These properties permit the normal distribution to be applied as the basis for estimating how huge or small sampling errors are. The normal distribution or normal curve is one of a biggest number of probable distributions; it has a standard deviation of 1 and a mean of 0.
In most cases, it is not feasible to gather data on the whole target population. Supposed an entrepreneur plans to invest a shopping mall in a certain locality and decides to sell more clothings. He might be interested to know the body sizes of the people within the perimeter from the store, however, finds it impossible to collect all the data about the residents. Then, if the data subset or sample size of the population of interest can be considered instead of including the entire population. Hence, repeating the data gathering procedure would most likely lead to a different group of numbers. A framework or representation of the distribution is used to provide some sort of consistency to the results.
Using normal distribution is very important since it provide appropriate description about the measures of the variables (height, weight, age, economic profile, reading ability, job satisfaction, work performance, memory, life span and many others) precisely and normally distributed.