Once the researcher has collected all the data from the experiment, it is time to begin analyzing the results. The process of analyzing data involves the use of logical techniques such as statistics to explain the information from the data. How to analyze the data is determined by whether the design used for the research was quantitative or qualitative. Organization of the research for analysis should be handled as predetermined by the design and method.
When analyzing qualitative data, the researcher should start off with an initial idea about what the data will say. However, as the process takes place, it is important to be open to any alternative theories that the data may support. Any analysis of qualitative data should consider how to measure the material to be sure that meaning can be established. Some of these analytical methods include classifying the material, discourse analysis, induction, grounded theory, and qualitative comparative analysis, as well as many others.
The researcher using quantitative analysis should review the data without any preconceived expectations. Looking through the data and compiling the information should provide the details for what the research is revealing. While looking at the information, researchers must perform the appropriate evaluative calculations in a consistent way to interpret the outcome of the experiment. There are a number of ways to analyze quantitative data, but they should be reflected by the question being asked by the researcher as part of the design. For further information about quantitative or qualitative analysis, try viewing the information in the Data Analysis and Interpretation section of the Sage Research Methods Project Planner, as well as a number of other resources listed in this guide.
|GIS/Mapping||Free to anyone (open source.) Download here|
|Scientific data analysis software, numerical computing environment and programming language||Available to faculty, but may be available for use in a lab.|
|Statistical Discovery Software Tool||Available to faculty, but may be available for use in a lab.|
|Mathematical analysis software and programming language||Available to faculty, but may be available for use in a lab.|
|All-in-one graphical and statistical analysis package||Available to anyone at APSU. Request from IT department.|
|Built to help develop information databases.||Free to anyone (open source.) Download here|
|Purpose-built for qualitative and mixed-methods research||Available to faculty, but may be available for use in a lab.|
|Statistical computing and graphics||Free to anyone. Download here|
|Scientific graphing and data analysis software package||Available to faculty, but may be available for use in a lab.|
|Advanced statistical analysis||Available to faculty, but may be available for use in a lab.|
|General-purpose statistical software package||Available to faculty, but may be available for use in a lab.|