5.0 Interpret Data: Overview
This is the step where you will turn data into information, and there are two parts to this step:
- The first part is the accounting or assessment, in which you will apply statistical algorithms to basic field measurements and turn these into what we have termed metrics, guided by the study’s response design. Later, these metrics will be combined into the final indicators, guided by the study’s inference design.
- These metrics are often used for active in-season management. In turn, you will convert these metrics into what we have termed indicators guided by the study’s inference design. There are many standard techniques for conducting field research, and many standard statistical techniques for summarizing data associated with field research. However, if you simply produce statistics, tables, and graphs you will have done an incomplete job of interpreting your data.
- The second part, finding meaning and relevance in the data, is both more difficult and more important.
- To be valuable as a scientific contribution, your study must able to help decision makers and the public understand whether an expensive restoration effort is working as intended, know if a stock is continuing to decline, know if recent adjustments to regulations have resulted in additional escapement, or know the answer to whatever important question launched the study in the first place. In other words, this job of finding scientific meaning in the data is what separates fishery science from accounting or arithmetic.