A-Level Biology Practical Terms
Your interactive visual glossary of every practical-skills term examiners test – accuracy, precision, reliability, errors and uncertainty – with diagrams, a percentage-error calculator and quick quizzes. Every UK exam board.
Last updated: February 2026
Practical Terms: The Vocabulary That Wins Practical Marks
Up to 15–20% of your A-Level Biology marks come from practical skills, and many are won or lost on precise vocabulary. Examiners apply specific accept/reject rules to words like accuracy, precision, reliability, validity, systematic error and uncertainty.
This visual glossary defines every practical term you need with a clear diagram for each, plus an interactive calculator and two quizzes. It applies to every UK exam board.
Accuracy vs Precision
Interactive: Accuracy vs Precision Trainer
This is the distinction examiners test most. Look at where the shots land on the target, decide whether the data is accurate and/or precise, then check your answer. The bullseye is the true value.
Systematic vs Random Error
Reliability, Repeatability & Reproducibility
How to improve reliability
- Increase repeats and calculate a mean
- Control all other variables
- Standardise your method
- Use equipment with better resolution
- Reduce human judgement (e.g. a colorimeter)
- Get others to reproduce your results
Resolution & Choosing Apparatus
Uncertainty & Percentage Error
Try it: Percentage Error Calculator
Enter a reading and the smallest division (resolution) of your instrument. The uncertainty is ± half the smallest division.
Recording Data: Decimal Places, Significant Figures & Rounding
Anomalies, Validity, Consistency & Variables
Try it: Systematic or Random?
Read the scenario and decide whether it describes a systematic or a random error.
Quick-Reference Glossary
Every key practical term in one place – learn these one-line definitions for fast recall.
| Term | One-line definition |
|---|---|
| Accuracy | How close a measurement is to the TRUE value |
| Precision | How close repeated measurements are to EACH OTHER |
| Reliability | Repeatable + reproducible = trustworthy |
| Repeatability | Same person, same setup → same results |
| Reproducibility | Different person, different setup → same results |
| Valid conclusion | Fair test: only one variable changed |
| Consistency | Results agree with each other (small range) |
| Systematic error | Same shift every time (can’t fix by repeating) |
| Random error | Unpredictable scatter (fix with more repeats) |
| Resolution | Smallest change an instrument can detect |
| Uncertainty | ± half the smallest division |
| Percentage error | (uncertainty ÷ reading) × 100 |
| Anomalous result | Doesn’t fit the pattern (circle + investigate) |
| Decimal places | Match the instrument’s resolution |
| Significant figures | Digits that carry real meaning |
| Rounding | Only at the END of a calculation |
Practical Vocabulary Costing You Marks?
Accuracy vs precision, systematic vs random, reliability vs validity – these distinctions earn marks on every paper, and they’re easy to get wrong. As a former examiner I’ll show you exactly how these terms are marked and drill them until they’re second nature.
Tyrone John • CBiol MRSB • Former WJEC/Eduqas & Edexcel Examiner • 25+ Years Teaching A-Level Biology
Book a Free ConsultationFrequently Asked Questions – Practical Terms
What is the difference between accuracy and precision?
Accuracy is how close a measurement is to the true value, while precision is how close repeated measurements are to each other, regardless of the true value. They are independent: data can be precise but not accurate (tightly clustered but all wrong, often due to a systematic error) or accurate but not precise (scattered but averaging near the true value). In a good experiment you want both. Using these two terms correctly is a frequent marking point.
What is the difference between systematic and random error?
A systematic error is the same error in the same direction every time, which shifts all your results and affects accuracy – for example a balance that is not zeroed or a thermometer reading 2°C too high. You cannot fix it by repeating; you must recalibrate or change the method. A random error is unpredictable scatter on either side of the true value, which affects precision – for example reaction-time variation or biological variability. You reduce random error by taking more repeats and calculating a mean.
What is the difference between reliability and validity?
Reliability is about consistency – results are reliable if they are repeatable (same person and equipment) and reproducible (different person and equipment). Validity is about whether you are actually measuring what you intended, which depends on a fair test where only the independent variable is changed and all control variables are kept constant. An experiment can be reliable but not valid, or valid but unreliable, so the two terms are not interchangeable.
How do you calculate percentage error?
Percentage error equals the uncertainty divided by the reading, multiplied by 100. The uncertainty is usually plus or minus half the smallest division of the instrument. Because percentage error depends on the size of the reading, you can reduce it by measuring a larger quantity (the same fixed uncertainty is a smaller percentage of a bigger value) or by using apparatus with a higher resolution. Suggesting this is a common and reliable way to gain marks in evaluation questions.
How many significant figures or decimal places should I use?
When recording raw data, match the resolution of the instrument – no more decimal places than it can actually measure, and no fewer (including trailing zeros, so a balance reading of 2.50 g is written as 2.50 g, not 2.5 g). For calculated answers, use significant figures: your final answer should have no more significant figures than your least precise measurement, and at A-Level two to three significant figures is usually appropriate. Always round only at the end of a calculation, never in the middle.