How to Discuss Unexpected Results in a Lab Report

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-08-27

Quick Answer

• Treat unexpected results as a normal part of scientific inquiry, not a personal failure, and address them directly in your discussion section.
• Analyze whether the deviation stems from procedural error, equipment malfunction, biological variation, or a flaw in your original hypothesis before proposing explanations.
• Be transparent about limitations and avoid overclaiming, a well-reasoned alternative explanation supported by your data is more valuable than forcing results to fit expectations.

Understanding the Purpose of a Lab Report Discussion

The discussion section of a laboratory report is where you interpret what your results mean in the context of your original research question. When results match expectations, the discussion confirms or extends existing knowledge. When results deviate, the discussion becomes an exercise in critical thinking, requiring you to distinguish between experimental failure and genuine discovery.

Many students and early-career researchers treat unexpected results as something to hide or explain away. This approach misunderstands the purpose of scientific writing. A lab report documents what you did, what you observed, and what you think those observations mean. The discussion is your opportunity to demonstrate that you understand the scientific process, including its uncertainties.

Unexpected results can indicate several things: a flaw in your methodology, an error in measurement, a misunderstanding of the underlying theory, or a genuine phenomenon that your experiment has uncovered. Your job in the discussion is to work through these possibilities systematically and present your conclusions honestly.

The National Library of Medicine hosts research methods resources that emphasize the importance of transparent reporting in biomedical research. The same principles apply to student lab reports. Transparency about what went wrong and what you learned from it demonstrates scientific maturity.

At a Glance: Decision Framework for Unexpected Results

Before you write a single word of your discussion, work through this decision framework. It will help you categorize your unexpected results and determine the appropriate response.

This framework is not a rigid formula. Use it as a starting point for thinking about your specific situation. The key distinction is between results that can be explained by known errors and results that challenge your underlying assumptions.

Core Principles for Discussing Unexpected Results

Separate Observation from Interpretation

Your results section reports what happened. Your discussion section explains what it means. When results are unexpected, this separation becomes especially important. Do not let your interpretation color your description of the observations.

State your results plainly in the results section. In the discussion, you can then explore possible explanations without confusing the reader about what you actually observed. This separation is a fundamental principle of scientific writing and is reinforced by reporting guidelines available through the EQUATOR Network, which catalogs standards for transparent research reporting.

Acknowledge Uncertainty Directly

Scientific writing does not require certainty. It requires honesty about the limits of your knowledge. When you discuss unexpected results, acknowledge that you cannot fully explain them if that is the case. Propose the most plausible explanations based on your data and the existing literature, and state clearly which explanations you can support and which remain speculative.

Uncertainty is not weakness. A discussion that acknowledges uncertainty while proposing testable explanations demonstrates stronger scientific thinking than one that forces a confident conclusion from ambiguous data.

Distinguish Between Error and Discovery

The most important judgment you will make in your discussion is whether your unexpected results stem from error or from a genuine phenomenon. This distinction requires careful analysis of your methods, your observations, and the existing scientific literature.

Experimental error includes procedural mistakes, equipment problems, and contamination. Discovery includes observations that contradict existing theory or reveal a variable you did not anticipate. In practice, most unexpected results in student laboratories are due to error. But you cannot assume this without examining the evidence.

Ask yourself these questions:

• Did I follow the protocol exactly as written?
• Was my equipment calibrated and functioning properly?
• Did I record all observations, including those that seemed unimportant at the time?
• Do my results show a pattern, or are they randomly scattered?
• Does the existing literature suggest a mechanism that could explain my results?

Your answers to these questions will guide your discussion.

Practical Workflow for Analyzing Unexpected Results

Step 1: Review Your Raw Data and Records

Before you can discuss unexpected results, you need to confirm that they are real. Review your raw data, laboratory notebook, and any electronic records. Look for transcription errors, unit conversion mistakes, and calculation errors. These are common sources of apparent anomalies that have nothing to do with your experiment.

Check that you recorded all measurements, including outliers. Do not discard data points simply because they do not fit your expectations. If you believe a data point is invalid, you must have a documented reason for excluding it, such as a known equipment malfunction or procedural error.

The NIH Data Management and Sharing Policy emphasizes the importance of maintaining accurate and complete research records. The same principle applies to student laboratory work. Your records are the foundation of your analysis.

Step 2: Identify the Type of Deviation

Once you have confirmed your results are accurate, categorize the deviation. Is it a single outlier, a consistent shift in all measurements, or a pattern that contradicts your hypothesis?

A single outlier suggests a localized error, such as a contaminated sample or a momentary equipment fluctuation. A consistent shift suggests a systematic error, such as incorrect reagent concentration or a calibration offset. A pattern that contradicts your hypothesis suggests either a flaw in your theoretical framework or an unaccounted variable.

Each type of deviation requires a different discussion approach.

Step 3: Examine Your Methods for Potential Errors

Go through your methods section line by line. Consider each step of your protocol and ask whether an error could have produced your results. Common sources of error include:

• Incorrect reagent preparation or concentration
• Improper sample handling or storage
• Contamination of samples or equipment
• Timing errors in reactions or incubations
• Equipment malfunction or miscalibration
• Operator technique variation

For each potential error, assess whether it is consistent with the pattern of your results. An error that would produce a different pattern than what you observed is less likely to be the cause.

Step 4: Consult the Existing Literature

Your unexpected results may not be as unexpected as you think. Search the scientific literature for similar experiments and their outcomes. You may find that other researchers have observed similar deviations and have proposed explanations.

The National Library of Medicine provides access to biomedical literature and research methods resources that can help you contextualize your findings. Even for non-biomedical experiments, understanding how other researchers have handled similar situations will strengthen your discussion.

Step 5: Formulate Alternative Explanations

Based on your analysis, develop one or more alternative explanations for your results. Each explanation should be specific, testable, and grounded in your observations or the existing literature.

For example, if your enzyme assay showed lower activity than expected, possible explanations include:

• The enzyme preparation lost activity during storage
• The substrate concentration was lower than calculated
• The assay conditions differed from optimal
• The enzyme has a different optimal pH or temperature than reported
• An inhibitor was present in one of your reagents

For each explanation, state what evidence supports it and what additional experiments could test it.

Step 6: Write Your Discussion

With your analysis complete, you can write your discussion. Structure it to address the following points in order:

1. Restate your main findings, including the unexpected results
2. Explain what you expected and why
3. Present your analysis of potential errors
4. Present alternative explanations supported by your data or the literature
5. State the limitations of your study
6. Suggest follow-up experiments or improvements to the methodology

This structure guides the reader through your reasoning and demonstrates that you have thought critically about your results.

Options and Tradeoffs in Handling Unexpected Results

Option 1: Attribute Results to Procedural Error

If your analysis identifies a clear procedural error that explains your results, you can attribute the deviation to that error. This is the most straightforward approach and is appropriate when the error is well-documented and its effect on the results is clear.

The tradeoff is that you must be honest about the implications. If the error compromised your entire experiment, you should state that the results cannot be used to answer your research question. If the error affected only part of your data, you can discuss which conclusions remain valid.

Option 2: Propose an Alternative Explanation

If you cannot identify a procedural error but your results deviate from expectations, you can propose alternative explanations. These should be grounded in your observations and the existing literature, not speculation.

The tradeoff is that alternative explanations require evidence. You cannot simply assert that a variable you did not measure might have affected your results. You need to explain why that variable is plausible and how it could produce the pattern you observed.

Option 3: Challenge the Original Hypothesis

In rare cases, unexpected results may indicate that your original hypothesis was incorrect. This is the most scientifically significant outcome, but it requires strong evidence. You must rule out procedural error and alternative explanations before concluding that your hypothesis is wrong.

The tradeoff is that challenging a hypothesis based on a single experiment is risky. Replication is essential. If your results contradict established theory, you should be appropriately cautious and suggest further investigation instead of declaring a new discovery.

Option 4: Report Results as Inconclusive

Sometimes the most honest conclusion is that your results are inconclusive. This is appropriate when you cannot identify the source of the deviation and cannot propose a well-supported alternative explanation.

The tradeoff is that inconclusive results are less satisfying. However, reporting inconclusive results honestly is better than forcing a conclusion that your data do not support. The Committee on Publication Ethics emphasizes honesty and transparency in reporting, principles that apply equally to student lab reports.

Observations and Measurements to Document

Your discussion will be stronger if you have documented your observations and measurements thoroughly. Beyond the raw data from your experiment, record the following:

• Environmental conditions during the experiment, such as temperature and humidity
• Equipment used, including calibration dates and any malfunctions
• Reagent lot numbers and preparation dates
• Any deviations from the written protocol, however minor
• Observations that seemed irrelevant at the time but might explain your results

These records serve two purposes. First, they help you identify potential sources of error when results are unexpected. Second, they demonstrate to your instructor or reviewer that you conducted your experiment carefully and thoughtfully.

The NIH Grants and Funding resources emphasize the importance of rigorous record-keeping in research. While student lab work is not grant-funded research, the same principles of documentation apply.

Records and Measurements: Building an Audit Trail

An audit trail is a complete record of what you did, when you did it, and what you observed. Building a strong audit trail from the start of your experiment makes it much easier to analyze unexpected results later.

Your audit trail should include:

• The date and time of each experimental step
• The identity of the person performing each step
• Equipment settings and calibration records
• Reagent preparation details, including concentrations and storage conditions
• Raw measurements before any calculations or transformations
• Notes on any anomalies or deviations observed during the experiment

When results are unexpected, your audit trail allows you to trace back through your process and identify where things might have gone wrong. Without this record, you are left guessing about the cause of your results.

Quality Controls and Verification Steps

Quality controls are procedures that verify your experimental system is working correctly. They are essential for distinguishing between genuine results and experimental artifacts.

Common quality controls include:

• Positive controls that should produce a known result
• Negative controls that should produce no result
• Replicate measurements to assess variability
• Calibration standards for equipment
• Blank samples to detect contamination

If your experiment included quality controls, check whether they produced the expected results. If your controls failed, your unexpected results may be due to a systemic problem instead of a genuine phenomenon. If your controls worked correctly, your unexpected results are more likely to reflect something real about your experimental system.

The EQUATOR Network provides reporting guidelines that emphasize the importance of describing quality controls and verification steps in research reports. Including this information in your lab report discussion demonstrates that you understand the importance of experimental rigor.

Common Failure Patterns in Discussing Unexpected Results

Pattern 1: Ignoring the Unexpected Results

Some students mention unexpected results only briefly or omit them entirely from their discussion. This is a serious error. Ignoring results because they do not fit your expectations is a form of selective reporting that undermines the integrity of your work.

The Committee on Publication Ethics identifies selective reporting as a form of misconduct. While a student lab report is not a publication, the same ethical principles apply. You must address all your results, including those that are inconvenient.

Pattern 2: Blaming All Unexpected Results on Error

The opposite failure is attributing every unexpected result to experimental error without evidence. This approach avoids the hard work of analyzing your results and can cause you to miss genuine findings.

If you claim that an error caused your results, you must identify the specific error and explain how it produced the pattern you observed. Vague claims of "human error" or "equipment problems" without specifics are not convincing.

Pattern 3: Overinterpreting Unexpected Results

Some students go too far in the other direction, treating every unexpected result as a major discovery. This overinterpretation is especially common when results seem to support a novel hypothesis.

Extraordinary claims require extraordinary evidence. If your results contradict established theory, you need to rule out all alternative explanations and demonstrate that your findings are reproducible. A single experiment with unexpected results is not sufficient to overturn existing knowledge.

Pattern 4: Using Unexpected Results to Avoid Conclusions

Some students use unexpected results as an excuse to avoid drawing any conclusions from their experiment. They claim that because the results were unexpected, nothing can be concluded.

This approach misunderstands the purpose of a discussion. Even when results are unexpected, you can draw conclusions about your experimental system, your methodology, and the questions that remain unanswered. A discussion that ends with "the results were unexpected, so no conclusions can be drawn" is incomplete.

Pattern 5: Failing to Connect Results to the Research Question

Finally, some students discuss unexpected results in isolation, without connecting them back to the original research question. This failure makes the discussion feel disconnected from the rest of the report.

Your discussion should always return to your research question. How do your results, expected or unexpected, help answer that question? What new questions do they raise? What would you do next to address those questions?

Limitations and Professional Escalation Criteria

Every experiment has limitations. Acknowledging these limitations is a sign of scientific maturity, not weakness. In your discussion, state clearly what your experiment could and could not determine.

Common limitations include:

• Small sample sizes that limit statistical power
• Limited range of conditions tested
• Use of simplified model systems
• Measurement precision limits
• Time constraints that prevented replication

When your results are unexpected, limitations become especially important. A limitation that you did not initially consider may explain your results. For example, if you tested only one concentration of a reagent, you may have missed a concentration-dependent effect.

Professional escalation criteria apply when unexpected results have implications beyond your own experiment. If your results suggest a safety concern, a significant deviation from established knowledge, or a potential error in published work, you should discuss this with your instructor, supervisor, or research mentor.

The NIH Grants and Funding resources describe the responsibilities of researchers to report concerns and seek guidance when appropriate. In a student context, your instructor or laboratory supervisor serves this role. Do not attempt to resolve significant concerns on your own.

Safety and Regulatory Context

Unexpected results can sometimes indicate safety problems. If your results suggest that a reagent is contaminated, a piece of equipment is malfunctioning, or a procedure is producing hazardous byproducts, you should report this immediately to your instructor or supervisor.

Do not continue experiments if you suspect a safety issue. Stop the experiment, secure any hazardous materials, and report the concern. Safety concerns take precedence over completing your experiment or writing your report.

Regulatory requirements may also apply to certain types of experiments. If your work involves human subjects, animal subjects, hazardous materials, or controlled substances, unexpected results may have regulatory implications. Your instructor or supervisor can advise you on the appropriate course of action.

The National Library of Medicine provides resources on research ethics and regulatory requirements that are relevant to biomedical research. For other fields, consult your institution's research office or your instructor.

Writing the Discussion Section: Structure and Style

Opening Paragraph

Begin your discussion by restating your main findings in plain language. State what you observed, including the unexpected results. Do not interpret yet. Simply describe what happened.

Expected Results Context

Next, briefly restate what you expected to find and why. This context is essential for the reader to understand why your results are unexpected. Reference your hypothesis and the theoretical basis for your expectations.

Analysis of Unexpected Results

Present your analysis of the unexpected results. Work through the potential explanations you identified in your workflow. For each explanation, state the evidence that supports it and the evidence that argues against it. Be honest about the strength of each explanation.

Alternative Explanations

Propose the most plausible alternative explanations for your results. Each explanation should be specific and testable. State what additional experiments could distinguish between the explanations.

Limitations

Acknowledge the limitations of your experiment. State clearly what your results can and cannot tell you. This section should be specific, not generic. Do not list every possible limitation. Focus on the limitations that are most relevant to interpreting your results.

Implications and Next Steps

Conclude your discussion by stating the implications of your results for your research question. What have you learned? What questions remain? What would you do differently in a future experiment?

Style Guidelines

Write in clear, direct prose. Use the first person when describing your own decisions and reasoning. Avoid passive constructions that obscure who did what. Use technical terms precisely and define them when necessary.

Do not apologize for your results. Acknowledge errors and limitations without self-deprecation. The goal is to demonstrate that you understand what happened and why.

Common Mistakes in Discussion Writing

Mistake 1: Restating Results Without Interpretation

Some students write discussions that simply restate their results in paragraph form. This is redundant and does not fulfill the purpose of a discussion. Your discussion should interpret your results, not repeat them.

Mistake 2: Introducing New Results

The discussion should not introduce new data that were not presented in the results section. If you forgot to include a result in your results section, go back and add it there. The discussion builds on the results section, it does not replace it.

Mistake 3: Overusing Hedging Language

Hedging language such as "may," "might," and "could" is appropriate when discussing uncertainty. However, overusing these words makes your writing sound weak and indecisive. Use hedges when you are genuinely uncertain, but state your conclusions confidently when your evidence supports them.

Mistake 4: Ignoring the Literature

A discussion that does not reference the existing literature is incomplete. Your results gain meaning through comparison with previous work. Even if your results are unexpected, you should relate them to what is known about your topic.

Mistake 5: Writing for the Instructor instead of the Reader

Some students write discussions that seem designed to please the instructor instead of to communicate with a reader. This approach produces vague, defensive writing. Instead, write as if you are explaining your work to a fellow scientist who is interested in your topic but has not seen your experiment.

Frequently Asked Questions

What should I do if my results do not match my hypothesis?

Do not panic. First, verify that your results are accurate by reviewing your raw data and records. Then work through the decision framework in this article to categorize the deviation. If you identify a procedural error, describe it and explain its impact. If you cannot identify an error, propose alternative explanations and suggest follow-up experiments. Address the unexpected results directly in your discussion instead of ignoring them.

How do I know if my unexpected results are due to experimental error?

Review your methods carefully and look for specific errors that could produce the pattern you observed. Check your records for equipment malfunctions, reagent preparation errors, timing mistakes, and contamination. If you find a specific error that explains your results, you can attribute the deviation to that error. If you cannot find a specific error, you should consider alternative explanations.

Can I exclude outliers from my data?

You can exclude outliers only if you have a documented reason for doing so, such as a known equipment malfunction or procedural error. You cannot exclude data points simply because they do not fit your expectations. If you exclude outliers, you must describe your exclusion criteria in your methods section and discuss the excluded data in your discussion.

What if my unexpected results suggest my hypothesis is wrong?

If your analysis rules out procedural error and alternative explanations, your results may indicate that your hypothesis is incorrect. State this conclusion cautiously and acknowledge the limitations of your experiment. Suggest follow-up experiments that could test your hypothesis more directly. A single experiment is rarely sufficient to overturn a hypothesis, so be appropriately cautious.

How much detail should I include about what went wrong?

Include enough detail for the reader to understand what happened and why it affected your results. Describe the specific error, when it occurred, and how it influenced your measurements. Do not provide excessive detail about every minor deviation. Focus on the errors that are relevant to interpreting your results.

Should I discuss unexpected results that I cannot explain?

Yes. Acknowledge that you cannot fully explain your results and propose the most plausible explanations based on your data and the literature. State clearly which explanations you can support and which remain speculative. Suggest experiments that could resolve the uncertainty. Honest acknowledgment of unexplained results is better than forcing an unsupported conclusion.

How do I write about unexpected results without sounding defensive?

Focus on the science instead of on yourself. Describe what you observed, what you expected, and what you think the deviation means. Acknowledge errors and limitations directly without apologizing. Use a neutral, analytical tone. The goal is to demonstrate your understanding of the experimental system, not to defend your performance.

What should I do if my unexpected results suggest a safety concern?

Stop the experiment immediately and secure any hazardous materials. Report the concern to your instructor or laboratory supervisor. Do not continue experiments until the safety concern is resolved. Safety concerns take precedence over completing your experiment or writing your report.

Using the Evidence

Related Articles

• Lab Meeting Presentations: Turning Ongoing Work Into Useful Discussion
• Common Limitations in Research: Examples and How to Address Them
• Methodology Limitations in Research: How to Identify and Address Them
• Western Blot Results
• medical lab science reddit

References and Further Reading

• Research Methods Resources. National Library of Medicine.
• EQUATOR Network. EQUATOR Network.
• Core Practices. Committee on Publication Ethics.
• NIH Grants and Funding. National Institutes of Health.
• ORCID for Researchers. ORCID.
• Data Management and Sharing Policy. National Institutes of Health.
• NCBI Literature Resources. National Center for Biotechnology Information.
• PubMed. National Library of Medicine.

This article is educational and does not replace institutional policy, professional advice, or applicable safety and regulatory requirements.