We prefer mostly normal distribution, because most of the data around us follows normal distribution example height, weight etc. will follow normal. We can check it by plotting the graph then we can see the bell curve on the histogram. The most importantly by CLT(central limit theorem) and law of large numbers, we can say that as n is large the data follows normal distribution.
Why we prefer Normal Distribution over the other distributions in Statistics
The Normal distribution is, by definition, symmetric. There is no other kind of Normal distribution, so the adjective is not used.
we prefer normal distribution over other distribution in statistics because most of the data around us is continuous. So, for continuous data normal distribution is used.
The normal distribution has two parameters, the mean and the standard deviation Once we know these parameters, we know everything we need to know about a particular normal distribution. This is a very nice feature for a distribution to have. Also, the mean, median and mode are all the same in the normal distribution. Also, the normal distribution is important in the central limit theorem. These and many other facts make the normal distribution a nice distribution to have in statistics.
It has no special name - other than a normal (or Gaussian) distribution graph.
The normal distribution can have any real number as mean and any positive number as variance. The mean of the standard normal distribution is 0 and its variance is 1.
The mean is 0 and the variance is 1. This need not be the case in any other Normal (Gaussian) distribution.
The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution. There are other differences in terms of when it is appropriate to use them. Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.
Gaussian distribution. Some people refer to the normal distribution as a "bell shaped" curve, but this should be avoided, as there are other bell shaped symmetrical curves which are not normal distributions.
Actually the normal distribution is the sub form of Gaussian distribution.Gaussian distribution have 2 parameters, mean and variance.When there is zero mean and unit variance the Gaussian distribution becomes normal other wise it is pronounced as Gaussian.Wrong! The standard normal distribution has mean 0 and variance 1, but a normal distribution is the same as the Gaussiand, and can have any mean and variance. Google stackexcange "what-is-the-difference-between-a-normal-and-a-gaussian-distribution"
The Normal ditribution is symmetric but so are other distributions.
It may not be better, but there is a lot of information on the normal distribution. It is one of the most widely used in statistics.