S. SMITH
IB HL Chemistry
Lab Report Format
If you are submitting a lab for DESIGN criteria only, focus on the
yellow highlighted areas of this report.
NAME:
DATE:
TITLE:
Your title should reveal both your independent and dependent variable.
GROUP/PARTNER:
RESEARCH
QUESTION:
Define the problem or research question. Give a clear and specific statement of your purpose for
the experiment. Make one or more statements describing the investigation. If a general purpose has
already been suggested, you may restate it, but then you must make it more specific and relevant to
your individual experiment.
HYPOTHESIS:
This is your prediction about the behavior of the variables under investigation. It should be specific
and directly related to your research question. Your hypothesis must have an explanation – you
need to state your reason for your hypothesis and be quantitative where possible. Using the “If…,
then…, because…” format may help you remember all of the components of a complete hypothesis,
but the format is NOT required. Do NOT formulate a hypothesis if you already know the expected
result or if you have no idea what result you might obtain. In these cases, state that no meaningful
hypothesis is possible. Note that your hypothesis does not need to be correct (i.e. your investigation
might prove it incorrect), however it should be reasonable.
VARIABLES:
List the main relevant variables with a brief statement explaining why they are relevant to this
investigation. (For relevancy, consider how the variable could affect the outcome of the experiment.)
Indicate which variables are independent (manipulated) and which are dependent (responding).
State which variables need to be controlled and how you will control them. An experimental design
diagram can be very helpful (hint, hint).
PROCEDURE:
If a detailed procedure is provided, summarize the method in paragraph form and cite the
source. In this situation there is no need to list materials or rewrite the actual procedure.
APPARATUS:
List materials used for the experiment. Describe the apparatus in detail, being as specific as
possible (e.g. “50 cm3 beaker” rather than “beaker”).
METHOD:
Describe a series of numbered instruction steps, in the order you would do them in the investigation.
Provide enough detail that another person could repeat your work. Design a method that collects
sufficient and relevant data for the variables under investigation and controls the other variables.
Provide a labeled diagram (even it is hand-drawn) as it can be very helpful to the reader.
Although you are not required to actually collect data for a design lab, it should be very
clear to the reader what data you would collect… and perhaps even how you might
process it.
DATA
COLLECTION:
The data you record as you are doing your lab is considered ‘raw, raw’ data. Although having an
organized table in advance to record raw raw data in is a good idea, it is not required. Your instructor
may ask that you get raw raw data initialed. Collecting and recording of raw data must include
qualitative as well as quantitative data, including units and uncertainties where necessary. Once
you have completed initial data collection, organize the data so that it is clearly presented, allowing
for easy interpretation. Use of one or more tables for raw data is expected. Include all relevant data,
even if mentioned in the procedure. Give an identifying number and title to each table. Organize
observations into rows and columns for greatest efficiency and clarity. If there are any difficulties
(‘spills’, ‘time constraints’) encountered in carrying out the stated method note them in this section.
DATA PROCESSING & PRESENTATION:
CALCULATIONS OF RESULTS:
Select an appropriate method to process the data. This may involve calculations, graphing or other
forms of analysis. Do one sample calculation; identical calculations do not need to be repeated.
Include any equations you use, show all steps clearly and explain the methods used. Often it is
preferable to set up an equation for an entire calculation, rather than carrying it out in separate steps.
This avoids rounding errors and reduces the likelihood of errors resulting from stepwise calculations.
Use significant figures appropriately. The final result should be consistent with the number of
significant figures in the experimental measurements and any subsequent calculations based on
them. For repeated trials, calculate a final result for each trial; do not use an average of raw data.
Calculate an average result, based on final results of repeated trials.
CALCULATIONS OF ERRORS AND UNCERTAINTIES:
Use final results of repeated trials for calculation of experimental uncertainty. Uncertainties should be
estimated for single measurements and carried throughout the calculations. They can be stated as
absolute or relative values. Errors should be calculated where possible (percent error, percent yield),
using the final average value. These two values – the uncertainty and the experimental error need to
be compared in the evaluation.
PRESENTATION OF RESULTS:
This must be easy to follow and understand, comprehensive, and appropriate to the nature of the
results. Errors and uncertainties should be noted, when relevant. Graphs will often be utilized,
especially for several values of continuous variables. When constructing graphs, be sure to show a
title and label the axes, use an appropriate size (not too small), use an appropriate scale, indicate
points clearly, and show the relationship by fitting points to line(s) or a smooth curve. If graphs are
not appropriate, summarize results in a table.
CONCLUSION:
Begin with a few summary statements that highlight the results of your investigation. Then interpret
the results and state a valid conclusion. Your conclusion should be clearly related to the purpose
of the experiment. It should address your hypothesis, if you stated one. Explain how your conclusion
follows from the results, directing the reader to specific evidence to support the conclusions. Provide
explanations of results obtained. Compare results with literature or accepted values (please cite
these resources), and calculate percent error when appropriate.
EVALUATION:
SOURCES OF ERROR:
Use this section to analyze all relevant sources of error. Do not be vague and do NOT use the
phrase ‘human error’. List pertinent errors and specifically indicate how each one might have
impacted the results. In your analysis, evaluate the procedures and results. For procedures, consider
the following questions: Are there flaws in the procedures which could have affected the results?
Were important variables not controlled? Were measurements and observations reliable? Is precision
unknown because of lack of replication? [These would be considered systematic errors and address
limitations of the investigation.] For results, consider these questions: What is the uncertainty of the
results and how does it impact any conclusions made? [Uncertainty is considered random error.]
How does the uncertainty compare to the actual experimental error (% error, % yield). If the
experimental error is greater than the random error, account for any differences. If there were
experimenter errors, you may discuss them – but only if they first appear in your raw data.
SUGGESTIONS FOR IMPROVEMENT:
This is a work in progress. If you have any suggestions to improve this document, please let your teacher know.
Last updated 9/30/2009
Suggestions must be made on how to improve the investigation according to weaknesses identified
in “sources of error”. Suggestions should be realistic, not involving unavailable equipment or
materials. They should be specific and not vague (e.g. “more careful work”). Proposed changes
may do any or all of the following: eliminate or reduce errors, improve control of variables, reduce
approximations, and/or provide other procedures for better measurements. State if modifications are
unnecessary or impossible (i.e. standard or prescribed procedures were used).
This is a work in progress. If you have any suggestions to improve this document, please let your teacher know.
Last updated 9/30/2009