How to Structure a Lab Report
Background Statement:
This is a short paragraph citing background information on the experimental topic that you have researched before you
carry out your investigation. Be concise and focused on your study question.
Question:
 This should be a scientific (testable) question you intend to answer by way of your experiment.
 Not a Yes/No question
 Should use language like “how”, “which”, or “why”
 Example: “How does the amount of light entering the eye affect the size of the pupil of the eye?
Hypothesis:
 Includes your educated guess (prediction) of what your results will be and why you expect them (prediction reason).
 For my class, it must take the form of “If (independent or manipulated variable) then (dependent or responding
variable) because (prediction reason).” Example: “If the amount of light that the eye is exposed to is decreased, then
the pupil will increase in size, because the eye is trying to acquire as much light as possible.”
 Don’t just say, “I think it will have an effect because…” – You need to specify what kind of effect you think it will
have.
Materials:
 A detailed list of the items you’re going to need: types of glassware, measuring tools, chemicals, etc. This should
include approximate quantities and makes and models of instrumentation, if applicable.
 Don’t need to include things like pencils and paper, unless they are being used for something special.
Procedure:
A numbered list of logical steps, not a giant paragraph, and each step starts with a verb. The point for “Logical Steps” is
given when the reader can tell what you did, and that what you did actually served to help you answer your question.
 Experiments typically have 3 types of variables in them, and your procedure should make it obvious what you chose
for each of them. The 3 types are defined as follows:
Independent or Manipulated Variable (IV): (only 1)
 The thing you’re changing on purpose from test to test – identify it.
 Is often found in the first part of the inquiry question: “How does the amount of light entering the eye (IV)
affect the size of the pupil of the eye?”
 You must include at least 3 levels of manipulation. For example, you would measure the response of the pupil
of the eye to three different light intensities.
Dependent or Responding Variable (DV): (only 1)
 The thing you’re measuring to determine if your manipulated variable made a difference (the results of your
tests) – identify it.
 Is often found in the second part of the inquiry question: “How does the amount of light entering the eye (IV)
affect the size of the pupil of the eye (DV)?”
Controlled Variables (CV): (At least 3 – 3rd CV allows you to be awarded the point for validity)
 These are the things you need to keep the same from test to test, so you can be sure that it was in fact your one
independent variable that made the difference in your results, not something else.
 Only list things that might actually make a difference; it is unimportant, for example, to mention that subjects
wore jeans, but it would be important to mention that they were all the same age and had good eye health.
Controlled variables are a validity measure for your experiment.
 You would want to list as many relevant controlled variables as you can think of, but your grade is only
affected if you have less than 3. If you only list 1 or 2, your grade will be affected unless I personally can’t
think of any more either.
 I should be able to tell what you had in mind for Independent (IV), Dependent (DV), and Controlled variables
(CV) by reading your procedure, so I would like you to underline and label each of these variables as they
appear.
 There are three additional elements in your procedure. They are:
Experimental Control (EC):
 This is the group that is not subjected to the manipulated variable and is therefore used to compare the results
of the group that was subjected to the manipulated variable.
Repeated Trials (RT): (At least 3 total trials)
 You need to mention (and do) repeated trials for each type of measurement.
Recorded Measurements (RM):
 You must specifically say that you recorded the measurement, not just that you took the measurement, and
identify what kind of data you took – that reveals what your RV was.
Data, Data Tables and Graphs:
 Measurements should be recorded to the proper significant figures.
 Has a title with the IV and DV clearly labeled. Example: “Light Intensity vs. Pupil Size”
 Rows, columns, and axes are correctly labeled and show units of measurement used (Examples: cm, inches, degrees
Celsius, etc.).
 Data tables are organized charts, showing multiple trials and average values calculated (only for number data – can’t
do averages of descriptive data).
 Generally, graphs display only the average data.
Conclusion:
 Your goal is to make this concise but informative: it shouldn’t be really long, but it needs to contain the important
information.
 Claim: conclusion statement; summarizes the general findings of the investigation by answering the investigative
question.
o Example: “In the investigation of how light affects pupil size, our findings suggest that as the light
intensity decreased, the size of the pupil increased.” Do not be vague!
 Evidence: supporting data from the data table; references the lowest average data point and the highest average data
point and each condition that caused it.
o Example: “The smallest pupil size was 3.3 mm when the light intensity was the highest. The largest pupil
size was 3.3 mm at the lowest light intensity.”
 Reasoning: explains how this data supports your conclusion. Compares high and low values of data, e.g. how much
more or less. Identifies the trend in the data and provides a scientific explanation for the trend.
o Example: “The size of the pupil was 1.5 times larger at the low light intensity than at the high light
intensity. The data showed the following trend, as light intensity decreased the pupil size increased. The
probable reason for this reaction is that the pupil decreased when light intensity is high to limit the
amount of light that can enter the eye and increases when light intensity is low to allow more light into
the eye. Too much or too little light inhibits the ability to see.
 Note 1: It does not matter what order you mention the high and low data points in.
 Note 2: If averages are calculated, use those only – do not give individual trial data here.
 Note 3: Always include units of measurement, and never round data (say “12.7 seconds,” not “about
13 seconds” when quoting it in the conclusion –the conclusion must exactly match what you reported
in the data table.)
 Note 4: You must use the extremes of your data (specifically, the data for the extremes of your DV).
Comparing just the low and medium pupil size data is not as compelling. (Nor should you mention
all the data, because I want to see if you can identify the most compelling data, not just restate the
entire data table – more is not always better.)
 Note 5: Data is not always linear. With linear data, the high and low extremes of your DV are the
same two data points as the high and low extremes for your IV conditions. (Linear data is data that
consistently goes up or down as your IV changes.) You must always provide the results for high
and low extremes of your DV, even if those two extremes were not caused by the extremes of
the IV.
Error Analysis
 Identify two specific errors that did occur or could have occurred (e.g. miscalibration of instrument, procedural error,
etc.) This is not random/human error (e.g. misreading a device, not recording data correctly etc.) Explain how these
errors affected your final results (i.e. did the error inflate your data?).