Because very many variables tend to have the Gaussian distribution. Furthermore, even if the underlying distribution is non-Gaussian, the distribution of the means of repeated samples will be Gaussian. As a result, the Gaussian distributions are also referred to as Normal.
No. Normal distribution is a continuous probability.
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
It is a continuous parametric distribution belonging to the family of exponential distributions. It is also symmetric.
No, the normal distribution is strictly unimodal.
Most random variables are found to follow the probability distribution function All this means is that most things which can be measured quantitatively, like a population's height, the accuracy of a machine, effectiveness of a drug on fighting bacteria, etc. will occur with a probability that can be calculated according to this equation. Since most things follow this equation, this equation is considered to be the "normal" probability density. "Normal" events follow a "normal" probability distribution.
No. Normal distribution is a continuous probability.
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
It is a continuous parametric distribution belonging to the family of exponential distributions. It is also symmetric.
A bell shaped probability distribution curve is NOT necessarily a normal distribution.
When its probability distribution the standard normal distribution.
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
No, the normal distribution is strictly unimodal.
Most random variables are found to follow the probability distribution function All this means is that most things which can be measured quantitatively, like a population's height, the accuracy of a machine, effectiveness of a drug on fighting bacteria, etc. will occur with a probability that can be calculated according to this equation. Since most things follow this equation, this equation is considered to be the "normal" probability density. "Normal" events follow a "normal" probability distribution.
The total area of any probability distribution is 1
I apologize my question should have read what are the characteristics of a standard normal probability distribution? Thank you
with mean and standard deviation . Once standardized, , the test statistic follows Standard Normal Probability Distribution.
Yes.