How do we analyse environmental data and decide whether a result is statistically significant?
The handling and presentation of environmental data, the use of means, ranges and standard deviation, the choice and use of statistical tests, correlation versus causation, and the evaluation of reliability and validity.
A focused answer to AQA A-Level Environmental Science 3.6 data handling, covering the presentation of data, means and standard deviation, statistical tests, correlation versus causation, and the evaluation of reliability and validity.
Reviewed by: AI editorial process; not yet individually human-reviewed
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What this dot point is asking
AQA wants you to handle and present environmental data, use means, ranges and standard deviation, select and use appropriate statistical tests, distinguish correlation from causation, and evaluate the reliability and validity of data. Command words are Describe, Explain and especially Calculate, so be confident computing a mean and standard deviation by hand.
Presenting environmental data
The way data are presented depends on their type:
- Tables organise raw data clearly with units in the headings.
- Bar charts compare discrete categories (such as species counts).
- Line graphs show how a continuous variable changes, for example over time.
- Scatter graphs show the relationship between two continuous variables, and a line of best fit indicates the trend.
Choosing the right chart is itself examined: continuous-against-continuous data demand a scatter or line graph, not a bar chart.
Descriptive statistics
The standard deviation is more informative than the range because it uses every value, not just the two extremes, so a single outlier does not dominate it.
Statistical tests and significance
Choose the test according to the question: a test of correlation (such as Spearman's rank) for a relationship between two variables, or a test of difference (such as a t-test or chi-squared) when comparing groups or observed against expected counts.
Correlation and causation
Reliability and validity
- Reliability is the repeatability of results: reliable data give similar values when the measurement is repeated, improved by replication and a mean.
- Validity is whether the data actually measure what they are intended to measure, achieved by controlling other variables and using a method that genuinely tests the hypothesis.
Exam-style practice questions
Practice questions written in the style of AQA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
AQA 20195 marksA student measures the number of mayfly nymphs at ten sites along a river. Describe how to calculate the mean and standard deviation, and explain what a large standard deviation would tell you about the data.Show worked answer →
Markers reward a correct description of the calculations plus a correct interpretation.
Mean: add all ten counts and divide by ten. Standard deviation: find the difference of each value from the mean, square each difference, add the squares, divide by the number of values (or one less for a sample), then take the square root.
Interpretation: a large standard deviation means the counts are widely spread around the mean, so the sites differ greatly and the mean is a less representative single figure; it suggests high variability, perhaps from patchy habitat or pollution, and warns that more replicates may be needed. Full marks need both the method outline and the spread interpretation.
AQA 20215 marksCalculate the mean and standard deviation of the five dissolved oxygen readings 7, 9, 8, 6 and 10 mg per cubic decimetre, and comment on the reliability of the data.Show worked answer →
A full worked calculation is expected.
Mean: .
Deviations from the mean: . Squared: , summing to . Variance (dividing by for a sample): . Standard deviation: .
Comment: the spread is moderate relative to the mean, so the readings are reasonably consistent; repeating the measurements would confirm reliability. Award the correct mean, the squared-deviation method, division by , the square root, and a reliability comment.
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