Interpreting Graphs in Science
In 2019, WHO epidemiologists spotted a sharp kink in Congo's Ebola curve on day 42 — they interpreted it as a new transmission chain and redirected 300 health workers within 48 hours.
Printable Worksheets
Print or save as PDF — or build a custom worksheet from any module's questions.
You see a line graph showing carbon dioxide levels in a classroom over a school day. The line rises steadily during lessons, drops sharply at recess and rises again afterwards.
What does this graph tell you about when CO2 levels are highest? What might be causing the pattern, and what action could the school take?
Your teacher puts a line graph of plant heights on the board. The line rises steadily for 10 days, then goes completely flat for 3 days, then spikes sharply upward. A student says "it went up." That is not wrong — but it tells you almost nothing. What happened on day 10? Why the plateau? Why the spike? Reading a graph scientifically means more than glancing at the line. Start by reading the title — it tells you what the graph is about. Then check the axes: what is being measured on each, and in what units? Look at the scale — a compressed axis can make small changes look dramatic, while a stretched axis can hide important variation.
Next, describe the overall pattern. Is the line rising, falling, flat or curved? Are there sudden jumps, plateaus or cycles? Ask yourself what each feature might mean in the real world. A sudden jump could indicate an experimental change, a reaction starting, or an outlier. A flat section might mean nothing is changing, or that the measurement has reached a limit.
Finally, connect the graph back to the original question. The graph is evidence, and your job is to explain what it proves or suggests.
A graph shows the temperature of water being heated. The line rises steadily, then flattens at 100 degrees Celsius for several minutes. The flat section is not an error — it shows the water boiling, with energy going into phase change rather than temperature rise.
BOM publishes rainfall graphs for every Australian region. Reading these graphs systematically — checking scales, identifying seasonal patterns, and spotting anomalies — helps farmers, engineers and emergency services make critical decisions.
Students often look only at the general direction of a line and ignore everything else. This is wrong. The shape, scale, labels and specific points all carry meaning. A graph is like a scientific argument written in visual form.
Know
- Graphs display relationships between variables in a visual format.
- The axes, scale and title provide essential context for interpreting a graph.
Understand
- Interpreting a graph involves describing trends, identifying relationships and explaining causes.
- Graphs can be used to make predictions beyond the measured data range.
Can Do
- Extract specific values and describe trends from a scientific graph.
- Draw conclusions supported by evidence from the graph.
Wrong: Interpreting a graph is just reading the numbers.
Right: True interpretation involves describing trends, suggesting causes, evaluating reliability and considering what the data means in a real-world context.
Wrong: Extrapolation always gives reliable predictions.
Right: Extrapolation assumes the trend continues unchanged, which may not be true outside the measured range. It should be done with caution.
Wrong: Describing the graph without linking it to the scientific context.
Right: Always connect your description to the variables and the real-world situation. A graph is a tool for understanding science, not just an image to describe.
Wrong: Assuming a trend will continue forever when extrapolating.
Right: Natural systems often have limits. A plant cannot grow infinitely tall, and a reaction cannot speed up forever. Consider physical boundaries.
Describing a trend means using precise scientific language. Avoid vague words like 'goes up' or 'changes.' Instead, say whether the relationship is direct or inverse. Note whether the line is linear (straight) or curved. Identify any plateaus — flat sections where the dependent variable stops changing.
Use data from the graph to support your description. Quote specific values: 'As temperature increased from 20 degrees to 60 degrees, solubility rose from 15 grams to 45 grams per 100 millilitres.' This kind of precise description shows you are reading the graph carefully, not guessing.
Always describe the trend in terms of the variables on the axes, not in general terms. The trend is not just 'it went up' — it is 'solubility increased as temperature increased.'
A graph of reaction rate against enzyme concentration shows a steep rise at low concentrations, then a plateau at higher concentrations. The correct description: 'Reaction rate increases with enzyme concentration up to a point, after which the rate plateaus because the substrate becomes the limiting factor.'
CSIRO marine scientists describe trends in ocean temperature graphs using exactly this precise language. Their descriptions inform national reports on climate impacts, where vague wording could lead to misunderstood policy decisions.
Many students describe a graph by saying 'the line goes up' without mentioning which variables are involved. This is wrong. A scientific trend description always names both the independent and dependent variables and describes their mathematical relationship.
Interpolation is estimating a value that lies between two known data points. If you know the solubility at 20 degrees and 40 degrees, interpolation lets you estimate it at 30 degrees. It is reliable because you are working within the range you have actually measured.
Extrapolation is estimating a value beyond your measured range. It is far riskier because you are assuming the trend continues unchanged. Outside your data range, new factors might take over. A metal might melt, a reaction might stop, or a biological system might reach a limit. Scientists use extrapolation cautiously and always label it as an estimate beyond the measured range.
A spring stretches 2 cm with 1 N, 4 cm with 2 N and 6 cm with 3 N. Interpolating: 2.5 N would stretch about 5 cm. Extrapolating to 10 N assumes the spring keeps stretching linearly, but in reality it might break or reach its elastic limit.
ABS demographers use interpolation to estimate population between census years and extrapolation to project future populations. They clearly state the assumptions behind extrapolated figures because they know trends can shift unexpectedly.
Students often think extrapolation is as reliable as interpolation. This is wrong. Interpolation works within known territory; extrapolation is a gamble that the pattern continues. Good scientists always flag extrapolated values as uncertain predictions.
Drawing a conclusion from a graph means linking the visual pattern to a scientific claim. A strong conclusion answers the original question, references specific data from the graph, and acknowledges any limitations. It does not overstate what the evidence shows.
A weak conclusion says 'the graph shows temperature matters.' A strong conclusion says 'The graph shows reaction rate increases linearly with temperature between 20 and 60 degrees Celsius, doubling from 0.5 to 1.0 grams per second. However, the experiment only tested three temperatures, so we cannot be certain the trend continues beyond 60 degrees.'
Always check whether your conclusion confuses correlation with causation. The graph shows what happened; your conclusion explains why, and that explanation must be supported by scientific reasoning, not just the graph alone.
A graph shows plant height against fertiliser amount. The conclusion 'more fertiliser makes plants taller' is weak because it ignores other variables. A stronger conclusion: 'Within the range tested, plant height increased with fertiliser concentration. Controlled experiments would be needed to confirm that fertiliser alone causes this effect, since light and water were not held constant.'
The Australian Institute of Marine Science publishes reef health reports where every conclusion is tightly tied to graphed data. Their scientists explicitly note limitations such as sampling location and time period, setting a standard for honest scientific communication.
Many students think a conclusion should simply repeat what the graph looks like. This is wrong. A conclusion interprets the pattern, connects it to scientific principles, and honestly states what the evidence can and cannot prove.
Click each sentence that supports the claim.
Speed Round · 6 questions
True or false? Tap as fast as you can. Build a streak.
The title and axis labels provide essential context for interpreting a graph.
Interpolation means estimating a value beyond the measured data range.
A plateau is a flat section where the dependent variable stops changing.
Extrapolation is always completely reliable.
A steeper gradient indicates a faster rate of change.
When describing a trend, saying 'it goes up' is specific enough for a scientific conclusion.
How are you completing this lesson?
Revisit the classroom CO2 graph from the opening scenario.
Write a short paragraph interpreting the graph, including a description of the trend, a proposed cause and one recommendation for the school.
Quick Check · 5 questions
Check Your Understanding · 3 questions
1. Describe the steps you would take before attempting to interpret any scientific graph.
2. A graph shows a steep line becoming flat. What does this tell you about the rate of change, and what might it mean in a reaction experiment?
3. Why is extrapolation less reliable than interpolation? Give an example where extrapolation might fail.
Show Your Working · 3 questions
SA1. Describe the process of interpreting a line graph, from reading the axes to drawing a supported conclusion.
SA2. Explain the difference between interpolation and extrapolation, and discuss why one is generally more reliable than the other.
Hint: Consider what assumptions each method makes about the data.
SA3. A graph of reaction rate against enzyme concentration rises steeply at first and then levels off. Interpret this shape and suggest a biological explanation.
Quick Check
1. B — Interpolation estimates a value between two known data points.
2. C — A plateau is a flat section on a graph.
3. B — The relationship may not continue outside the measured range.
4. B — The description links the variables directly.
5. B — The scale affects how dramatic the trend appears.
Show Your Working Model Answers
SA1 (5 marks): Read the title and axis labels to identify variables and units [1]. Check the scale on each axis [1]. Identify the overall trend and specific values [1]. Consider the gradient and what it means [1]. Draw a conclusion supported by evidence and mention limitations [1].
SA2 (4 marks): Interpolation estimates a value within the measured data range [1]. Extrapolation estimates beyond the measured range by extending the trend [1]. Interpolation is more reliable because it uses actual data points [1]. Extrapolation assumes the trend continues unchanged, which may fail if the relationship changes (e.g. plant growth slowing due to limited nutrients) [1].
SA3 (4 marks): The steep rise shows reaction rate increasing quickly with enzyme concentration [1]. The levelling off shows the rate stops increasing despite more enzyme [1]. This suggests a limiting factor such as substrate concentration running out [1]. Once all substrate is bound, adding more enzyme cannot increase the rate further [1].
Interpolation
Estimating within measured data
Extrapolation
Extending beyond measured data
Gradient
Rate of change between variables
Plateau
Flat section, no change
Origin
Zero point on both axes
Scale
Range and interval on axes
Put what you have learned to the test! Jump through the questions in game form.
Play GameYour Badges
0 of 6Mark lesson as complete
Tick when you've finished Learn, Practice and the game. Earns +85 XP and +25 coins.
Work through this topic 1-on-1 with an experienced HSC tutor.
Book a free session →