OCR Gateway GCSE Chemistry A (J248) · Practical Skills
Mini-Lesson
Practical Skills
This mini-lesson walks you through Working Scientifically for the OCR Gateway Practical Activity Groups (PAGs): choosing variables, telling accuracy from precision, spotting errors, calculating uncertainty, and reading titres and graphs — all with real chemistry.
Work through each screen, answer the questions as you go (some are wordy, some are calculations) and collect ⭐ stars. Press Start when you're ready.
Planning an investigation
Three kinds of variable
Before you touch any apparatus, decide what you will change, measure and keep the same. Every PAG that's an investigation has the same three roles:
Independent variable — the one thing you deliberately change.
Dependent variable — the thing you measure in response.
Control variables — everything you keep the same to make it a fair test.
In a rates PAG you might change temperature, measure gas given off, and control concentration and volume.
Watch out: a test is only fair (and the result valid) if you change one variable at a time. Change two and you can't tell which caused the effect.
Quick check
Spot the variable
?A student measures how the temperature of acid changes the time for magnesium to dissolve, keeping the acid concentration and volume fixed. What is the dependent variable?
Making & recording measurements
Units, resolution & repeats
Good data starts with the right kit and the right habits. Always record an SI unit and stay within an instrument's resolution (the smallest change it can show):
Mass — balance, in g (resolution often 0.01 g).
Volume — measuring cylinder, pipette or burette, in cm³.
Temperature — thermometer, in °C.
Time — stopwatch, in s.
A clear table: independent variable on the left, repeats in the middle, a mean on the right. Always head columns with a quantity / unit.
Why repeat? Doing each measurement two or three times and taking a mean reduces the effect of random error and lets you spot anomalies.
Sort it
Random or systematic?
Tap whether each problem is a random error (scattered, unpredictable) or a systematic error (shifts every reading the same way).
Quality of data
Accuracy vs precision
These two words are not the same — examiners love testing the difference:
Accurate — close to the true value.
Precise — readings are close to each other (tightly clustered), whether or not they're correct.
The bullseye is the true value. Tight cluster = precise; centred on the middle = accurate.
Watch out: data can be precise but wrong (a tight cluster off-centre — usually a systematic error). Precision is about repeatability; accuracy is about the true value. They are different ideas.
Quick check
Reading the target
?A burette is misread so every titre comes out 0.30 cm³ too high, but the four repeats agree to within 0.05 cm³. Which best describes this data?
Sources of error
Random vs systematic error
Two families of error spoil measurements, and they behave differently:
Random error — unpredictable scatter (e.g. judging when a colour change happens). Repeat & mean to reduce it.
Systematic error — shifts every reading the same way (e.g. a balance not zeroed). Recalibrate / re-zero to fix it.
A balance reading 0.04 g with an empty pan has a zero error: every mass will be 0.04 g too high.
Watch out: a zero error is a systematic error, not a random one — it affects every reading identically, so repeating and averaging will not remove it. You must re-zero (tare) the balance.
Calculate
Mean — but spot the anomaly
1In a rates experiment a student collects gas: 18, 20, 32, 19 cm³. One result is a clear anomaly. Calculate the mean of the remaining results.
cm³
Hint: 32 is the anomaly — ignore it. Mean = (18 + 20 + 19) ÷ 3.
PAG 6 · technique
Reading a burette (titration)
In an acid–alkali titration you run acid from a burette into a fixed volume of alkali (added with a pipette) until the indicator just changes. The volume of acid used is the titre.
Read at eye level from the bottom of the meniscus, to the nearest 0.05 cm³.
Watch out: a burette is read to 0.05 cm³ (not 0.1) — its graduations are every 0.1 cm³, so you can estimate to the half-division. Read it at eye level or you get a parallax (systematic) error.
Calculate
The concordant mean titre
2A titration gives titres of 24.10, 24.05, 26.50 and 24.15 cm³. Using only the concordant titres (within 0.10 cm³ of each other), calculate the mean titre.
cm³
Hint: 26.50 is the rough/odd one out — drop it. Mean = (24.10 + 24.05 + 24.15) ÷ 3.
Uncertainty
How sure are you?
Every measurement has some uncertainty — a band the true value probably lies in. For a set of repeats, a simple estimate is half the range:
uncertainty = range ÷ 2range = largest value − smallest value (of your concordant repeats)
You quote it as mean ± uncertainty. Tighter clustering (more precise data) gives a smaller uncertainty.
Range = 24.15 − 24.05 = 0.10 cm³, so uncertainty = 0.10 ÷ 2 = 0.05 cm³.
Result: 24.10 ± 0.05 cm³.
Calculate
Your turn — uncertainty
3Four repeat masses of a salt are 2.48, 2.51, 2.49, 2.52 g. Calculate the uncertainty using uncertainty = range ÷ 2.
g
Hint: range = 2.52 − 2.48 = 0.04 g. Uncertainty = 0.04 ÷ 2.
Presenting & processing data
Graphs, best-fit & gradient
Use a bar chart for categories (e.g. mass of salt from different acids) but a line graph when both variables are continuous (e.g. volume of gas vs time). Then:
Draw a line of best fit — a smooth line with roughly equal points either side.
Ignore anomalies when drawing it (circle them, don't let them pull the line).
Find the gradient with a big triangle: gradient = rise ÷ run.
Line of best fit (blue), a circled anomaly left off the line, and a gradient triangle (green).
Watch out: the line of best fit does not have to pass through every point and must ignore anomalies. The gradient gives the rate — here, the rate of gas production.
Calculate
Read the gradient
4On a volume–time graph, the line of best fit rises from the point (10 s, 15 cm³) to (50 s, 75 cm³). Calculate the gradient (the rate, in cm³/s).
The PAGs need you to pick the correct technique to separate or purify a mixture:
Filtration — separates an insoluble solid from a liquid (residue vs filtrate).
Crystallisation — recovers a soluble salt by evaporating the solvent.
Distillation — separates a liquid from a solution by boiling & condensing.
Chromatography — separates a mixture of dyes by how far each travels.
Filtration: the insoluble residue is trapped in the paper; the liquid filtrate passes through.Quick check
Choose the technique
?You have made copper sulfate solution (a soluble salt dissolved in water) and want to obtain dry crystals. Which technique should you use?
Safety & risk assessment
Hazards, risks & control
A risk assessment names the hazard (what could cause harm), the risk (chance of it happening) and a control measure (how you reduce it). Chemicals carry standard hazard symbols:
Common hazard symbols: corrosive, flammable and toxic. A typical control: wear eye protection and use a fume cupboard.
Worked example (making a salt): dilute sulfuric acid is irritant/corrosive, so a control is to wear safety goggles; the Bunsen flame is a burn hazard, so tie hair back and use tongs.
Quick check
Control the risk
?The hazard when heating dilute acid in a beaker is that hot acid may spit into your eyes. Which is the best control measure?
Conclusions & evaluation
From data to a verdict
A good conclusion answers the question using the data and links back to the chemistry. A good evaluation judges how much to trust it:
Repeatable — the same person with the same kit gets close results again.
Reproducible — a different person or method gets close results too.
Valid — the experiment was a fair test that actually answered the question.
Suggest improvements: more repeats, smaller intervals, better-resolution apparatus.
If results hold up both ways, the conclusion is reliable.
Watch out: taking more repeats improves reliability and reduces random error, but it will not fix a systematic error — you fix that by re-calibrating the apparatus.
Match up
Term ↔ definition
Tap a term on the left, then its matching definition on the right.
Recap
The skills to know
Variables: change = independent · measure = dependent · keep same = control (fair test)
Accuracy = close to true value; precision = readings close together
Errors: random → repeat & mean · systematic (incl. zero error) → re-calibrate
Uncertainty = range ÷ 2, quoted as mean ± uncertainty
Titration: read burette to 0.05 cm³; mean only the concordant titres
Graphs: line of best fit ignores anomalies; gradient = rise ÷ run