the average of many statistically independent samples (observations) of a random variable with finite mean and variance is itself a random variable—whose distribution... from wikipedia.org