## What is Descriptive Data Analysis?

Statistics are not always a witch’s brew of calculations and equations. It can happen that there are statistical tools that are very straightforward in both exercise and information cover. Descriptive data is one of the easiest forms of statistical analysis to understand. This helps summarize data in such a way that some patterns may be discerned from the figures. There are no conclusions that can be drawn beyond the information analyzed, and this really cannot be used for determining a conclusions from hypothesis. It is a very simple interpretation of data, which includes:

- Central tendency. This is a way of noting the center point of the frequency distribution for data;
- Measures of spread. This is used to describe how far spread out collected scores are. It permits summarization of a set of data. It can include statistics such as variance, range, and standard deviation.

## Descriptive Analysis of Data

Simplicity does not mean useless. Indeed, descriptive statistics are the foundation stone of quantitative data analysis. It takes large amounts of information and puts them into a manageable form. In addition to what has already been mentioned, descriptive analysis of data can include distribution (some of the frequency of individual values for a given variable), median (number at the exact middle of a set of numbers), and dispersion (spread of numbers around the central tendency, which includes range and standard deviation).

## The Use of Descriptive Data Analysis in Research

Given the terminology of descriptive statistics, the logic of the research will view the extent of the data and a time perspective. It can be intensive, studying just a few units of information, or extensive and examine a large group of units. Descriptive data analysis is best suited for Excel spreadsheet and database programs. The figures can be viewed in a qualitative analysis, or cross tabulations. Ultimately, the results have to be assessed and explained

## Examples of Descriptive Data Analysis

Descriptive Data Analysis Can Be Used for Any Number of Reasons

- The Average Height of a Group of Soldiers;
- The median test score on an examination;
- The mean prices of gasoline over a given period of time.

The use of descriptive statistics is basically up to the researcher and what information is needed. This form statistics is excellent for any type of cross tabulation which will show data as governed by any given variables (e.g., number of blonde haired accountants with blue eyes). As panel data analysis is particularly valuable in the area of finances and economics, descriptive analysis of data can help with retail marketing and population demographics. The beauty is in the immediate understanding of the results. No one has to be a rocket science to quickly grasp the message resulting from any analysis.

This is the form of statistical analysis that is perhaps most commonly understood. People learn about standard deviation and other definitions before they graduate from high school. It has a wide number of uses, but it also has to be understood that the depth of analysis is not substantial. Descriptive data analysis and give a very good view of the surface. In-depth inferences are best analyzed by other tools.