Descriptive statistics is a broad term that represents the numbers, which summarize the data in a meaningful manner before applying the analytical measurement tools to reach to any conclusion. However, descriptive statistics is not useful for making inferences from the sample. The descriptive statistics is significant because it is not possible to present the pattern of the data from the raw data listing, hence, it is a way of presenting the summary of the information in a simpler manner for easy interpretation of the data. 

Descriptive statistics include two categories, measures of the central tendency and measures of the variability or spread. The measures of the central tendency describe the one number representing the central position of the frequency distribution of a set of data. It includes three types, namely, mean, median and mode. On the other hand, measures of spread represent how spread out the data is. In other words, it represents the variability within the data. It includes standard deviation, range, quartiles, variance and absolute deviation. All these measures represent the level of the spread within the data from its mean, position of the observation within the dataset or difference between highest and lowest observations and many other types of variability.

Thus, descriptive statistics is used for presenting the summary of the datasets in an easy manner so that the understanding of the frequency and variability of the data becomes simpler. It is also beneficial for presenting the data through visual tools, such as, graphs and charts, which makes interpretation of the nature of the datasets more precise.