Step 5 – Analyzing Data

There are many ways of making sense of the collected data. For the purpose of this project, the constructive method of data analysis was used because of its practicality. There are four aspects to this method.

• Reading data —data are read or closely scrutinized in order to recall the events and experiences that they represent. What was done? What was said? What really happened?

• Selecting data —important factors are separated from unimportant ones, similar factors are grouped, complex details are sorted and simplified.

• Presenting the data —the selected data are presented in a form that is easy to take in at a glance.

• Interpretating data and drawing conclusions — Relationships are explained and a practical model constructed to fit the situation which has been researched.

Once a decision has been made to end simultaneous data collection and analysis, the information must be organized so that the analysis can begin. All of this material is called the study data base and needs to be organized in some fashion so that information is easily retrievable. Developing the study data base involves fairly simple sorting of all the data. The goal is to be able to locate specific information during analysis. The data therefore needs to be organized according to some scheme that makes sense to the investigator and then indexed accordingly.

Data analysis is the process of making sense out of one’s data. All of the information that has been gathered together and organized topically or chronologically should be read through several times from beginning to end. While reading, the investigator jots down notes, comments, observations and queries in the margins. At this stage the researcher is virtually holding a conversation with the data, asking questions of it, making comments, and so on. These notes serve to isolate the most striking aspects of the data. The notes are developed into a preliminary outline or system of classifications into which data are sorted initially. The outline begins with a search for regularities —things that happen frequently with groups of people. Patterns and regularities then are transformed into categories into which subsequent items are sorted. These categories or patterns are discovered from the data.