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Your Name
Date
Mr. Conte
IB Biology ---Level
Block----
Title
Investigating the effects of changing hydrogen peroxide solution concentrations on the enzyme
activity of catalase in Solanum tuberosum (potato).
Introduction:
Sets the scene for the lab. Gives background information. Needs references.
In this particular lab talk about enzymes and specifically catalase, where is it found, what is the reaction
that it catalyses. What are the products etc?
DO NOT just write everything you know about enzymes. What you write must be relevant to catalase
and this specific lab.
Finish the introduction by leading into the lab. Such as: The purpose of this lab is to investigate……
DESIGN:
Aspect 1: Defining the problem and selecting variables.
Research Question:
What is the relationship between changing the concentration of the substrate hydrogen peroxide (H2O2)
solution from 0% to 5% and the enzyme activity of catalase in Solanum tuberosum as measured by the
amount of froth produced when pieces of S. tuberosum are placed into the H2O2 ?
Hypothesis:
If we increase the concentration of the substrate H2O2 from 0% to 5% then we would expect to see an
increase in enzyme activity because (scientific reason with reference)
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Units of measurements:
Independent Variable:
H2O2 concentrations (%)
Uncertainty for concentration (+/- 0.5%)
Dependent Variable:
Thickness of the froth (mm)
Uncertainty for thickness (+/- 1.0 mm)
Controlled Variables:
Same size piece of S.tuberosum
Same volume of H2O2 for each concentration
Same time period that each sample of potato is exposed to the H2O2 solutions.
Aspect 2: Controlling variables.
Independent variable:
Two mL of each concentration of H2O2 solution will be added to the potato pieces. Five levels of
treatment will be used plus a control: 0% (control), 1 %, 2%, 3%, 4% and 5%. Each level of treatment will
be repeated three times.
Dependent Variable:
Enzyme activity of catalase in S.tuberosum will be determined by measuring the thickness of froth
produced after 30 seconds using a mm ruler.
Draw a diagram so that there is no confusion at all as to what you are measuring
How each controlled variable is kept constant:
Table 1: Controlled variables and methods for controlling and monitoring them.
Variable
Same size pieces of
S.tuberosum
Same volume of
H2O2
Same time period
that each sample of
potato is exposed
to the H2O2
solutions.
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Method to control
Aspect 3: Developing a method for collection of data:
Materials:
BE HIGHLY SPECIFIC
Exactly what equipment, quantities and sizes. Put it in a table if it helps
Procedure:
BE HIGHLY SPECIFIC and it must be able to answer your research question
Do simple sketches to help explain how to set up the lab
Your procedure must be written so that anyone could read your procedure and carry out your
investigation exactly the same way you did.
Your procedure must attempt to answer the research question.
If the lab is only for Design then in the last point of your procedure draw up the table to show how
your results will be recorded.
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DATA COLLECTION and PROCESSING
Aspect 1: Collecting Raw Data
Table #: Title must include as a minimum the independent and dependent variables and name of species.
It must be clear as to what information is in the table.
Example:
Table 1: Relationship between the effects of changing water temperature in which samples of Elodea sp.
are grown in from 25oC to 50oC and the volume of gas produced in 24 h by the Elodea sp. samples. Five
trials were conducted at each level of treatment. Irregular observations are also recorded.
Independent variable
(Units and Uncertainties)
5 levels of treatment to
determine possible trend
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Trial Number
At least three trials.
More is better
Dependent variable
(Units and Uncertainties)
Irregular
observations
Aspect 2: Processing Raw Data
Table #: Title must include as a minimum the independent and dependent variables and name of species.
Independent variable
(Units and Uncertainties)
Average…
(Units and Uncertainties)
Standard Deviation
Sample Calculations of how average was calculated and how you calculated the standard deviation.
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Table #: Accuracy of the data. Title must include what information is contained in the table.
Independent
variable
(Units and
uncertainties)
Literature
value
(theoretical
value)
Taken
from……
(units)
Our average
of the
dependent
variable
(Units and
uncertainties)
Our
calculated
range of
values taking
into account
the
uncertainty
(units)
Does the
literature
value
(theoretical
value) fall
within our
calculated
range of
values
(yes or no)
Deviation
from
literature
value
(%)
Accuracy*
of the
data
* Determination of “accuracy”. We will consider our average’s accuracy to literature values based on its
deviation from the literature value on the following arbitrary scale. Accuracy will be determined by the
deviation of our values from the literature value not just if the literature value falls within our range of
values.
≤ 5%
High accuracy
6% to 9 % Moderate accuracy
≥ 10 %
Low accuracy
Sample calculations: Show one sample calculation for every different type of calculation performed.
Deviation from literature value (%) =
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literature value – our average x 100
literature value
Table #: Precision of the data. Title must include what information is contained in the table.
Independent
variable
(units and
uncertainties)
Average of the
Dependent variable
(units and
uncertainties)
Standard
Deviation
The % that the
standard deviation
is of the average
value.
Precision* of
the data
* Determination of “precision”. We will consider our measurement’s precision based on the percentage
the standard deviation is of the average value on the following arbitrary scale.
≤ 5%
High precision
6% to 9 % Moderate precision
≥ 10 %
Low precision
Sample calculations: Show one sample calculation for every different type of calculation performed.
Precision (%) = Standard Deviation x 100
Average value
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Table #: Summary of the accuracy and precision of our results.
Independent variable
(units and uncertainties)
Accuracy of our results
Precision of our results
Statistical Analysis.
Perform an unpaired two tailed T-test on the averages from the first and last values of the independent
variables to determine if there is a significant difference between the two averages.
Ho: State your null hypothesis. There is no significant difference between the average……… at the 0.05
level of significance.
Table #: Title
Independent variable
Average of the
dependent variable
Standard Deviation
Number of
measurements to
calculate average
Significance level at which the critical value of t is determined = 0.05
Degrees of freedom = (n1 + n2 – 2)
Critical value of T =
Calculated value of T =
p value (<0.05 or > 0.05) =
Is there a significant difference between the two averages at the 0.05 level of significance?
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Aspect 3: Presenting Processed Data
There are so many graphs that you could draw. Concentrate on the ones that help to answer the
research questions. Don’t go drawing graphs for the sake of drawing graphs. Apart from the graphs
shown and depending on the data you can draw graphs to show:
maximum and minimum error bars,
compare literature values to your calculated values.
the range of values taking into account the uncertainties.
As a minimum the two graphs below are very helpful.
Figure #: Average volume of gas produced by 10 g of Elodea in 24 hours at temperatures ranging from
25.0 oC-50.0 oC. Error bars indicate ± one standard deviation from the mean
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Figure#: Average volume of gas produced by 10 g of Elodea in 24 hours at temperatures ranging from
25.0 oC-50.0 oC. Trend line is shown with r2 value.
* Determination of the strength of the correlation between the variables (r2) we will use the following
arbitrary scale
0.00 to 0.39 = Weak correlation
0.40 to 0.69 = Moderate correlation
0.70 to 1.00 = Strong correlation
Conclusion and Evaluation.
Aspect 1: Concluding
NEVER SAY WORDS LIKE PROVEN or CORRECT. A hypothesis can only be supported or not supported.
Does the data support the hypothesis? What data do you have that suggests that the hypothesis is
supported or not supported? Base your conclusion on trends in graphs, comparisons of graphs, R2 values,
T-tests etc. Refer to the data in your conclusion. E.g. The trend line in Figure 1 shows that there is a
positive, linear relationship between the temperature in which S.cerevisiae are grown and the rate of
cellular respiration. As the temperature increase the rate of rate of cellular respiration also increases.
The correlation coefficient of 0.9 indicates that it is a strong relationship between….
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Report your statistical analysis like this; There is a significant difference between the average IQ of ISM
students taking science course and students not taking science courses at the 0.05 level of significance.
ISM students taking science courses had higher IQ scores (M = 121, SD = 14.2) than did those taking
other courses (M = 117, SD = 10.3), t(44) = 1.23, p = <0.05. (The 44 refers to the degrees of freedom)
Explain your results using biological theory. What biological process is occurring?
Compare your results to reference material. That is, how accurate are your calculations? Can you
explain why you may not be accurate in your evaluation. How close as a percentage did your values
deviate from theoretical values? Can you explain differences or at least suggest possible reasons why
your values differ from the literature?
Aspect 2: Evaluating Procedures and Aspect 3: Improving the Investigation
Table # : Evaluation of procedure and suggested improvements.
Level of treatment
of independent
variable
(Units and
uncertainties)
Type of error
(systematic or
random)
Did this affect the
accuracy or
precision of the
data?
In what way did it
affect the accuracy
or precision of the
data?
How could this be
improved for
further
investigations?
Apart from the control of variables in your procedural weakness include items such as :
Levels of treatment. Were there sufficient levels of treatment to determine if a trend is evident? If not
what do you suggest?
Number of trials at each level of treatment. Were there a sufficient number of trials at each level of
treatment to gather sufficient data to answer the question accurately? If not what do you suggest?
Don’t just say things like, “do more”. Generally to perform a T-test we like to have at least 10
measurements in each sample.
Notes on random and systematic errors.
Random errors.
Random errors are errors in measurement that lead to measurable values being inconsistent when
repeated. For example in five trials at one level of treatment to determine if increasing temperature affects
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the rate of cell respiration in yeast, one of the trials had less yeast than the other four trials.
Random errors affect the precision of the data.
How were random errors minimised?
Systematic errors.
Systematic errors are biases in measurement which lead to the situation where the mean of many
separate measurements at one level of treatment differs significantly from the actual value of the
measured variable. For example at one level of treatment to determine a change in mass of a variable ,
the experimenter accidently left her pen on the weighing scale while measuring the mass. Systematic
errors affect all the results of the trials the same.
Systematic errors affect the accuracy of the data.
How were systematic errors minimised?
Bibliography or Reference List (you may use footnotes if you wish)
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