How to present results in lab report without interpretation

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

Quick Answer

• Present only observed data, measurements, and statistical outcomes in the results section, saving all meaning and implications for the discussion section.
• Organize results with tables, figures, and descriptive text that report what happened, not why it happened or what it means.
• A common limitation is that some journals and instructors allow brief context sentences, so check your specific assignment rubric or target journal instructions before writing.

Understanding the Results Section

The results section of a laboratory report serves one primary function: to communicate what you observed and measured during your experiment. This section is not the place for explaining why results occurred, comparing them to published literature, or drawing conclusions about their significance. Those activities belong in the discussion section where you interpret the data within the broader context of your field.

Students frequently struggle with this distinction because the line between reporting and interpreting can feel blurry. A statement like "the temperature increased" is factual reporting. A statement like "the temperature increased because the reaction is exothermic" crosses into interpretation because it assigns a cause. Similarly, "the absorbance was 0.45 at 600 nm" is a result, while "the absorbance of 0.45 indicates high bacterial growth" is an interpretation because it connects the measurement to a biological meaning.

The results section answers the question "what did you find?" The discussion section answers "what do those findings mean?" Keeping these questions separate in your writing helps readers evaluate your data independently before considering your conclusions. This separation also protects your scientific credibility because it shows you can distinguish between observation and inference.

Research reporting guidelines exist to help authors present their work transparently and completely. The EQUATOR Network maintains a collection of reporting guidelines for different study types, and consulting these resources before writing can help you understand what information belongs in each section of a report. While these guidelines primarily target published research, the same principles of clear and complete reporting apply to student laboratory reports.

At a Glance

This table shows the division of labor across the main sections of a laboratory report. The results section focuses exclusively on presenting findings. The discussion section handles interpretation. The methods section describes procedures. When you write, check each sentence against this framework to ensure you place information in the correct section.

Core Principles for Factual Reporting

Report Observations Without Explanation

The fundamental rule of the results section is to state what happened without stating why it happened. This rule applies to all types of data, whether you measured plant height, bacterial colony counts, chemical reaction rates, or behavioral responses in animals.

Consider the difference between these two sentences:

• Factual: "The mean seedling height was 12.4 cm in the treatment group and 9.8 cm in the control group."
• Interpretive: "The treatment group grew taller because the fertilizer provided essential nutrients."

The first sentence reports measurements. The second sentence explains the mechanism behind those measurements. The explanation belongs in the discussion section where you can evaluate whether your results support or contradict existing knowledge.

This principle becomes more challenging when you need to describe unexpected results. You might be tempted to explain why something went wrong or why your hypothesis was not supported. Resist that temptation in the results section. Simply report what you observed. The discussion section gives you space to address anomalies, propose explanations, and acknowledge limitations.

Use Descriptive Language

Descriptive language in the results section focuses on what the data show. Verbs like "increased," "decreased," "remained stable," "correlated with," and "differed from" describe relationships in your data without assigning causes.

Compare these approaches:

• Descriptive: "The reaction rate increased as temperature increased from 20°C to 40°C."
• Interpretive: "Higher temperatures accelerated the reaction by increasing molecular collisions."

The first sentence describes a relationship between two measured variables. The second sentence explains the physical mechanism behind that relationship. Both statements might be true, but only the first belongs in the results section.

Descriptive language also applies to statistical outcomes. You can report that "the difference between groups was statistically significant at p < 0.05" without explaining what that significance means for your hypothesis. The meaning belongs in the discussion.

Present Data in Logical Order

Organize your results to follow the logical progression of your experiment. If you tested multiple variables, present results for each variable in the order you described them in your methods section. If you collected data over time, present results chronologically. This organization helps readers follow your experimental logic without getting lost.

A common approach is to present results in the same order as your objectives or hypotheses. If your first objective was to measure baseline values, present those measurements first. If your second objective was to test the effect of a treatment, present those results next. This structure creates a clear narrative that readers can follow.

Within each subsection, decide whether to present text, tables, or figures first. A common pattern is to describe the main finding in text, then direct readers to the corresponding table or figure for complete data. For example: "Mean heart rate was significantly lower in the treatment group (Table 1)." This approach gives readers the key finding while providing access to full data.

Practical Workflow for Writing Results

Step 1: Compile All Data

Before writing, gather every piece of data you collected during the experiment. This includes raw measurements, calculated values, statistical test results, and any observations recorded in your laboratory notebook. Having everything in one place helps you see the complete picture before you start writing.

Organize your data by variable or experimental group. Create tables that show your raw data and calculated summary statistics. Identify which data points are most relevant to your objectives and which are peripheral. This organization will guide your writing structure.

Step 2: Create Tables and Figures

Tables and figures present data efficiently and allow readers to see patterns at a glance. Decide which data are best presented in each format. Tables work well for exact numerical values and multiple variables. Figures work well for showing trends, distributions, and relationships.

Label every table and figure with a descriptive title and number them in the order they appear in your text. Include units in table headers and axis labels. Provide enough detail in captions that readers can understand the data without referring to the methods section.

When you create tables, keep them simple and focused. Each table should present data relevant to one aspect of your results. Avoid cramming too many variables into a single table because this makes it difficult for readers to extract meaning. If you have many variables, consider using multiple tables.

Step 3: Write Descriptive Text

Write the text of your results section after you have organized your tables and figures. The text should guide readers through your data, highlighting the most important findings and directing attention to specific tables and figures.

Each paragraph should focus on one finding or one set of related findings. Start with the most important result and work toward less important ones. Use clear topic sentences that state what the paragraph will describe.

The text should not repeat all the data shown in tables and figures. Instead, it should summarize the key patterns and point readers to the visual presentation for complete details. For example: "Cell viability decreased with increasing drug concentration (Figure 2). The highest concentration tested reduced viability to 23% of control values."

Step 4: Review for Interpretive Language

After drafting your results section, read through it carefully and mark every sentence that includes interpretation. Look for words that signal explanation, such as "because," "therefore," "indicates," "suggests," "demonstrates," and "implies." These words often introduce interpretive statements.

Also look for comparisons to published literature, references to your hypothesis, and statements about implications. These elements belong in the discussion section. Move any interpretive content to your discussion section or remove it entirely if it does not belong anywhere.

Consider asking a classmate or colleague to review your results section and identify any sentences that seem interpretive. A fresh reader can often spot problems that you miss because you are familiar with your own reasoning.

Options and Tradeoffs in Presenting Results

Text Versus Tables Versus Figures

You have three main options for presenting data: descriptive text, tables, and figures. Each format has strengths and limitations, and the best choice depends on the nature of your data and the message you want to convey.

Descriptive text works well for highlighting key findings and guiding readers through your results. Text is flexible and can emphasize the most important patterns. However, text becomes unwieldy when you have many numerical values because readers cannot easily compare numbers embedded in sentences.

Tables excel at presenting exact values and allowing readers to compare numbers across groups or conditions. Tables are efficient for data with multiple variables or many data points. The limitation of tables is that they do not show trends as clearly as figures, and readers must work to extract patterns from the numbers.

Figures are best for showing trends, distributions, and relationships. Graphs make patterns visually obvious and are particularly useful for time-series data, dose-response relationships, and comparisons between groups. The limitation of figures is that they present approximate values instead of exact numbers, so readers cannot extract precise data from them.

A well-written results section typically uses a combination of all three formats. Text highlights key findings, tables provide exact values, and figures show patterns. Choose the format that best serves each piece of data.

Raw Data Versus Summary Statistics

Decide whether to present raw data, summary statistics, or both. Raw data includes every individual measurement you collected. Summary statistics include means, medians, standard deviations, standard errors, and confidence intervals.

Raw data gives readers complete information and allows them to verify your calculations. However, raw data can be overwhelming when you have many measurements. Summary statistics condense the data into manageable values but lose individual variation.

For most laboratory reports, summary statistics are appropriate for the main results, with raw data available in appendices if needed. Present means and measures of variability for each experimental group. If you have a small number of measurements, consider presenting the raw data in a table so readers can see all values.

Statistical Results

If you performed statistical tests, report the test used, the test statistic, degrees of freedom, and p-value. This information allows readers to evaluate the strength of your evidence.

Report statistical results in a consistent format. For example: "The mean difference between groups was statistically significant (t = 2.45, df = 18, p = 0.025)." This format gives readers the essential information about the test without requiring them to consult your methods section.

When you report statistical results, do not interpret what they mean for your hypothesis. State that the difference was statistically significant or not significant, but save the implications for the discussion section.

Observations and Measurements

Recording What You See

Your results section should include observations that are relevant to your experiment, even if those observations were not part of your planned measurements. Unexpected observations can be valuable, and reporting them honestly strengthens your scientific credibility.

For example, if you noticed that a solution changed color during an experiment, report that observation. If a piece of equipment malfunctioned and may have affected your data, report that too. These observations provide context that helps readers evaluate your results.

Distinguish between observations you made directly and measurements you took with instruments. Direct observations include color changes, physical states, and behavioral responses. Measurements include values from balances, spectrophotometers, thermometers, and other instruments. Both types of information belong in your results, but they should be clearly labeled.

Handling Anomalous Data

Anomalous data points are values that differ substantially from the rest of your data. You may be tempted to exclude them or explain them away in the results section. The appropriate approach depends on the situation.

If you have a clear reason to exclude a data point, such as a documented equipment failure or procedural error, you can exclude it and note the exclusion in your results. For example: "One sample was excluded from analysis because the tube broke during centrifugation."

If you do not have a clear reason for an anomalous value, include it in your results and report it honestly. You can discuss possible explanations in the discussion section. Excluding data without justification is a form of data manipulation that violates research integrity.

The Committee on Publication Ethics Core Practices emphasize the importance of honest and transparent reporting in research. These principles apply to student laboratory reports as well as published research. Presenting all your data, including inconvenient results, demonstrates scientific integrity.

Negative Results

Negative results are findings that do not support your hypothesis or show no effect of your treatment. These results are just as important as positive results, and they belong in your results section.

Report negative results factually, just as you would report positive results. State what you observed without apologizing for it or explaining it away. For example: "No significant difference in growth rate was observed between the treatment and control groups (p = 0.42)."

The discussion section is where you can explore why your hypothesis was not supported. You might discuss limitations in your methods, variability in your samples, or the possibility that your hypothesis was incorrect. The results section simply reports what you found.

Records and Documentation

Laboratory Notebook Practices

Your laboratory notebook is the foundation of your results section. Accurate, complete records allow you to write a results section that faithfully represents your experiment. Incomplete or disorganized records lead to gaps in your results and uncertainty about what you actually observed.

Record every measurement at the time you take it. Do not rely on memory or transcribe values later from loose notes. Include the date, time, and conditions for each measurement. Note any equipment used and its calibration status. Record observations immediately, including things that seem unimportant at the time.

The National Institutes of Health Data Management and Sharing Policy emphasizes the importance of planning for data management throughout the research process. While this policy applies to NIH-funded research, the principle of thoughtful data management applies to all scientific work. Good records make good results sections possible.

Organizing Data Files

If you collect data electronically, organize your files systematically. Use consistent naming conventions that identify the experiment, date, and variable. Store raw data files separately from analyzed data so you can always return to the original measurements.

Back up your data regularly. Losing data because of a computer failure is preventable and frustrating. Keep copies in multiple locations, such as your computer, a cloud service, and a physical drive.

When you analyze data, keep a record of the steps you took. Note which software you used, which statistical tests you ran, and which data points were included or excluded. This documentation allows you to verify your analysis and answer questions from reviewers or instructors.

Tracking Versions

As you revise your results section, keep track of changes you make. Save versions of your document so you can return to earlier drafts if needed. This practice is especially important when you receive feedback from instructors or collaborators and need to track how you addressed their comments.

Version tracking also helps you avoid accidentally deleting content you might need later. When you move interpretive content from your results to your discussion, keep a copy of the original text in case you need to reference it.

Common Failure Patterns

Mixing Interpretation into Results

The most common failure in results sections is including interpretive statements. Students often write sentences that explain why results occurred or what they mean, even when they know these statements belong in the discussion.

This failure typically happens because students want to demonstrate their understanding of the experiment. They worry that a purely factual results section will seem superficial. In reality, a clean results section demonstrates scientific discipline and respect for the reader's ability to draw conclusions.

To avoid this failure, write your results section first without any interpretation. Then, when you write your discussion, you can reference your results and add interpretation. This two-step process keeps the sections separate.

Repeating All Data in Text

Another common failure is repeating every value from tables and figures in the text. This repetition makes the results section long and tedious without adding information.

The text should highlight key findings and direct readers to tables and figures for complete data. For example: "The treatment group showed significantly higher enzyme activity than the control group (Table 2)." This sentence gives readers the main finding without listing every value.

If you find yourself writing sentences that simply restate numbers from a table, consider whether those sentences are necessary. Often they can be shortened or removed entirely.

Including Methods in Results

Some students include procedural details in their results section, such as how they prepared samples or which equipment they used. This information belongs in the methods section.

The results section should focus on what you found, not how you found it. If you need to remind readers of a procedural detail to understand a result, refer to the methods section instead of repeating the detail.

For example, instead of writing "Samples were incubated at 37°C for 24 hours, and the resulting absorbance values are shown in Table 1," write "Absorbance values after incubation are shown in Table 1." The incubation details belong in the methods section.

Overexplaining Statistical Results

Students sometimes write lengthy explanations of statistical concepts in their results sections. They explain what a p-value means or why they chose a particular test. This information belongs in the methods section or the discussion.

In the results section, simply report the statistical outcomes. State which test you used, the test statistic, and the p-value. If readers need more information about the test, they can consult your methods section.

Presenting Raw Data Without Summary

Some students present long tables of raw data without any summary statistics or descriptive text. This approach forces readers to extract meaning from the numbers themselves, which is difficult and frustrating.

Always provide some level of summary. Calculate means, standard deviations, or percentages for each group. Write text that highlights the key patterns in the data. Raw data can be included in appendices if needed, but the main results should be digestible.

Quality and Welfare Considerations

Accuracy in Reporting

Accuracy is the most important quality standard for a results section. Every value you report must be accurate and verifiable. Check your calculations, verify your data entry, and confirm that your tables and figures match your raw data.

Errors in results sections undermine your credibility, even if the errors are minor. Readers who find one mistake may question the accuracy of your entire report. Take the time to verify every number before submitting your work.

The Committee on Publication Ethics Core Practices emphasize the importance of accuracy and integrity in research reporting. Fabricating or falsifying data is a serious ethical violation with consequences that can follow you throughout your career. Always report your actual results, even when they are disappointing or unexpected.

Transparency About Limitations

While the results section should not include interpretation, it should be transparent about limitations that affect the data. If equipment malfunctioned, samples were contaminated, or procedures deviated from the protocol, report these issues.

Transparency about limitations does not mean explaining why results turned out a certain way. It means honestly reporting the conditions under which you collected your data. Readers can then evaluate your results with full knowledge of the circumstances.

For example: "The spectrophotometer was recalibrated midway through data collection after readings appeared unstable." This statement reports a fact about your data collection without interpreting how it affected your results.

Animal Welfare Context

If your laboratory work involves animals, your results section should reflect the conditions under which the animals were housed and tested. Report any welfare issues that arose during the experiment, such as illness, injury, or unexpected mortality.

Animal welfare is beyond an ethical concern but also a scientific one. Stress, illness, and poor housing conditions can affect experimental outcomes. Reporting these conditions helps readers evaluate your results and contributes to the broader goal of improving animal welfare in research.

The National Institutes of Health provides guidance on responsible animal research through its grants and funding policies. Researchers who receive NIH funding must follow established standards for animal care and use. These standards exist to protect both the animals and the scientific validity of the research.

Safety and Regulatory Context

Laboratory Safety Reporting

Your results section should not include safety information unless it directly relates to your data. However, you should report any safety incidents that affected your experiment, such as spills, exposures, or equipment failures.

Safety incidents can affect data quality, and reporting them helps readers understand your results. For example, if a chemical spill contaminated some of your samples, you should report this in your results or methods section.

The broader context of laboratory safety is important for all researchers. Following established safety protocols protects you and your colleagues and ensures that your experiments can be completed without interruption.

Regulatory Compliance

Depending on your field and institution, your research may be subject to regulatory requirements. These requirements might include institutional review board approval for human subjects research, institutional animal care and use committee approval for animal research, or biosafety committee approval for work with hazardous materials.

Your results section should not include regulatory information unless it is relevant to understanding your data. However, you should be aware of the regulatory context for your work and ensure that you have the necessary approvals before beginning your experiment.

The National Institutes of Health Grants and Funding pages describe the regulatory requirements that apply to NIH-funded research. These requirements exist to protect research participants, animals, and the integrity of the research enterprise.

Professional Escalation Criteria

When to Seek Help

If you are struggling to keep interpretation out of your results section, seek help from your instructor, teaching assistant, or writing center. These resources exist to help you improve your scientific writing.

Signs that you need help include:

• You cannot identify which sentences in your draft are interpretive
• Your instructor has commented multiple times that your results section includes interpretation
• You are unsure whether a particular statement is factual or interpretive
• You are spending excessive time trying to decide what belongs in results versus discussion

Getting feedback early in the writing process is more efficient than trying to fix problems after you have written a complete draft. Share your outline or partial draft with your instructor and ask for guidance on the results section.

When to Consult Institutional Resources

If you have questions about data management, research integrity, or publication ethics, consult your institution's research office or library. These offices can provide guidance on institutional policies and best practices.

The Committee on Publication Ethics Core Practices provide a framework for understanding ethical issues in research. If you are unsure whether a particular practice is acceptable, consult these resources or speak with a research integrity officer at your institution.

When to Escalate Concerns

If you observe data fabrication, falsification, or other research misconduct in your laboratory, you have a responsibility to report it. Consult your institution's research integrity policies for guidance on how to report concerns.

Research misconduct is a serious issue that undermines the integrity of science. The Committee on Publication Ethics Core Practices describe the responsibilities of researchers to report misconduct and cooperate with investigations. Protecting the integrity of research benefits everyone.

Frequently Asked Questions

What is the difference between results and discussion in a lab report?

The results section presents your observations and measurements without explaining them. The discussion section interprets those findings, compares them to published literature, and draws conclusions. Results answer "what did you find?" while discussion answers "what does it mean?"

Can I include a brief explanation in the results section?

Some instructors and journals allow brief context sentences in the results section, but the safest approach is to keep the results section purely factual. Check your assignment rubric or target journal instructions to see what is expected. When in doubt, save explanations for the discussion section.

How do I report statistical results without interpreting them?

Report the test you used, the test statistic, degrees of freedom, and p-value. For example: "The difference between groups was statistically significant (t = 2.45, df = 18, p = 0.025)." Do not add statements about what the significance means for your hypothesis.

Should I include raw data in my results section?

Raw data can be included in appendices, but the main results section should present summary statistics such as means, standard deviations, and percentages. Tables and figures should present data in a digestible format that readers can understand without extensive calculation.

What should I do with unexpected results?

Report unexpected results honestly in your results section without explaining them. Note any procedural issues that may have affected the data. Use the discussion section to explore possible explanations and implications of unexpected findings.

How do I know if a sentence is interpretive?

Ask whether the sentence states what happened or why it happened. "The temperature increased" is factual. "The temperature increased because the reaction is exothermic" is interpretive. Also watch for words like "indicates," "suggests," "demonstrates," and "implies," which often introduce interpretation.

Can I use tables and figures in the results section?

Yes, tables and figures are essential tools for presenting results efficiently. Use tables for exact numerical values and figures for trends and relationships. Label each table and figure with a descriptive title and refer to them in

Using the Evidence

Related Articles

• Qualitative Data Analysis: Coding, Theming, and Interpretation
• Common Mistakes in Meta-Analysis and How to Avoid Them
• Bioinformatics vs Data Science: Which Career Is Right for You?
• Ethical Concerns in Research: Common Pitfalls and How to Avoid Them
• How to Present Data in Research Papers: Methods, Tables, and Figures

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.