Anomalous Results, Conclusions & Evaluation (AQA GCSE Biology): Revision Note

What is an anomalous result?

• An anomalous result is a value that appears to be outside the general pattern of the results

  • It is usually an extreme value that is either very high or very low compared with the others

• AQA defines anomalies as:

Values in a set of results which are judged not to be part of the variation caused by random uncertainty

• Describe an anomalous result by saying the way in which it does not fit the pattern

  • Saying that it is "wrong", "a mistake" or "an error" is not enough to describe an anomalous result

• When you have anomalous results you should:

  • leave them out when you calculate a mean

  • ignore them when you draw a line of best fit

    • If you ignore a point on a graph, show this clearly, e.g. by drawing a circle around it

• Repeating a reading does not stop anomalous results happening, but it helps you to spot anomalies

• Examiner reports show that students lose marks by not showing which point on a graph they have treated as anomalous

• When asked to identify an anomaly in a table, ring the raw result and say how it differs, e.g. much lower than the other repeats

How to write a conclusion

• A conclusion says what your results show, and should relate to the aim of the investigation

  • Before you write it, reread the aim in the question

• In your conclusion you should:

  • link the independent variable to the dependent variable

    • For example, "as the temperature increased, the rate of water loss also increased"

  • support your conclusion with evidence from your results, comparing values from the table or graph, e.g. the time taken was shorter at pH 7 than at pH 9

• Only conclude what your results actually show:

  • Be careful not to state a causal link when one hasn't been proven; sometimes a conclusion may just state that two variables are linked but cannot state that a change in one variable caused a change in another (i.e., correlation, not causation)

  • Do not apply the results of a conclusion too broadly

    • For example, results gained from studying woodlice may not be applicable to humans

• Examiner reports show that students lose marks by writing conclusions that are not backed up by evidence from their results

Sources of error & improvements

• Error, in the context of scientific investigation, refers to specific errors in measurement, not just general mistakes like spilling a solution, or adding the wrong volume

• A measurement error is the difference between a measured value and the true value

• Measurement errors can be:

  • random errors

    • These cause readings to be spread about the true value, e.g. when starting and stopping a stopwatch by hand

    • You can reduce the effect of random errors by repeating readings and calculating a mean

  • systematic errors

    • These cause readings to differ from the true value by a consistent amount each time, e.g. a balance that does not read zero before you start (a zero error)

    • Repeating readings does not remove a systematic error; check that the balance reads zero before you use it, or repeat the measurements with a different set of equipment and compare the results

• The true value is the value that would be obtained in an ideal measurement

• Uncertainty is the interval within which the true value can be expected to lie

• Parallax error happens when you read a scale from an angle, so be sure to read scales at eye level, e.g. when reading a volume of liquid in a measuring cylinder, or reading a thermometer

• For every source of error you identify, suggest a specific, matching improvement that would reduce it

• Only suggest improving something that the given method does not already control