BIOLOGY LAB REPORTS
A formal lab report is a written report of the experiment which tells the reader:
 why and how the experiment was done
 the results of the experiment
 what the results of the experiment mean.
Formal lab reports should be written in the past tense and should contain formal language.
A logical format should be followed when preparing the lab report which enables the reader to understand
everything that was done. In Biology, you will follow the format as described below. Note, however, that not all
biology labs will require a formal lab report.
Formal Lab Report Format
The top of the first page should contain the underlined title of the lab in the center of the page. The date should be
placed in the top left corner and the name of the scientist (your name) should be in the top right corner with your
partner’s name(s) beneath yours.
The following is a list of sections in the report along with instructions as to what is required in each section. All
sections should be in bold font.
1. Introduction
This is the first section of your lab report. An introduction outlines the background information on the topic/question
addressed in the lab experiment. Where appropriate you should research the topic and be sure to reference any
sources you use.
The purpose of the introduction is to lead the reader logically into the purpose of your lab. As such, the introduction
should include a statement of the purpose of your lab. The purpose of the experiment is the general aim (usually
given by your teacher or stated in the handout) of the lab activity. This should be followed by a clear, concise, and
focused statement of the specific problem you are investigating, written in your own words, and preferably stated in
question format.
A poor problem definition would be: “What factors affect plant growth?” or “Is
water a good solvent?”
A focused problem would look something like this:
“How does wavelength of light affect plant growth?” or
“Is vinegar as effective as water in dissolving different kinds of solutes?”
2. Hypothesis
The hypothesis should be directly related to the problem and should include a prediction statement. It should be
written as a testable statement about what you think is going to happen when you change one variable. If
appropriate, you should quantify certain variables in your hypothesis. The hypothesis statement may be followed
by a brief explanation.
A poor hypothesis would be: “Light affects plant growth.”
A good, testable hypothesis would look something like this:
“If _________, then __________ (because __________).”
For example: “If identical plants are exposed to light of different wavelengths
indicated by colors, then the rate of growth will increase as light wavelength
increases.”
3. Experimental Design
You need to identify the variables that you will control and manipulate in your experiment. Variables are factors or
conditions that could change in an experiment. There are 3 kinds of variables that you need to take into account.
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Independent variable – the factor/condition being tested; it is also sometimes called the experimental or
manipulated variable. (In our example, light wavelength is the independent variable.)
Dependent variable – the factor/condition that is expected to change in response to a change in the
independent variable; it is also sometimes called the responding variable. (In our example, rate of plant
growth is the dependent variable.)
Fixed or controlled variables – the factors/conditions that must be maintained constant or the same in all
set-ups. (In our example, the fixed variables include: same species of plant, same amount of water given
to set-ups, same temperature, same type of soil, same amount of soil, etc.)
Notice that the independent and dependent variables are embedded in a well-stated hypothesis.
Next, you will have to describe (or draw a diagram) the experimental set-up(s)/group(s) by specifying the various
treatments you applied to it (them). In our example, you could have 3 experimental set-ups: you could expose one
plant to short light wavelength (represented by blue color); another plant to medium wavelength (green); and then
another to long wavelength (red). You also need to include a control set-up/group (or simply called “control”) in
order to cancel out the effects of variables other than the one you are testing, i.e. the independent variable. This
way you can be sure that the effect (i.e. dependent variable) is due to the action of the independent variable and
none other. In our example, the one control set-up is a plant that is not exposed to light at all, but will receive the
same treatment of fixed variables as the other experimental set-ups. Another control set-up you could add is a
plant that is exposed to white light,without any color filters. Note that, in some cases, an experiment does not
require a control. For example, if you are comparing the pH of water against other liquid substances, it is not
possible to come up with a set-up with no pH!
An easy way to manage the diagram is to simply take a photo of the set-up during the actual lab with a phone or
laptop, then paste (and label) it into the report.
4. Materials:
List the materials and apparatus that you used for this lab. Include important details like mass, volume, and
concentrations of chemicals and solutions, the capacity of glassware, and the type/model of equipment used.
Example:
1 – red 100-watt lamp
1 – green 100-watt lamp
1 – blue 100-watt lamp
20 – Vigna radiata seedlings of the same height
planted in small pots
1 – ruler
1 L tap water
5. Safety Precautions
Record the necessary safety information and special hazards of all materials used in the experiment. Describe
what you did to make sure that these hazards do not become a problem to you.
6. Procedure
The purpose of this section is so that another scientist will know what you have done well enough to exactly repeat
your experiment. Be sure to follow the guidelines below:
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Numbers, “bullet points”, or a flow chart can be used to explain the procedural steps.
Avoid the use of I, we, us, etc. -- write in the “third person”.
Use command form.
Don’t forget the quantities and the correct units. Procedural details not only provide relevant experimental
information but also show how you are keeping certain variables fixed, while changing others.
Where appropriate, it is important to outline why one approach is taken versus another.
If you have made any changes from your original plan, your final report should reflect those changes.
Often times, steps are planned to control certain variables. If you do not feel the purpose to a step is
obvious, it can be beneficial to explain why you have chosen to make it.
Keep in mind to clearly mention what specific data will be recorded and how often the measurements will
be replicated (generally at least 3-5 trials must be taken).
7. Observations and Results
This section is a record of the data collected data during the experiment (raw data) as well as processed/calculated
data (results). Quantitative raw data should be presented in table form. Be concise in your descriptions of
qualitative data but be thorough as well. Report any changes in procedure or unusual conditions. Some labs
would require you to draw your observations instead; make sure that your drawings are labeled. Graphs are
another way of presenting both/either raw and/or processed data.
All numerical data tables, graphs, and drawings should be clearly identified with number and title. The title must be
informative – they should concisely summarize what was done to obtain the data in your table or graph. Correct
units and consistent decimal places must be used for all data. Make sure that your data reflects the precision of
your measurements by using the correct number of significant digits. Here is an example of a well prepared raw
data table.
Table 1. Height of bean seedlings exposed to different colors of light over 10 days.
Height of Plants (cm)
Day
1
2
3
4
5
6
7
8
9
10
Red
Blue
Green
White
No Light
2.2
2.5
3.1
3.4
3.8
4.5
4.9
5.6
5.9
6.3
2.1
2.4
2.9
3.5
4.0
4.7
5.1
5.8
6.4
7.0
2.2
2.3
2.5
2.8
3.4
3.9
4.3
4.7
4.9
5.1
2.1
2.4
3.0
3.4
4.1
4.8
5.5
6.3
7.2
8.5
2.1
2.1
2.1
died
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Results are different from data. Results are what happens to the raw data after you do a calculation (say,
computing the rate of growth from raw data). They are what ‘result’ after you manipulate the data. Your results
may be presented in the form of table, graph, or labeled drawing. Furthermore, if calculations are done, it is
necessary to show how you manipulated the data, i.e., show your calculations. A brief explanation of what you are
doing at each stage of the calculation is just as important as the calculation itself. For each type of calculation you
perform, ONE SAMPLE calculation should be shown. The sample calculation must include 1) the appropriate
formula, 2) the substitution of appropriate numbers (data), 3) the final answer and 4) a clear statement of what the
calculation is for or what particular data is pertains to.
In many cases, the raw data and results can be presented in a single table. In the example table given above, you
may incorporate the mean and standard deviation at the bottom of columns, constituting the processed data.
A graph is a visual representation of data. The most common types of graph that you will use are:
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Line graph – used to show the relationship between the dependent and independent variables,
DO (mg/L)
DO at Different Temperatures
14
12
10
8
6
4
2
0
R2 = 0.9787
0
10
20
30
40
Temperature (oC)
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Bar graph – used to show how one category is different from others; note the gaps between
categories.
Source: http://www.ehow.com/how_4450338_make-bar-chart-excel.html
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Histogram – similar to a bar graph, but there are no gaps between the bars because they are directly
related/continuous with the ones on each side.
Source: http://media.techtarget.com/digitalguide/images/Misc/iw_histogram.gif
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Pie chart – used to show proportions of the whole.
Source: http://www.dpi.nsw.gov.au/__data/assets/image/0003/110496/barraba-pie-charts.gif
Let’s focus on the line graph, since there are a number of biology labs that require this type of data presentation.
When you construct a line graph, follow these guidelines:
 Dependent variable is on the y-axis.
 Independent variable is on the x-axis.
 Scale divisions should be simple; intervals should be uniform.
 LABEL THE AXES! Make sure you include the UNITS.
 Don’t forget the TITLE – should be informative; it could be the same title as the corresponding data
table.
 If you have many graphs in one lab report, NUMBER them accordingly.
8. Conclusion and Evaluation
This is the section where you explain and analyze the results of your experiment and draw a conclusion(s). It
shows that the purpose was fulfilled. You should state your conclusion clearly and also state if you accept or reject
your hypothesis. Next, you should briefly justify the concluding statement in terms of the data that you have
processed. Any calculated results should be compared to values from the literature (i.e. accepted values from
professional laboratories) where possible.
This section should include:

Conclusion based on your Hypothesis:
o States the relationship between independent and dependent variables
o Correctly interprets the graph of the data or results (this is the “analysis” part)
o If appropriate/possible, compares results with those in literature in support of conclusion
o Includes some elaboration based on the science being learned
Example:
In conclusion, I reject my hypothesis. The average growth rate of V. radiata seedlings did not increase with
increasing wavelength of light. In the experiment, white light which incorporates all wavelengths of visible
light, produced the highest growth…
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Discussion of errors and limitations of the experiment
o Must comment on the “quality” of the results: do they make sense?
o Identifies anomalous results where appropriate
o Prioritizes errors and suggests where they came from
o Focuses on “procedural/systematic” and “random” errors
o Human errors should not be the main source of errors!
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Suggestions for improvements
o Identifies weaknesses in the experiment and suggests realistic suggestions for improvement
o Improvements should help to improve the errors previously identified (there should be a
corresponding improvement suggestion for every error mentioned)