How frequently you use statistical analyses in your work? Is it every day? Every week? Every quarter? Annually?None at all? Now it is time to gather your data and evaluate your performance and get ready to take off. Using descriptive analytics is a cutting edge advantage , that is, if you know how to use it. As we go along, we will understand how to keep going with your strategies by looking into the intricacies of your data, and delving into which data to examine and use to advance your next move.
What is descriptive analytics? Descriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information. Its main objective is to uncover valuable insights from the data being analyzed. It answers the questioned “What happened?.”
Descriptive analytics is the backbone of analytics. This is the starting point of further more complex analytics like predictive and prescriptive. Its findings may not be as exciting as any more complex models, but the latter my not be more meaningful and complete without the data gathered using descriptive analytics. Even if it is the simplest type, it is the most commonly used. It is still very valuable.
There are two primary types of descriptive analytics: measures of central tendency and measures of dispersion. The first generally tells about the middle of a data set. What should be taken note of are the following: mean (the average of the data), median (the midpoint of the responses), and mode (the response with the highest frequency). The second, on the other hand, describes about the extent of stretch of data set. In this type, the following must not be forgotten: range (the difference between the lowest and highest values), variance (the average degree to which each of the points differ from the mean), and standard deviation (used to quantify the amount of variation or dispersion of a set of data values).
Examine the data below:
The data above are just very simple so you could clearly understand the use of descriptive analytics. This table is about the buying behavior of customers. We are looking into the customers, the items purchased and the amount spent. We have a better picture of the customers overall. We could see that the average amount spent is 2 dollars but most customers buy only one item. The data show that there is high spread of the number of items purchased. On an average basis, the number of items purchased is not high. This is where our understanding of measures of central tendency sets in to provide us wide understanding of the customers buying habits not just on the basis of average.
As we go along, let’s examine the significance and practicality of each of these types, and learn how they are used in business. For now, let’s have the basic concepts. As move along, we will uncover the unique features and uses of these analytical tools. Continue to subscribe.