IB Biology HLStage 2 — Collect & Process DataIA & Paper 2Practical skill~12 min read
Collecting Data
This is the doing phase — the part where you finally run the experiment you spent so long designing. The job now is to come away with raw data that is honest, precise and complete, including the things you noticed as well as the things you measured.
📚 What you need to know
Quantitative data is numerical data you measure. Qualitative data is what you observe but cannot put a number on.
Your raw data table is the foundation of the report. It comes first, and it contains only direct measurements — no calculations.
Design the raw data table before you start, not afterwards.
It needs a specific title, clearly labelled columns for the IV and DV, and units and uncertainties in the column headers, not in the body.
Record every value to the correct precision of the instrument — 1.50 g from a two-decimal-place balance, not 1.5 g.
Sufficient data means at least five increments of the independent variable and at least three replicates each, ideally five.
Qualitative observations are evidence. They often explain a result that otherwise looks wrong.
If something goes wrong, record it and respond to it. Never erase an anomalous result.
The raw data table
The raw data table is the first table in your report and the one everything else is built from. If it is wrong, every calculation after it inherits the problem.
The independent variable goes in the left-hand column, in order. Each replicate gets its own column, so nothing is averaged before it has been written down.
Requirement
What it looks like in practice
A specific title
It names both variables and the organism, not just “Results table”
Labelled columns
The independent variable on the left, then one column per replicate of the dependent variable
Units and uncertainties in the header
“Time / s (±0.2)” at the top, so the body of the table holds nothing but numbers
Direct measurements only
Initial and final mass, not the change in mass. The change is a calculation and belongs in the next table
Enough data
At least five values of the IV, at least three replicates each, and five replicates if you can manage it
Doing the sums in your head as you go, and only writing down the answer, is the fastest way to lose marks in this section. The assessor cannot check a calculation they cannot see, and if you have thrown away the original readings there is no way back.
Recording to the right precision
Your instrument decides how many decimal places you write. Writing fewer throws away information you actually collected; writing more claims precision you never had.
The trailing zero in 1.50 g is not decoration. It says the balance could tell the difference between 1.50 and 1.51, and that is real information.
Every value in one column, the same way. If one mass is 1.50 g, none of the others may be written as 1.5 g. A column with mixed precision looks careless even when the readings are right.
Qualitative observations
Qualitative data is everything you noticed but could not put a number on. It is not filler, and it is not an afterthought. It is often the only thing that explains a result which otherwise looks like a mistake.
Type of observation
Example
What it can explain later
Turgidity of plant tissue
Potato cylinders feeling firm and stiff, or soft and limp
Whether water moved in or out, backing up your mass data
Colour
Leaves yellowing from a mineral deficiency
Why a plant’s growth rate was lower than expected
Behavioural response
Woodlice moving steadily away from a light source
The direction of a response, not just the count in each half
Texture or appearance
A cloudy milk suspension turning clear
How far a reaction actually went, and whether it finished at all
Here is the pattern that earns marks later. Your numbers say the mass gain in pure water was smaller than expected. Your observation says the cylinders already felt soft and floppy at the start. Put the two together and you have a real explanation: the tissue was partly dehydrated before you began.
When the experiment misbehaves
Biological experiments rarely run perfectly. Noticing a problem and responding to it sensibly is a scientific skill in itself — and it only counts if you write it down.
The extra trial is what turns a suspicion into evidence. Two readings agreeing and one disagreeing is a much stronger case than one odd number on its own.
Problem
How to respond
The reaction is far too fast or too slow
Adjust the enzyme or substrate concentration until the rate is measurable, then record the change you made and the reason for it
One repeat gives a wildly different result
Record it, then run an additional trial so you end up with a set of concordant results. Do not delete anything
Organisms are not behaving as expected
In fieldwork, empty quadrats may mean you need to reconsider the sampling location. Record that decision and your reasoning
A sample is prepared wrongly
Discard it and prepare a replacement before starting, so every sample really is comparable. Note what happened
WE 1
Designing the header row
A student will time how long a filter paper disc soaked in catalase takes to rise in hydrogen peroxide, at five concentrations, with three repeats. Write a suitable set of column headers for the raw data table. (3 marks)
Step 1: independent variable on the left, with unit and uncertainty
Concentration of hydrogen peroxide / % (±0.05)
Step 2: one column per replicate of the dependent variable
Time for disc to rise, trial 1 / s (±0.2)
Time for disc to rise, trial 2 / s (±0.2)
Time for disc to rise, trial 3 / s (±0.2)
Step 3: check what is missing
No mean column, and no rate column — those are calculations, so they belong in the processed table.
Four columns, units and uncertainties in the headers, no calculated valuesthe ±0.2 s allows for reaction time, not just the stopwatch display — say so if asked
WE 2
Correcting how readings were recorded
A student records these masses from a balance that reads to two decimal places: 2.4 g, 2.37 g, 2.400 g. Explain what is wrong and rewrite them. (3 marks)
Problem 1: too few decimal places
2.4 g throws away a digit the balance actually gave, and it does not match the rest of the column.
Problem 2: too many decimal places
2.400 g claims the balance can read to 0.001 g, which it cannot. That is dishonest precision.
Step 3: match every value to the instrument
All three must be written to two decimal places.
2.40 g, 2.37 g, 2.40 gconsistency down a column is the quick check — every entry should have the same number of decimal places
WE 3
Responding to an odd reading
In the beetroot investigation, the three absorbance readings at 50 °C are 0.40, 0.71 and 0.43. Describe how the student should respond, during the practical. (3 marks)
Step 1: record it as it stands
Write 0.71 into the table and mark it as possibly anomalous. Do not erase it.
Step 2: get more evidence
Run a fourth trial at 50 °C. It gives 0.43, which agrees with the other two.
Step 3: note a possible cause
Record a likely reason — for example the disc was cut from tissue that had already been damaged, releasing extra pigment before the water bath.
Record it, run a fourth trial, note the probable causeyou do not exclude it yet — that decision happens on the next page, and it has to be justified
💡 Exam tips
Draw the raw data table before the practical, then you only have to fill boxes in.
Units and uncertainties belong in the header. Never write “g” after every number in the body.
Write down the actual readings, including initial and final values — not the change.
Keep every value in a column to the same number of decimal places.
Keep a running set of observations as you go. Trying to remember them afterwards never works.
Record anything you changed mid-experiment and why. That is evidence of good practice, not an admission of failure.
⚠ Common mistakes
Doing calculations on scrap paper and only recording the answers. The raw readings are gone for good.
Putting a mean or a percentage change in the raw data table. Those are processed values.
Rubbing out an anomaly. Record it, then justify excluding it later if you can.
Writing 1.5 g from a two-decimal-place balance. The zero matters.
Ignoring qualitative observations, then having nothing to explain a strange result with.
Only three values of the independent variable because you ran out of time. Plan the timing at the pilot stage.
Up next: Processing Data — turning those raw readings into means, rates and standard deviations, with the working shown and the significant figures under control.
Want this explained one-to-one?
Book a free session with an experienced IB Biology tutor and get your trickiest topics made simple.
