# Standard Deviation Formula for Ungrouped Data

Standard Deviation Formula for Ungrouped Data: Standard deviation is normally represented by the symbol known as sigma or letter ‘σ’. The calculation of this entity can be found by using a formula called, standard deviation formula, which is used by mathematicians or statisticians. It can be articulated in the same units as the mean or average of all the data points.

## Standard Deviation Formula for Ungrouped Data

In the field of statistics, classification of data can be broadly categorized into two types. The first category is known as, grouped data, whereas the second one, is named as, ungrouped data. It essential for everyone to know that these data have to managed differently as well as mathematically. Hence, the procedure for calculating the measures of central tendencies such as standard deviation calculated for ungrouped data is always found different. In this context, the data values are always recognized and indicated as ungrouped if the observations are recorded in a random manner. This situation will occur without grouping them into class intervals. For example, while considering the measurement of the height of students in a class, it can be listed in a random manner. This value of such a data obtained should form an ungrouped data of value. Users may find it confusing while understanding the procedure to evaluate the standard deviations of either grouped or ungrouped data. It may be possible that one may not be able to understand some of the steps to be followed or may not be possible to arrive at results, which may be not perfect. To explain the procedure as to how to evaluate the standard deviation of ungrouped data a step by step process of how it is possible to find the standard deviation of any type category of ungrouped data with frequency is given. For this purpose, the user must follow the step-by step approach to find the standard deviation for a discrete or ungrouped data variable.

## Standard Deviation (Ungrouped Data)

In this procedure, as a first step it is essential to calculate the mean or average of the data. In the second step, the user has to subtract the mean from each observation. In the third step, calculating the square of each of the resulting observation should occur. In the fourth step, the user has to sum all these squared results together. In the final step, all that the user has to do is to divide the total number of observations to know the variance.

## Standard Deviation Formula for Ungrouped Data Examples 