Evaluating Experiments

Evaluating Experiments

Part 1: Identifying Sources of Error:

  • Be aware that error can come from both systematic sources (such as faulty equipment) and random events (such as human error).
  • Understand that systematic errors can usually be identified and eliminated, while random errors are part of the inherent uncertainty of any experiment.

Part 2: Quantifying Uncertainty:

  • Know how to calculate absolute uncertainty, which is simply a measure of the spread of data.
  • Understand how to calculate percentage uncertainty, which takes into account the size of the measurements being made.
  • Be able to calculate standard deviation, a measure of how spread out a set of values are from the mean, and use this in the evaluation of data.

Part 3: Improving Experimental Design:

  • Be able to suggest changes or additions to experimental procedures to reduce error or uncertainty.
  • Understand the concept of optimisation in experimental design, aiming to get the most accurate results with the least effort or cost.

Part 4: Devising Further Experiments:

  • Understand the role of controls and blanks in experimental design, both to check for errors and to validate results.
  • Be able to suggest further experiments to test different variables, or to confirm surprising or ambiguous results.

Part 5: Communicating Results:

  • Know how to present data in a clear and understandable way, using tables, graphs or diagrams as appropriate.
  • Understand the importance of including all relevant detail in a lab report, including uncertainties or problems encountered.
  • Be able to critically evaluate results, identify limitations or problems, and suggest ways these could be addressed in future work.
  • Know how to draw conclusions from experimental data, and support those conclusions with appropriate evidence and reasoning.