How to Write a Lab Report

A lab report answers one question for the reader: what did you do, what did you find, and what does it mean?

A lab report communicates an experiment clearly enough that someone else could understand it, judge it, and in principle repeat it. Most follow the same structure across the sciences. Knowing what belongs in each section — and, just as important, what doesn’t — is most of the battle, because the commonest mistakes are putting the right information in the wrong place.

Title, aim, and hypothesis

The title should describe the experiment specifically, not vaguely — “The effect of temperature on the rate of catalase activity” tells the reader more than “Enzyme experiment.” State the aim — what the experiment set out to investigate — and, where relevant, a testable hypothesis that predicts a relationship you can confirm or reject with data. A good hypothesis names the variables and the expected direction of the effect.

Introduction

Give the reader the background needed to understand the experiment: the relevant theory, key terms, and why the question matters. Build toward your aim and hypothesis so they arrive as the logical endpoint of the introduction, not as a surprise. Keep it focused — this is context, not a literature review — and cite any theory or prior work you draw on.

Method (materials and procedure)

Describe what you did in enough detail that the experiment could be reproduced — the materials, the apparatus, the quantities, and the steps in order. Write it in the past tense and, in most disciplines, the passive voice (“the solution was heated to 40°C”), because the focus is the procedure, not you. Don’t write it as a numbered set of instructions to the reader; describe what was actually done. Note any controls and how you kept other variables constant, since that’s what makes your results trustworthy.

Results

Present your findings — but don’t interpret them yet. Put data in clearly labelled tables and figures, each with a caption, correct units, and a figure or table number, and refer to them in the text (“as shown in Figure 1”). Report the key trends in words — the direction, the size of the effect, anything unexpected — but resist explaining why; that’s the discussion’s job. Every table or graph should be readable on its own and legible in greyscale, since many reports are printed in black and white.

Discussion

This is where the marks are. Explain what the results mean, whether they support your hypothesis, and how they fit the underlying theory. Compare your findings with what the theory or previous studies would predict. Then be honest about limitations and sources of error — what could have affected the results, whether the errors were random or systematic, and how a future study might improve. A discussion that engages critically with imperfect data is far stronger than one that pretends everything went perfectly.

Conclusion and references

Close with a short conclusion that answers the aim directly and states what the experiment showed — no new information, no fresh data. Then list every source you cited, in the required style. Throughout, favour precision over length: a clear, well-labelled report always beats a long, cluttered one, and examiners reward the report they can follow without effort.

Present results without interpreting them

The results section reports what happened; the discussion says what it means. Keeping them separate is the single most common structural requirement, and merging them is the most common structural error. Results contain the data, the tables, the figures and the statistical outcomes — stated plainly, without explanation of significance.

Every table and figure needs a number, a caption and units, and each must be referred to in the text. A figure the text never mentions is decoration; text describing data that appears nowhere is unsupported.

Report numbers with appropriate precision

Precision should reflect the measurement, not the calculator. Reporting a mean to six decimal places when the instrument reads to one implies an accuracy you do not have. Carry units throughout, state uncertainty where the discipline expects it, and be consistent about significant figures across comparable values.

Where statistics are used, report them in the conventional form for your field — the test, the statistic, the degrees of freedom, and the p-value — rather than describing the outcome in words alone.

Use the discussion to explain, not to repeat

A weak discussion restates the results in prose. A strong one answers four questions: what the findings mean in relation to the aim, whether they support the hypothesis, how they compare with theory or published work, and what limited them.

Comparison with expectation is where most of the analytical marks sit. If the result matched theory, say by how much and what that confirms. If it did not, resist the temptation to blame “human error” — identify the specific mechanism, whether that is heat loss to the surroundings, a systematic instrument offset, or a reaction that had not gone to completion.

Treat error analysis seriously

Error is not a confession; it is part of the measurement. Distinguish the two kinds, because they have different consequences and different remedies.

• Random error — scatter around the true value, reduced by repetition and visible as spread in your data.
• Systematic error — a consistent offset in one direction, which repetition does not reduce and which usually points to calibration or method.

Where a result is consistently off in one direction, saying so and identifying a plausible systematic cause demonstrates more understanding than any number of repeats.

Write in the conventions of your discipline

Most sciences expect past tense for what was done and found, and present tense for established knowledge. Passive voice remains standard in the method for many departments, though several now prefer active. Check your handbook rather than assuming, and be consistent — drifting between conventions within a report is noticeable.

Conclude briefly and answer the aim

The conclusion should be short and should return explicitly to the aim stated at the start: what was found, whether the hypothesis was supported, and what the value obtained was. It introduces nothing new. A conclusion that ends without stating the actual result — the measured value, the accepted or rejected hypothesis — has stopped one sentence short of its job.