OCR GCSE Biology A: Working scientifically: planning, recording, presenting and evaluating practical data (J247) – Revision Notes

These are quick-recall notes for the working scientifically section (5e) of the OCR GCSE (9-1) Gateway Science Biology A (J247) specification, Version 4.0 (August 2026): practical skills 2a to 2d plus statements 1.2, 1.3 and 1.4 as used in the Topic B7 practicals. None of it is marked Higher Tier only. The study guide has the full explanations and longer worked examples.

Links: OCR GCSE Biology hub, printable checklist, practice questions, PAG 1 to 4 guide, PAG 5 to 8 guide and the free 10-minute diagnostics.

The cycle in one line

Theory, then hypothesis, then plan, then measure, then record, then present, then analyse, then conclude, then evaluate, then improve. The specification also says science needs peer review and communication of results, and that risk should be evaluated.

Key definitions

Term	Meaning
Hypothesis	A testable explanation built from scientific theory (1.2a)
Prediction	What you expect to observe if the hypothesis is right
Independent variable	The one you change
Dependent variable	The one you measure
Control variable	Kept the same so the test is fair
Control group	Receives no treatment, for comparison
Anomaly	A result that does not fit the pattern
Accuracy	Closeness to the true value
Precision	Closeness of repeats to each other
Repeatability	Same person, method and equipment give the same results
Reproducibility	Different person, method or equipment give the same results
Random error	Unpredictable scatter; reduced by repeats and a mean
Systematic error	The same shift in every reading; repeats do not remove it
Resolution	The smallest change an instrument can show
Correlation	A link between two variables, not proof of cause

Method in steps: planning an investigation

1. State the hypothesis from the theory and the prediction.
2. Name the independent and dependent variables, and say how each is measured.
3. List control variables and how each is held constant.
4. Choose apparatus with a suitable resolution: a syringe or measuring cylinder for small volumes, not a beaker.
5. Decide the range and number of values of the independent variable (at least five if possible).
6. Decide repeats and sample size; say how samples are chosen at random.
7. Include a control group.
8. Name risks and one precaution for each.
9. Draw an empty results table with headings and units.
10. State how the data will be processed (a mean, a percentage change, a graph).

Sampling (1.2d)

• Representative sample: take at random, not by choice.
• Fieldwork: random coordinates for quadrats, enough quadrats, an identical quadrat size.
• Bigger sample, better estimate.
• Density = mean count per quadrat / quadrat area. Population estimate = density x total area.

Recording and tables

Do	Avoid
Independent variable in the first column	Mixing the order of columns
Units in the column heading only	Units in every cell
Same decimal places as the instrument allows	24.00 from a ruler marked in mm
Record repeats, then the mean	Averaging an anomaly without comment
Note qualitative observations	Recording on scrap paper

Averages and spread (1.3c, 1.3d)

Measure	How
Mean	Total / number of values
Median	Middle of the ordered list; for an even count, the mean of the middle two
Mode	Most frequent value
Range	Largest minus smallest
Uncertainty estimate	Half the range, written as mean ± half range

Worked reminder. Four repeat readings are 5.1, 5.4, 5.2 and 5.3. The total is 21.0, the mean is 5.25, the range is 0.3 and the half-range is 0.15, so the result is 5.25 ± 0.15.

Anomalies. Say that it is anomalous, say why you think so, repeat it if possible, and leave it out of the mean while stating that you did.

Graphs and charts (2c, 1.3a, 1.3b)

Data	Form
Two continuous variables	Line graph or scatter graph
Category on the x axis	Bar chart, bars with gaps
Grouped continuous data	Histogram, bars touching
Structure	Labelled diagram in pencil with ruled label lines

Checklist for plotting: axes the right way round, labelled with quantity and unit, even scale using over half the grid, small crosses for points, a line of best fit (not dot-to-dot unless the pattern is clearly not a straight line), and a title.

Describe a trend in three parts: the general pattern, a quoted value or two with units, and any change in the pattern (levels off, peaks, falls).

Rate and gradient (M4 skills)

• Rate = amount changed / time taken.
• Gradient of a straight line = change in y / change in x.
• For a straight line y = mx + c, the gradient is m and the y-axis crossing point is c.
• A steeper line means a faster rate. A line that flattens means the rate has fallen to zero or a factor has run out.
• Extrapolation beyond the data is a prediction, not a measurement.

Worked reminder. 8.4 cm³ of gas collected in 7 minutes gives 8.4 / 7 = 1.2 cm³ per minute.

Units, prefixes and magnification (1.4)

Prefix	Symbol	Factor	Convert
tera, giga, mega	T, G, M	10¹², 10⁹, 10⁶	1 Gm = 10⁹ m
kilo	k	10³	1 km = 1000 m
deci	d	10⁻¹	1 m = 10 dm
centi	c	10⁻²	1 m = 100 cm
milli	m	10⁻³	1 mm = 1000 µm
micro	µ	10⁻⁶	1 µm = 1000 nm
nano	n	10⁻⁹	1 nm = 10⁻⁹ m

• Magnification = image size / real size. Rearrange: real size = image size / magnification.
• Put both sizes in the same unit before dividing.
• Standard form: 0.00042 m = 4.2 x 10⁻⁴ m.
• Significant figures: give no more than the least precise data. 0.04567 to 2 significant figures is 0.046.
• Percentage change = (new - old) / old x 100. A negative answer is a decrease.

Worked reminder. An image 24 mm long at x80: real size = 24 / 80 = 0.30 mm = 300 µm.

Error types, with an example each

Source	Type	Fix
Reading a scale from an angle	Random or systematic, depending on whether the angle is always the same	Read at eye level
Thermometer reads 2 °C too high	Systematic	Calibrate, or compare with another thermometer
Different seedling sizes	Random	Bigger sample, mean
Timer started late every time	Systematic	Start together with the reaction

Evaluation formula

Weakness, then effect on the data, then a specific fix. For example: “the lamp warmed the water (weakness), so the rate rose because of temperature as well as light (effect); put a water-filled beaker between the lamp and the tube (fix).”

A conclusion refers to the data, matches the hypothesis, and goes no further than the evidence.

Quick self-test

1. Find the mean of 12, 15, 14, 13 and 16.
2. Find the median of 8, 3, 9, 5, 5 and 7.
3. A mass falls from 4.0 g to 3.4 g. Give the percentage change.
4. Convert 0.35 mm to micrometres.
5. A cell is 120 µm long and its image is 36 mm. Calculate the magnification.
6. A real cell is imaged at x80 as 24 mm. Find its real length in µm.
7. State how precision differs from accuracy.
8. Which type of chart suits the number of snails in each of four named habitats?
9. A line of best fit passes through (0, 0) and (7, 8.4). Give the gradient with its meaning.
10. A ruler reads 1 mm too high in every measurement. Is this random or systematic error?
11. Write 0.00042 m in standard form.
12. Give one reason for taking samples at random.

Answers

1. Total 70, mean = 14.
2. Ordered: 3, 5, 5, 7, 8, 9; median = (5 + 7) / 2 = 6.
3. (3.4 - 4.0) / 4.0 x 100 = -15%, a 15% decrease.
4. 0.35 x 1000 = 350 µm.
5. 36 mm = 36 000 µm; 36 000 / 120 = x300.
6. 24 mm / 80 = 0.30 mm = 300 µm.
7. Precision is closeness of repeats to each other; accuracy is closeness to the true value.
8. A bar chart, because the habitats are categories.
9. 8.4 / 7 = 1.2, meaning 1.2 cm³ per unit of time (rate).
10. Systematic, because every reading shifts by the same amount.
11. 4.2 x 10⁻⁴ m.
12. It avoids bias, so the sample represents the whole population.

Where marks are usually lost

• Listing “same conditions” without naming the variable and how it is kept constant.
• Describing a graph without quoting any values.
• Labelling a result “accurate” when only the repeats agree.
• Treating an anomaly as part of the mean without comment.
• Dot-to-dot lines on a scatter graph that has a clear overall trend.
• Dividing a size in mm by a size in µm.
• Forgetting units on a rate, which is amount per time.
• Saying “human error” without naming the actual mistake.
• Concluding that one variable causes another from correlation alone.
• Giving an improvement such as “be more careful” instead of a specific change.

Official syllabus

OCR GCSE (9-1) Gateway Science Biology A (J247), Version 4.0 (August 2026), first assessment 2018, published by OCR: section 5e Working scientifically (statements 1.2, 1.3, 1.4 and 2a to 2d), section 5f mathematical skills, and Topic B7 Practical skills.