Planning and Evaluating Experiments
Planning: state the independent (changed), dependent (measured) and controlled variables; write a hypothesis; choose apparatus and quantities (with reasons); give a step-by-step method; identify hazards and precautions. Analysis: tabulate with units; plot graphs with the independent variable on ; draw a line of best fit; calculate gradients using a large triangle; use derived quantities (1/t, ln k). Evaluation: identify anomalies; distinguish random errors (scatter; reduce by repeats) from systematic errors (shift all results; reduce by changing method); calculate % error against a reference value and compare with total % uncertainty; suggest specific improvements.
Learning objectives
- Identify variables and write a hypothesis.
- Plan a safe, detailed method.
- Process data and calculate gradients.
- Evaluate errors and suggest improvements.
Your measured enthalpy of neutralisation is 10% less exothermic than the data book value, but your total uncertainty is only 3%. What does that tell you?
Core idea
A good plan names its variables, uses real quantities, and explains how it will reduce error. "Be careful" earns nothing.
Control every variable except one, process the data with graphs, and compare your error with your uncertainty.
Each stage feeds the next.
Measured −52.0, accepted −57.1 kJ mol⁻¹. % error?
- Goal
- %.
- Strategy
- |E − A| / A.
- Difference.
- Relative to the accepted value.
Summary
- Independent, dependent, controlled.
- Large triangle for gradients.
- Random vs systematic error.
- Systematic error
- Error that shifts every result the same way.
- Random error
- Unpredictable scatter; reduced by repeats.
Create a free account to read the rest of this lesson: key formulae, worked examples, explore the graph, common mistakes, exam tip, guided practice and more. Your answers are checked and your progress is saved.