Standardization of normal distribution

Standardization Of Normal Distribution. Normal distribution is also called Gaussian distribution or Gaussian law of error as this theory describes the accidental error of measurements. This distribution is known as the normal distribution or alternatively the Gauss distribution or bell curve and it is a continuous distribution having the following algebraic expression for the probability density. This is the distribution that is used to construct tables of the normal distribution. Logically a normal distribution can also be standardized.

To standardize a normal random variables subtract the mean from the random variable and divide the difference by the standard deviation. The standardized normal random variable u is defined as u x μ σ. This is the distribution that is used to construct tables of the normal distribution. A standard normal distribution SND. As you might suspect from the formula for the normal density function it would be difficult and tedious to do the calculus every time we had a new set of parameters for µ and σ. Logically a normal distribution can also be standardized.

A normal distribution has some interesting properties.

It is used to compare two or more distributions of data. A normal distribution with a mean of 0 and a standard deviation of 1 is called a standard normal distribution. A standard normal distribution SND. You may be wondering how the standardization goes down here. The standardized normal distribution. The amazing fact is that these 3 noticings will be true for any distribution of values and this includes normal distributions.