Analysing results

A conclusion is a statement that links the results back to the hypothesis or research question, supported by the data.

Structure of a strong conclusion (CCEA mark scheme)

1. State the trend observed (positive correlation, optimum, plateau, etc.).
2. Quote at least one data value to support it (with units).
3. Refer to the science that explains the trend.
4. State whether the hypothesis is supported.

Example: "The rate of reaction increased as temperature increased from 10 °C (1.2 cm³/s) to 40 °C (4.8 cm³/s). This is because particles have more kinetic energy at higher temperatures, so more frequent and more energetic collisions occur. The hypothesis is supported up to 40 °C."

Identifying anomalies

An anomaly is a result that does not fit the overall pattern. Spot it by:

• Plotting the data and looking for points off the line of best fit.
• Comparing repeats — a single value far from the others.
• Checking the calculated mean — does dropping one repeat change the mean significantly?

If found, circle the anomaly on the graph and exclude it from the calculation of the mean.

Possible causes of anomalies

Cause	Example
Measurement error	Misread the burette / parallax error
Procedural error	Incorrect timing, contamination
Random variation	Temperature drift, draughts

Reliability vs validity vs accuracy

• Reliability — how close repeat values are to each other. Improved by repeating and taking a mean.
• Validity — whether the experiment actually tests what it claims. Improved by controlling variables.
• Accuracy — how close a value is to the true value. Improved by using better apparatus and calibration.

CCEA tip

When asked to "evaluate the experiment", give one strength AND one weakness, each with a suggested improvement. Listing only weaknesses caps your mark, no matter how many you list.