Analysis may include
- collection of data from experiments
- comparative research
- observations
- documentation (i.e., lab notebooks, technology/engineering design journals, and logs)
- application of formulas (e.g., mathematical, chemical)
- conclusions
- quality control (e.g., identification of quality standard, data validation).
Process/Skill Questions:
- What are quality controls, and what is the purpose of having them?
- How are quality controls maintained?
- What would be the consequences of not maintaining quality controls?
- What types of questions need to be answered when collecting data for an experiment?
- How and why are data collected from lab activities?
- What different methods are used to document data?
- How are data used to model biotechnical processes?
- How can the data analysis prove or disprove the question of the experiment?
- How do the results from the quality controls affect the data interpretation?