Lesson 3 of 8 / Practical and data skills
Make the pattern easy to see
Which graph makes your measurements answer the question?
In this lesson: Present raw data and processed results using appropriate tables, axes, scales and units.
About 5 min
The key ideaChoose a display that matches the variables, and keep measured values distinct from calculations and interpretation.
Work with the evidence
Let the variable choose the display
Reaction rate / arbitrary units
Temperature is quantitative. The line guides the eye between measured points; more measurements near the peak are needed to estimate the optimum closely.
Original illustrative data. Repeats and their variation are needed for a fuller evaluation.
Explanation
Record raw measurements before calculating a mean or rate. A table should identify the variables and put units in headings, so each value has an unambiguous meaning. Keep decimal places consistent with the measuring instrument for comparable raw readings. Preserve the individual repeats rather than replacing them with only an average.
For a quantitative relationship such as temperature against reaction rate, use a graph with the independent variable on the horizontal axis and the dependent variable on the vertical axis. Label both axes with quantities and units, use a sensible scale and plot points accurately. Use a line or curve that represents the pattern appropriately; do not force a straight line through an obviously curved relationship.
Separate categories, such as different plant species, are suited to a bar chart when comparing a response. A scatter plot of paired measurements helps inspect an association. A histogram represents frequencies over continuous intervals; adjacent bars are not separate named categories. The meaning of the horizontal axis determines the choice.
An anomaly is a result that differs from the pattern or comparable repeats. Check the record and method, and investigate or repeat where possible. Do not silently erase an inconvenient value. Explain any decision to exclude it and consider how that decision affects the conclusion.
Interpolation estimates within the measured range. Extrapolation extends beyond it and is less secure because the biological relationship may change. A graph with no measurements near an apparent optimum cannot establish its exact position.
Step by step
- 1
Identify the variables
Decide whether values are quantitative, categories or frequency intervals.
- 2
Choose and label the display
Use appropriate axes, units, scale and points or bars.
- 3
Describe only what the data support
Use values from the measured range and flag uncertain extrapolation.
Worked example
Work through the evidence
An enzyme rate is measured at 10, 20, 30 and 40 degrees C. The highest measured rate is at 30 degrees C. Can you report an exact optimum of 30 degrees C?
One way to explain it
The highest measured rate was at 30 degrees C. The true optimum could lie between tested temperatures. Use additional values around the peak, with repeats and temperature control, to estimate it more closely.
Why this answer works
- Separate the highest sampled point from an exact optimum.
- Identify the missing resolution in the independent variable.
- Propose additional measurements where they are informative.
Is this true? "Every set of plotted points should be joined by straight segments."
The display and fitted relationship should match the data and question. A best-fit line or smooth curve may be appropriate; categorical bars do not imply intermediate values.