It is called a normal distribution.
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.
I am under the assumption that in statistics, if the ten percent condition is not met, meaning that the sample size is more than 10% of the population, then the result is not a normal distribution.
i dont even no
Why we prefer Normal Distribution over the other distributions in Statistics
It is called a normal distribution.
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.
I am under the assumption that in statistics, if the ten percent condition is not met, meaning that the sample size is more than 10% of the population, then the result is not a normal distribution.
i dont even no
The Student's T- Distribution is a type of probability distribution that is theoretical and resembles a normal distribution. The Student T- Distribution differs from the normal distribution by its degrees of freedom.
a Gaussian or 'normal' distribution
The normal distribution is a statistical distribution. Many naturally occurring variables follow the normal distribution: examples are peoples' height, weights. The sum of independent, identically distributed variables - whatever their own underlying distribution - will tend towards the normal distribution as the number in the sum increases. This means that the mean of repeated measures of ANY variable will approach the normal distribution. Furthermore, some distributions that are not normal to start with, can be converted to normality through simple transformations of the variable. These characteristics make the normal distribution very important in statistics. See attached link for more.
It is probably the most widely used distribution in statistics. In addition, a lot of information exists on this distribution.
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.
normal_distribution