In statistics, distribution of a data population pertains to how data is spread out within the given population and how these are arranged. There are several statistical measures that used in describing how specific data are spread out within a given population. One is by using the ranger which measures the ranged of values within a population, the deviation, which is the difference each value in the population from the mean among others. The statistic or measure of dispersion that looks into the looseness or tightness of data is the standard deviation. It measures how often a data deviates from the norm of the mean of the population.
Standard deviation is an important measure to further describe how the elements of a population behave. This is also often referred to as the standard error of the mean. Standard deviations are also used in as a measure of confidence when making statistical conclusions. This can be use to determine the reliability or significance of a data.
An application where the standard deviation is deemed important in making conclusions is related to weather forecasting. Even if two places have the same average temperature of a given number of days, one cannot readily conclude from by just looking at the average temperature alone that the weather in these two places are the same. The standard deviation can be use to determine which of the places has a more reliable temperature prediction. The place with higher standard deviation will have a greater chance of having unreliable temperature prediction since the standard error is greater.
