GCSE Chemistry revision

Chemical measurements

Chemical measurements, conservation of mass and the quantitative interpretation of chemical equations

AQA 4.3.1.4 Foundation & Higher

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Revision summary

Read on screen, then print for Cornell-style active revision.

Reacting Mass Calculations: Experimental data is converted into moles, allowing balanced equation mole ratios to determine the theoretical mass of products or reactants.
Percentage Yield Evaluation: Reaction efficiency is determined by comparing the actual experimental yield against the maximum predicted theoretical yield

1. Reacting Mass and Percentage Yield Calculations AQA

Reacting Mass Calculations: Experimental data is converted into moles, allowing balanced equation mole ratios to determine the theoretical mass of products or reactants.
Percentage Yield Evaluation: Reaction efficiency is determined by comparing the actual experimental yield against the maximum predicted theoretical yield

Calculating Mean Values: Repeating experimental measurements allows for the calculation of a reliable mean value, improving accuracy after removing any anomalous points.
Quantifying Experimental Uncertainty: Uncertainty is measured using the mean, where a smaller range indicates greater precision and lower experimental error.

2. Estimating Uncertainty using Range and Mean AQA

Calculating Mean Values: Repeating experimental measurements allows for the calculation of a reliable mean value, improving accuracy after removing any anomalous points.
Quantifying Experimental Uncertainty: Uncertainty is measured using the mean, where a smaller range indicates greater precision and lower experimental error.

Graphical Representation: Plotting experimental results on scatter graphs or line charts displays the overall distribution of data, allowing a line of best fit to be drawn to show trends between variables.
Handling Anomalous Results: Anomalies (outliers) are results that deviate significantly from the trend line; these should be identified, excluded when calculating mean values, and investigated or repeated.

3. Plotting Graphs and Identifying Anomalies AQA

Graphical Representation: Plotting experimental results on scatter graphs or line charts displays the overall distribution of data, allowing a line of best fit to be drawn to show trends between variables.
Handling Anomalous Results: Anomalies (outliers) are results that deviate significantly from the trend line; these should be identified, excluded when calculating mean values, and investigated or repeated.