Part 2

• How to answer the evaluation

  • quality of the data - is there enough, difference between values
  • Is it repeatable/reproducible
  • confidence in data - error bars close together
  • Improvements - better equipment, resolution, systematic error
• How to plan experiments

  • identify variables (independent, dependent, control)
  • Use correct units for variables
  • Identify suitable range of independent (at least 5 values)
  • explain why repeats are needed - reliability, identify anomalies
  • Design a control experiment
  • Assess risks