Data Analysis

Data analysis is a practice in which raw data is ordered and organized so that useful information can be extracted from it. The process of organizing and thinking about data is key to understanding what the data does and does not contain. There are a variety of ways in which people can approach data analysis, and it is notoriously easy to manipulate data during the analysis phase to push certain conclusions or agendas. For this reason, it is important to pay attention when data analysis is presented, and to think critically about the data and the conclusions which were drawn.

Raw data can take a variety of forms, including measurements, survey responses, and observations. In its raw form, this information can be incredibly useful, but also overwhelming. Over the course of the data analysis process, the raw data is ordered in a way which will be useful. For example, survey results may be tallied, so that people can see at a glance how many people answered the survey, and how people responded to specific questions.

Key Concepts

Data collection is the systematic recording of information; data analysis involves working to uncover patterns and trends in data sets; data interpretation involves explaining those patterns and trends.

Scientists interpret data based on their background knowledge and experience, thus different scientists can interpret the same data in different ways.

By publishing their data and the techniques they used to analyze and interpret that data, scientists give the community the opportunity to both review the data and use it in future research.