Descriptive Statistics is one of the simplest techniques used in quality management to obtain a meaningful insight into the data being analyzed. (The original article can be found at the source link mentioned below the extract)

Let us take a few examples. It makes sense to build a frequency table of complaints by categories from the raw data on complaints from different customers. It clearly tells us the top few complaints that need immediate attention. On the other hand, it would be preferable to compute the average or mean from loan processing time data of thousands of applications from a bank to find out the average turnaround time required to process any application. This can subsequently be compared with industry average to benchmark bank's performance.

SCAN: Basics of Statistics- www.discover6sigma.org/post/2005/12/statistics-simplified/

Data types tell us how we can gain meaningful insight in the data – this could be achieved by computing mean or by building frequency table or by using other summary measures such as mode or median. Therefore, it is important to understand the type of data being analyzed to determine what summary measures are applicable to obtain a meaningful insight.

Read full article at: www.discover6sigma.org/post/2011/06/desc-stats/

Interesting Read !!

Descriptive statistics provides simple summaries about the sample and about the observations that have been made.

When we talk about ‘data driven decision making’, knowing and classifying data is a first important step to gain meaningful insights.

very useful information!!

i have a confusion in differentiating the types of data. Hope this will make things much clear.