Data Interpretation
Methods also include ways of interpreting and organizing data, either once it has been collected or simultaneously with data collection. More specific methodologies, such as ways to structure the analysis of your data, include the following:
- Coding. Reviews transcripts of interview data and assigns specific labels and categories to the data. A common social science method.
- Cost/benefit analysis. Determines how much something will cost versus what measurable benefits it will create.
- Life-cycle analysis. Determines overall sustainability of a product or process, from manufacturing, through lifetime use, to disposal. You can also perform comparative life- cycle analyses or specific life cycle stage analyses.
- Comparative analysis. Compares two or more options to determine which is the “best” solution given specific problem criteria such as goals, objectives, and constraints.
- Process analysis. Studies each aspect of a process to determine if all parts and steps work efficiently together to create the desired outcome.
- Sustainability analysis. Uses concepts such as the “triple bottom line” or “three pillars of sustainability” to analyze whether a product or process is environmentally, economically, and socially sustainable.
In all cases, the way you collect, analyze, and use data must be ethical and consistent with professional standards of honesty and integrity. Lapses in integrity may lead to poor quality reports not only in an academic context (poor grades and academic dishonesty penalties) but also in the workplace. These lapses can lead to lawsuits, job loss, and even criminal charges. Some examples of these lapses include
- Fabricating your own data (making it up to suit your purpose)
- Ignoring data that disproves or contradicts your ideas
- Misrepresenting someone else’s data or ideas
- Using data or ideas from another source without acknowledgment or citation of the source
Writing Tip!
Failing to cite quoted, paraphrased, or summarized sources properly is one of the most common lapses in academic integrity, which is why your previous academic writing classes spent considerable time and effort to give you a sophisticated understanding of how and why to avoid plagiarizing, as well as the consequences of doing so.
