Lab Observations, Data Tables, and Lab Reports

Lab observations are the facts you record with your senses and instruments during an experiment, data tables organize measured values in rows and columns with units, and a lab report is a structured document that describes the aim, method, results and conclusions of an investigation. In brief: record what you see, not what you expect, include units and uncertainty in every column heading, and write a report with the sections aim, method, results, discussion and conclusion.

Good records make an experiment repeatable and believable. An observation such as “the solution turned from colorless to blue within 20 seconds” is much more useful than “the reaction worked”. This article explains the difference between qualitative and quantitative observations, shows how to design a data table, lists the parts of a lab report, includes a worked example of a table and calculations, explains how to graph and discuss results and covers common mistakes.

How do you make good observations?

Qualitative observations describe qualities without numbers: color, smell (safely), texture, state, the formation of bubbles or a precipitate. Quantitative observations are measurements with numbers and units: mass, volume, temperature and time.

• Record observations at the time they happen, in the notebook, not on loose paper to be copied later.
• Describe what you see, not what you think it means. “Colorless gas bubbles form on the zinc” is an observation. “Hydrogen is produced” is an interpretation, and it belongs in the discussion.
• Note the starting appearance of all materials, the changes during the experiment and the final appearance.
• Give details: “pale yellow precipitate settles slowly” is better than “solid forms”.
• Record unexpected events, such as a spill or a change in procedure, as these may explain strange results.

How do you design a data table?

1. Prepare the table before the experiment, so you know what to measure.
2. Give the table a title that explains the content.
3. Put the independent variable in the first column and the dependent variable in the following columns.
4. Write units and, if known, uncertainties in the column headings, not in each cell: for example “Mass (g) ±0.01”.
5. Record all digits that the instrument shows, with the same number of decimal places in each column.
6. Leave room for repeated trials, averages and calculations.

What are the sections of a lab report?

Worked example: density of a metal

A student measures the density of a metal cylinder with a balance (±0.01 g) and a measuring cylinder (±0.5 mL).

1. Volume. Final minus initial: 40.0 − 30.0 = 10.0 mL, and so on for each trial.
2. Density. Trial 1: 27.15 ÷ 10.0 = 2.715, rounded to 2.7 g/mL (two significant figures, limited by the volume). Trial 2: 27.15 ÷ 10.5 = 2.586, which is 2.6. Trial 3: 27.15 ÷ 9.5 = 2.858, which is 2.9.
3. Mean. (2.715 + 2.586 + 2.858) ÷ 3 = 2.720, so the mean is 2.7 g/mL.
4. Uncertainty. The volume uncertainty is ±0.5 mL on each reading, so ±1.0 mL on the difference, which is 10% of 10 mL. This dominates the mass uncertainty (0.04%). The density is about 2.7 ± 0.3 g/mL.
5. Comparison. The accepted density of aluminum is 2.70 g/cm³, which lies within the range, so the metal is consistent with aluminum. The percent error of the mean is |2.72 − 2.70| ÷ 2.70 × 100% = 0.7%.

The calculation also shows an improvement for the discussion: a more precise instrument for volume, such as a 50 mL cylinder with 0.1 mL divisions, or measuring the dimensions of the cylinder with calipers, would greatly reduce the uncertainty.

How do you write the discussion?

• Summarize the pattern in the results, using numbers from the data.
• Explain the pattern with chemical ideas, such as the particle model or collision theory.
• Compare with the accepted value or the hypothesis, and calculate the percent error where relevant.
• Identify specific sources of error, say whether they are random or systematic and describe the likely effect on the result.
• Suggest realistic improvements, for example “use a burette instead of a measuring cylinder”.
• Avoid blaming “human error” without being specific.

How should you present graphs?

Plot the independent variable on the x-axis and the dependent variable on the y-axis. Choose scales that use most of the graph area, label axes with the quantity and unit, plot points accurately and draw a line or curve of best fit through the trend, not a line joining each point. Add a title and, if appropriate, error bars that show the uncertainty. In a spreadsheet, check that the chart type is a scatter plot for numerical data.

How do you keep a lab notebook?

• Use a bound notebook with numbered pages, and write in ink.
• Date each entry and write down the title and the aim.
• Cross out mistakes with a single line so that they remain readable. Do not erase or tear out pages.
• Record the details of chemicals: names, concentrations, lot numbers and supplier where relevant.
• Attach or tape in printouts, and note the file names for electronic data.

Why do scientists keep records?

Record-keeping has been important since the beginning of experimental science. Notebooks of researchers such as Michael Faraday, who kept detailed lab diaries in the 19th century, allow historians to follow how discoveries were made. In the 20th and 21st centuries, record-keeping also supports patents, regulation and research integrity, and repeatability of results is considered a core standard of scientific work.

Which mistakes are common?

Mistake 1: Recording interpretations instead of observations

Write what you see and measure. Put explanations in the discussion.

Mistake 2: Leaving out units or uncertainties

A number without a unit is incomplete. Put the units in the column headings.

Mistake 3: Rounding raw data

Record all digits shown by the instrument, and round only the calculated results.

Mistake 4: Writing a conclusion that is not supported by the data

The conclusion must answer the aim and refer to the evidence, and not claim more than the experiment shows.