Collecting Data in Biology (DP IB Biology): Revision Note
Collecting data in Biology
This is the "doing" phase of your investigation where you perform the experiment you have carefully designed
Your goal is to gather high-quality raw data that is both accurate and sufficient to answer your research question
This involves making precise measurements and recording all relevant information, including both numbers and observations
Principles of data collection
Collect and record sufficient relevant quantitative data
Quantitative data is numerical data that you measure in your experiment
The foundation of your report is a raw data table.
This should be the first table you present and must contain only the direct measurements you take, with no calculations
Designing your raw data table before you start is crucial
A well-designed table must include:
A specific title that describes the experiment.
Clearly labelled columns for your independent and dependent variables
Units and uncertainties in the column headers, not in the body of the table
Data must be recorded to the correct precision of the instrument
This is a common place where students lose marks
For a digital balance that reads to two decimal places, all masses must be recorded to two decimal places (e.g., 1.50 g, not 1.5 g)
For a graduated cylinder with 1 cm3 divisions, a volume should be recorded to the nearest 0.5 cm3
Sufficient data means collecting enough data points to see a trend
This includes:
collecting data for at least five increments of your independent variable
carrying out at least three replicates (and ideally five or more in biology) for each increment to ensure reliability
Identify and record relevant qualitative observations
Qualitative data is non-numerical data that you observe during the experiment
These observations provide context and are crucial for your final analysis and evaluation
Do not underestimate the importance of qualitative data
It can help explain unexpected results or errors
Examples of important qualitative data in biology include:
the turgidity of plant tissue (e.g. potato cylinders feeling firm and stiff or soft and limp).
the colour of leaves (e.g. yellowing due to a mineral deficiency).
behavioural responses of organisms (e.g. woodlice moving away from a light source).
the texture or appearance of a substance (e.g. a cloudy solution of milk turning clear in an enzyme experiment).
Identify and address issues that arise during data collection
Biological experiments rarely go perfectly to plan
A key scientific skill is to notice and respond to issues as they happen
If you encounter a problem, do not ignore it
Record the issue in your lab notes
Examples of issues and how to address them:
The reaction is too fast or slow:
You may need to adjust the concentration of an enzyme or substrate to get a measurable rate
Record the change and the reason for it
An anomalous result (outlier):
If one of your repeat trials gives a result that is very different from the others, record it, and then conduct an additional trial to get a reliable set of concordant results
Do not erase the outlier; you will justify its exclusion later
Organisms are not behaving as expected
In an ecological study, if you find no organisms in your quadrats, you may need to reconsider your sampling location
Record this decision and your reasoning
Worked Example
Research question:
"What is the effect of pH (from pH 4 to pH 10) on the rate of activity of the enzyme trypsin in breaking down casein protein?"
Quantitative data:
The time taken for a casein suspension to become transparent after adding trypsin solution
pH (±0.1) | Time (Trial 1) /s (±0.2) | Time (Trial 2) /s (±0.2) | Time (Trial 3) /s (±0.2) | Time (Trial 4) /s (±0.2) |
|---|---|---|---|---|
4.0 | 185.4 | 182.9 | 184.1 | — |
5.0 | 158.3 | 160.2 | 159.0 | — |
6.0 | 102.5 | 101.8 | 103.1 | — |
7.0 | 63.4 | 62.8 | 63.0 | — |
8.0 | 46.9 | 52.6 (anomalous) | 47.0 | 47.1 |
9.0 | 65.1 | 64.8 | 65.9 | — |
10.0 | 150.5 | 148.8 | 149.3 | — |
Qualitative data:
At pH 4.0 and 5.0, the casein suspension remained cloudy for a long time, showing low enzyme activity
Between pH 6.0 and 8.0, the solution cleared much more rapidly, with the fastest reaction at pH 8.0 — suggesting this is near the optimum pH for trypsin
At higher pH values (9.0–10.0), the reaction slowed again, and the solution stayed slightly opaque, indicating that trypsin was beginning to denature
Issue addressed during collection:
At pH 8.0, Trial 2 gave a time of 52.6 s, which was noticeably longer than the other two (46.9 s and 47.0 s)
A fourth trial was performed, giving 47.1 s, confirming that Trial 2 was an anomalous result, likely caused by incomplete mixing when the enzyme was first added
Worked Example
Research question:
"What is the effect of sucrose concentration (from 0.0 M to 1.0 M) on the percentage change in mass of potato (Solanum tuberosum) cylinders after 24 hours?"
Quantitative data:
The raw data would be recorded in a table like the one below, showing all initial and final mass readings for each replicate cylinder
Sucrose Conc. / M | Replicate | Initial Mass / g (±0.01) | Final Mass / g (±0.01) |
|---|---|---|---|
0.0 | 1 | 1.85 | 2.12 |
2 | 1.88 | 2.16 | |
3 | 1.86 | 2.14 | |
0.2 | 1 | 1.91 | 2.02 |
2 | 1.89 | 1.99 | |
3 | 1.87 | 1.98 | |
... | ... | ... | ... |
Qualitative data:
The potato cylinders placed in the 0.0 M sucrose solution (distilled water) felt very firm and stiff (turgid) after the 24-hour period
The potato cylinders placed in the 1.0 M sucrose solution felt very soft and limp (flaccid)
Issue addressed during collection:
When cutting the potato cylinders, one cylinder for the 0.4 M solution was accidentally cut too short (2.5 cm instead of 3.0 cm)
This cylinder was discarded and a new one was cut to the correct dimensions before the experiment began to ensure all cylinders had the same surface area to volume ratio
Examiner Tips and Tricks
Record raw data directly
Never perform calculations in your head or on scrap paper
Your raw data table must show the actual measurements you took (e.g., initial and final mass, not just the change in mass)
Units and uncertainties belong in the headers
This is the correct scientific convention and makes your tables clear and easy to read
Avoid writing units after every number in the table body
Your observations are evidence
Don't treat qualitative data as an afterthought
Good observations can be used as evidence in your conclusion and evaluation to explain why your results might differ from what you expected
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