Descriptive statistics are utilized to describe the basic features of the data in a study. Descriptive statistic data provide simple summaries about the sample and the measures utilized within quantitative methodologies. Descriptive statistics are especially helpful in simplifying large amounts of data and can be a component of quantitative, qualitative, and mixed methods research. This page will help you contextualize how you can use descriptive statistics within your research project. In addition, we have identified tools and resources that you can access to summarize your quantitative data.
Descriptive Statistics and Inferential Statistics
Are descriptive statistics and inferential statistics one and the same? In short, no. Descriptive statistics are used to describe quantitative data sets whereas inferential statistics are utilized to draw quantitative conclusions (i.e., probability, differences between groups, etc.). Descriptive statistics are especially helpful when researchers are presenting large amounts of data and need to succinctly summarize aspects of quantitative findings.
Descriptive statistics can be illustrated developing graphical summaries (see below). Tables, figures, and infographics are tools that researchers can utilize to not only simplify data but help narrate compelling researcher. For example, you can access the I AM A #YOUNGWOKER report to see the ways in which descriptive statistics are utilized to inform about how young workers struggle today. Click here to access the report.
You can also watch the way in which the descriptive data from these charts and graphs were utilized to create the I am a #YoungWorker animated video.
To further understand the difference between inferential and descriptive statistics, you can watch the tutorial below:
Graphical summaries present diverse aspects of the data, focusing on the value of the data and/or the frequency of the data. In other words: what values does the data (aka variable) take on and with what frequency?
Graphs summarize and illustrate different types of data (i.e., categorical, continuous, and ordinal). Different types of graphical summaries lend themselves to different types of descriptions and visualizations.
You can also watch the graph and summaries excel tutorial below (and follow along by downloading the excel file here):
Among the different types of descriptive tables and graphs you can develop to visually represent your data, pivot tables are an especially useful tool. Pivot tables can automatically sort, count total or give the average of the data stored in one table or spreadsheet. In addition, you can interact with the data by dragging and dropping fields geographically.
You can watch the pivot table tutorial below to learn how to create you own pivot table (and download the data set here to follow along with the tutorial):
Common Descriptive Terms
This is a tutorial video that reviews foundational concepts to understanding descriptive statistics. The video below will illustrate how you can represent a set of numbers with one number that indicates the “center” of your quantitative data. The terms utilized in this video–mean, median, and mode–are defined below as well as access to the mean, median, and mode calculator.
The average and more specifically– the sum of a data set divided by the number of data (i.e., (80 + 90 + 90 + 100 + 85 + 90) / 6=89 1/6).
The number in the middle. In order to find the median, you have to put the values in order from lowest to highest, then find the number that is exactly in the middle (bold): 80 85 90 90 100 since there is an even number of values, the median is between these two, or it is 90. Notice that there is exactly the same number of values before the median as after the median.
The value that occurs most often. In this case (80, 85, 90, 90, 100), there are two 90’s, the mode is 90. A set of data can have more than one mode.
Click here to access the statistics glossary and define commonly used terms utilized within quantitative research
Descriptive Statistics Tools & Resources
Did you know that your excel program was capable of supporting descriptive statistics analysis? Excel can help you organize large quantitative data sets and produce different types of graphs and and summaries. Watch the tutorial below:
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Information for this page has been has been adapted from:
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches. Los Angeles, CA: Sage.