Title: What is the effect of Light intensity on the rate of photosynthesis?
Hypothesis: As the light intensity increases, hence the distance between the light and the
plant decreases, the number of bubbles produced decreases until the rate reaches a
plateau.
Table 1: Table of Variables
Table of Variables
Units
Range Examined
Independent Variable
Distance between plant and light
source
cm
0-100
Dependent Variable
Number of Bubbles Produced
Bubbles
0-1000
Control Variables
Temperature
CO2 Concentration
Units Possible effect on results
mL
Method for Control
(Explained in procedure)
The temperature is a factor that influences
Conduct all experiments in
photosynthesis. Higher temperatures will
the same room preferably
cause more bubbles and lower temperatures
at the same time
will cause less bubbles, affecting the results.
The greater the concentration, the more
Minut
bubbles produced. If concentration of CO2 is
es
altered, so will the results.
Conduct all experiments in
the same room preferably
at the same time
Time the plant is
The mass of the potato might alter the
Grams
submerged in the water
osmosis rate
Use a timer to time
Time for which bubbleMillim The length of the potato might alter the
counting is allowed
eters osmosis rate
A ruler was used to
measure the length of the
potato
Type of Plant
The type of potato might affect the solute
Use the same potato
concentration in the potato, altering osmosis throughout the
rate
experiment
The light source
If different lights with different intensity
were used, the number of bubbles produced
will be altered
Control Group
None
Use the same light for all
trials
Table 2: Effects of Light Intensity on the Number of Bubbles Produced Data Collection Table
Bubbles Produced Per Minute (Bubbles/min)
Distance from Light
Source (cm)
0
15
25
50
75
100
Uncertainty of Ruler
+/- 0.5
(mm)
Uncertainty of Bubbles
+/- 10.0
(Bubbles)
Trials
1
29.0
62.0
0.0
0.0
0.0
0.0
2
17.0
0.0
0.0
0.0
0.0
0.0
3
300.0
143.0
120.0
1.0
0.0
0.0
4
135.0
93.0
30.0
0.0
0.0
0.0
5
116.0
134.0
15.0
0.0
0.0
0.0
6
130.0
64.0
37.0
0.0
0.0
0.0
7
195.0
129.0
78.0
0.0
0.0
0.0
8
574.0
330.0
62.0
0.0
0.0
0.0
Observations:
Since there is no technical way to count the amount of bubbles produced by the plants
other than counting through the human eye, the uncertainty of the calculation will be
relatively large. The experimenters set the uncertainty for the bubbles to be +/-10 bubbles
because when the bubbles are being produced rapidly, a stream of bubbles arises in the
blink of an eye. As the experimenters replayed the video in slow motion, the experimenters
estimated that approximately 10 bubbles go pass with one blink of an eye. However, the
uncertainty of the ruler is +/-0.5mm.
There are two outliers presented in the data above, which are highlighted in yellow. The
0cm trial for the 8th trial is an outlier because 574 does not fall within two standard
deviations of the mean (574>547.524). The 15cm trial for the 8th trial is also an outlier
because 330 does not fall within two standard deviations of the mean (330>314.357).
Therefore, these two points are considered outliers and will be omitted from the data
processing.
For the 7th and 8th trial for distances 0cm and 15 cm, the experimenters noticed that the
bubbles were appearing rapidly and rose to the top in streams. Thus it made it really hard
to count the exact amount of bubbles produced since the bubbles were really small and
produced in large quantities. Also, the temperature for the 7th and 8th trail for distances
0cm and 15cm increased after the trial was conducted.
Process Data:
Processed Data (DCP Aspect 2)
Table 3: Effects of Light Intensity on Number of Bubbles Produced Processed Data
Table
Distance from Light Source (cm)
0
15
25
50
75
100
Average Number of Bubbles Produced
Per Minute (Bubbles/min)
131.7
89.3
42.8
0.1
0.0
0.0
STDEV
96.9
51.4
41.8
0.4
0.0
0.0
-0.7
Correlation
In this table, the average is calculated after the two outliers were removed from the data.
The corresponding standard deviation and correlation were adjusted to values after the
outliers were removed as well.
After conducting a t-test on the oxygen production for the 0cm to 100cm trial, the
experimenters suggest that there is a significant statistical difference between the data,
since the two-tailed P value was 0.0171.
Sample Calculations for Processed Data.
Average (Bubbles) (Calculated by Excel): (All the data for 0cm trial were calculated and
presented below)
Standard Deviation (Bubbles) (Calculated by Excel): (all data for 0cm trial were calculated
and presented below:
T-test (Calculated by GraphPad): (all data for 0cm-100cm trial were calculated and
presented below)
Slope (Bubbles/min) (Calculated by Excel): (all values for the 0cm-15cm trial were
calculated and presented below)
R-value (Calculated by Excel): (all values for the 0cm-15cm trial were calculated and
presented below)
Presenting Processed Data (DCP Aspect 3)
Graph 1:
The graph above illustrates the relationship between bubbles produced per minute and the
distance of the plant from the light source with the outliers removed. There is an indirect
relationship between the amount of bubbles produced per minute and the distance of plant
from light source- as the distance increases between the plant and the light source, the
amount of bubbles produced decrease. After conduction the correlation test, the
researchers found that the correlation is -0.7, indicating a moderate, negative correlation
between the two variables.
Graph: 2
The values for error bars are +/-96.9, +/-51.4, +/-41.8, +/-0.4, 0, and 0 for trials 0cm,
15cm,
25cm, 50cm, 75cm, and 100cm, respectively.
The error bars for distances of 0cm, 15cm, and 25cm have a slightly overlap with each
other. This suggests that there is not a really big variation between the data within those
parts. However, the error bars for the 0cm, 15cm, and 25cm trial do not overlap with the
errors bars for the 50cm, 75cm, and 100cm trial at all. This suggests that there is a big
variation between the data, and that the variation most likely is not due to chance. Thus the
difference is significant. However, the error bar for the 0cm trial is really big, meaning that
there is a big variation in the data.
The overall trend is as distance from the light source increases, average bubbles produced
per minute increases.
DISCUSSION, EVALUATION & CONCLUSION (Criteria DEC)
Discussing and Reviewing (DCE Aspect 1)
Light intensity affects the rate of photosynthesis. As the distance between the light source
and the plant, which indirectly measures light intensity, increases, the amount of bubbles
produced by the plant, which indirectly measures photosynthetic rate, decreases. There is an
indirect relationship between light intensity and photosynthetic rate.
The amount of bubbles produced measures the photosynthetic rate. The average amount of
bubbles produced per minute was 131.714 when the distance between the light source and
plant was 0cm, while during the 100cm trial the average amount of bubbles produced per
minute was 0. There is a big difference between the amounts of bubbles produced. Also, the Rvalue of -0.7 supports the moderate, negative relationship between the two variables. Thus,
the hypothesis is supported by the data collected in the investigation.
Photosynthetic rate is affected by light intensity, temperature, and carbon dioxide
concentration. Light intensity affects photosynthetic rate because as there is more light
available for the plant, there are more photons as reactants available for the chlorophyll to
react with. As the number of collisions increase, the photosynthetic rate increases
(Benckiser).
The experimenters cannot find accepted values for all distances in the experiment. The
experimenters compared the experimental values with those of another study conducted by
another experimenter as a reference (Light). The number of bubbles differed by a lot, which a
percentage discrepancy of 99% for the 50cm trial. However, the overall trend exhibited in
both experiments ware similar. The big percentage of discrepancy can be attributed to the
imprecise counting method, and the different light bulbs used in the two experiments. The
general trend shows the relationship between the independent and dependent variable: as
the distance between the plant and the light source increases, the number of bubbles
produced decreases; therefore assuring the accuracy.
Evaluating Procedures and Suggesting Improvements: (DCE Aspect 2)
A) ACCURACY, PRECISION and RELIABILITY
Since the experimenters could not find any accepted values of the experiment, it is hard to
determine the exact extent of accuracy of this experiment. However, the experiment should be
considered relatively accurate since it exhibits a similar trend to all the other studies the
experimenters found that were conducted on the same matter.
The data is relatively low in precision. The error bars for the 0cm, 15cm, and 25cm have
error bars that overlap, yet the error bars are really big. This shows there is a big variation in
the data, as all data points are quite spread out. Also, the standard deviation for trials 0cm,
15cm, and 25cm of data are really big. For example, the standard deviation for the 0cm trial
goes up to 96.9, which is a huge variation in data. There is a big standard deviation in our data
due to the imprecise measuring method. Also, the experimenters calculated the %
discrepancy between the experimenter’s trial and the class average for the 25cm trial. The
results were a % discrepancy of 30.9%, indicating a relatively large discrepancy. All
experimenters did a different trial, and each experimenter had a different counting method
for the bubbles. Thus, the data collected were not similar, indicating low precision.
The data is relatively reliable due to the trend found in the graph without outliers. As graph
2 indicates, there is an obvious observable trend showing that as the distance between the
light source and plant increases, the number of bubbles decreased. However, though the over
all trend is obvious, the R-value is -0.7, which is only a moderate value.
There are no known systematic errors presented in the data, since all data follow an
observable trend and all equipment were used correctly, assuring no systematic errors. Some
random errors have caused impacts on the data, which will be discussed in the experimental
weakness and limitations section below.
In conclusion, the overall accuracy of the data is adequate due to the observable trend in
the data. However, the precision is relatively low due to the big standard deviations in the
data. The reliability of the data is adequate due to the moderate R-value.
B) EXPERIMENTAL WEAKNESSES AND LIMITATIONS
The procedure was easy to follow and there were no major difficulties in keeping the
control variables constant, and all the independent variables were manipulated accordingly to
produce the most accurate and precise results possible.
The control variables were mostly kept constant throughout the experiment. The type of
plant used was ensured to be Cabomba, which ensures the relative amount of chlorophylls
involved in the reaction. The temperature of all trials would be the same since all trials were
conducted at the same time in the same room. The CO2 concentration was also held constant
throughout the experiment as all trials were conducted in the same room. The time the plant
was submerged in the water was a total of 3 minutes, which consists of 2 minutes of
observing and a minute of counting for all trials. The experimenters only started counting the
number of bubbles the Cobomba plants produced in each trial 2 minutes after the plant was
submerged. The counting continued for one minute for every trial. Lastly, the light used to
shine on the plants was consistent, as it was from the same light throughout all the trials.
These procedures ensure that the changes measured in the dependent variable were a true
reflection of manipulating the independent variable. This assures the fairness and validity of
the data.
Also, the range of the independent variable was not appropriate because starting from the
50cm trial, the data collected were almost all 0. This means that the distance between the
light source and the plant was already too big at 50cm, which means that any distance greater
than that would not have an impact on the data. Therefore, the range of the independent
variable was inappropriate.
Another weakness was the large spread of data in almost all trials. This spread is due to the
imprecise measuring method of measuring the bubbles. All experimenters used their human
eyes to physically count the amount of bubbles produced, which is really inaccurate,
especially for the trials of closer distance since the rate of bubbles being produced is so fast
that it is really hard to count every single bubble. This resulted in the large spread of data,
especially the first few trials with distances of 0cm, 15cm, and 25cm.
The equipment used was mostly accurate and precise. All the rulers used to measure the
length of the Cobomba plants were standardized, and all timers were standardized as well.
Some random errors were made throughout the experiment. For the first trial, the
experimenter cut the plant with a straight cut, while for all the other trials, the experimenter
cut the plant diagonally. Since the surface area might have an impact on the results produced,
this error might have altered the results for the 0cm trial from Group 8. However, the impact
can be ignored since Group 8’s 0cm trial data was already an outlier and omitted from the
analysis of data.
Also, the number of leafs on each plant was really hard to be kept consistent. Even though it
is easy to measure out the length of the plant and cut it accordingly, the number of leafs on
each of the sections of plants will still vary. Therefore, the amount of chlorophyll present to
allow photosynthesis varies amongst each plant. This is a considerable impact on the data
because the more leafs a plant has, the higher the photosynthetic rate and vice versa. Thus,
this limitation should be valued greatly.
Lastly, the rise in temperature should be considered, especially for the 0cm trial. Since the
higher the temperature, the greater the photosynthetic rate, and since the light was right next
to the plant for the 0cm trial, the temperature rose from 22 to 24, which most certainly had an
impact on the data. Thus, for at least the 0cm trial, both the light intensity and the
temperature altered the photosynthetic rate, which explains why there were so many bubbles
produced during the 0cm trial for all groups.
Overall, random errors can be ranked in the following order based on their impact on data
from smallest to greatest: the cutting method of the plant, the number of leafs on the plant,
and the rise in temperature for the trials. The impacts of how each individual factor affected
the data were discussed above.
The lack in trials is also a weakness of the experiment. 8 Trials might be enough to
determine the general trend of the data, but it is not enough to establish an experiment with
high precision.
The weaknesses of the experiment can be ranked in the following order based on their
impact on the data from smallest to greatest: inappropriate range of independent variable,
cutting method of the plant, the number of leafs on the plant, the rise in temperature for the
trials, the lack in trials and the imprecise counting method of bubbles which caused a large
spread in data.
Lastly, this experiment is not reproducible based on several reasons. First, the difficulty of
counting the air bubbles. As mentioned before, experimenters have different ways of counting
air bubbles, and as the experimenter changes, the results will change as well. Second, the wide
range of the individual data shows that the data is really wide spread, meaning that other
scientists have a smaller probability of getting the same results when they repeat the
experiment. Lastly, since there are too many variables that might change the data that would
be hard for experimenters to control, like the number of leafs on each plant, it is really hard to
produce the same results as those of this lab.
However, the overall reliability of the trend is high. The general trend shows an apparent
decrease in photosynthetic rate after an increase in distance between the light source and the
plant, which is supported by scientific evidence.
C) EXPERIMENTAL IMPROVEMENTS
In order to ensure the accuracy of the experiment and minimize the effects of random
errors, there are a few things that can be improved upon.
First of all, the experimenters should always keep in mind to keep a consistent cut while
cutting the plant, preferably a diagonal cut across the plant. If one of the plants were cut
inconsistently, the experimenters should cut another plant that has a diagonal cut. This will
help minimize the random errors made during the experiment.
Secondly, the appropriate data range should be set around a range from 0cm to 50cm, as
the experiment showed that any value above 50cm seemed to have no impact on the
photosynthetic rate. Therefore, appropriate trial distances should consist of trials with
distances such as 0cm, 5cm, 10cm, 15cm, 20cm, 30cm, 40cm, and 50cm. This way, the
experimenters can take a closer examination to see exactly how much each distance impacts
the data and photosynthetic rate.
Also, there should be a better way to measure the number of bubbles produced. A way to
improve this significant limitation is to use a camera device with the function of recording in
slow motion to record every trial, and the experimenters can play the video in slow motion
and count all the bubbles produced. This will significantly reduce the imprecision in data,
since most of it is caused by the poor bubble-counting method. A better improvement to this
limitation would be to use a Photosynthesis Measurement System called LCpro+ (ADC) that
allows experimenters to control the concentrations of CO2 and H20, therefore ensuring a
more precise experiment.
Moreover, the experimenters not only should keep the length of the plant consistent, they
should also keep the number of leafs on each plant relatively consistent as well. While they
cut the plants out, they should make sure the leafs on each plant are roughly the same, and
pull out the extra leafs on each plant. This will also reduce the imprecision in data because the
number of chlorophyll present in each leaf directly determines the rate of photosynthesis. By
controlling the number of leafs, which in turn affects the number of chlorophylls, the
experiment would improve in terms of precision.
In addition, the experimenters should pay attention to the change in temperature in the
trials. Since there is not a better way to keep the temperature constant, the experimenters
should just always consider the rise in temperature while evaluating the experiment.
Lastly, more trials should be conducted to ensure the reliability of the experiment. Eight
trials do not provide a strong scientific evidence for the investigated question. Therefore, by
increasing the number of trials conduced to at least 50 trials, it increases the chances of
having more precise, accurate, and reliable data.
Concluding: (DCE Aspect 3)
In conclusion, the distance between the light source and plant affects the production of
bubbles; hence the light intensity affects the rate of photosynthesis. The greater the light
intensity, the greater the amount of bubbles produced, hence the greater the photosynthetic
rate. For example, the 0cm trial had an average of 131.7 bubbles, while the 100cm trial had an
average of 0 bubbles, showing a clear decrease in the oxygen production. Therefore, the
relationship between light intensity and photosynthetic rate is established.
Reference Cited:
"ADC BioScientific Ltd." ADC Bioscientific. N.p., n.d. Web. 02 Mar. 2013.
Benckiser, Reckitt. "Rate of Photosynthesis: Limiting Factors." Rate of Photosynthesis: Limiting
Factors (n.d.): n. pag. Advancing the Chemical Sciences. RSC. Web. 31 Oct. 2014.
"Light Intensity and Rate of Photosynthesis (Carol Cao) - Sed695b3." Light Intensity and Rate of
Photosynthesis (Carol Cao) - Sed695b3. N.p., n.d. Web. 31 Oct. 2014.
Experiment Title:
Photosynthesis rate and light intensity
Student name:
SL
Submitted to Turn it In for plagiarism
check: Y
N
Teacher: Ms. Tyler
Date:
HL
Total
DATA COLLECTION & PROCESSING
ASPECT 1. Recording raw data
Records appropriate quantitative & associated qualitative raw data, including units & uncertainties where relevant.
Stu
Partial Incompl
Teac
den
(1
ete (0
her
t
mark) marks)
Complete (2 marks)
eval
che
uati
ckli
on
st
a. Includes descriptive table titles that summarize the investigation including the
Records Does not
independent & dependent variables (& if appropriate, essential control variables).
appropr record
b. Includes tables with correct column & row headings.
iate
any
c. The correct units are listed with column & row headings (units should not be included
quantit appropri
with the raw data).
ative
ate
d. Appropriate uncertainties have been estimated for all raw data & stated with the units
data &
quantita
(in column & row headings).
associat tive raw
e. All uncertainties are stated as absolute values (not percent) to one significant digit.
ed
data or
qualitat raw data
f. Data is recorded with the same precision as the uncertainty (i.e. with the same number of
ive raw is
decimal places as the uncertainty). *
data but incompg. The raw data is appropriate for the research question investigated & logical. Data must
with
rehensib
be collected independently.**
some
le.
h. If significant outliers are present, they are identified in raw data & omitted from Aspect
mistake
2. data processing.
s or
(None of
i. Justifies choice of uncertainty (considers precision/uncertainty of equipment plus any
omissio the
random errors that may significantly affect the variation in data e.g. parallax error when
ns.
points
measuring instruments cannot be clearly aligned with the measurement being made, human
are
reflex when timing, etc).
(Some
complet
j. Relevant qualitative data that may enhance and support the interpretation of the results
of the
ed.)
has been included.
points
are
omitted
.)
ASPECT 2. Processing raw data
Processes the quantitative raw data correctly &, where relevant, includes uncertainties & error bars.
Stu
Teac
den
her
t
Complete (2 marks)
eval
che
uati
ckli
on
st
a. If necessary, processes raw data into a form suitable for graphical representation (e.g.
adding, subtracting, averages, % change, rate etc.).
b. Processed data is recorded in a correctly formatted table (see aspect 1 above).
c. Calculates variation within trials by establishing standard deviation.
d. Determines if a significant difference exists between levels of treatment by performing a
t-test
e. Includes clearly labeled sample calculations for each method of data processing used.
(show one sample for each calculation made).
f. or if data is already in a form suitable for graphical presentation plots a suitable ‘best-fit’
curve or line graph.
DATA COLLECTION & PROCESSING continued on the next page
Partial
(1
mark)
Incompl
ete
(0
marks)
Processe
s
quantit
ative
raw
data,
but with
some
mistake
s &/or
omissio
ns.
No
processi
ng of
quantita
tive raw
data or
major
mistakes
are
made in
processi
ng.
(Some
of the
points
are
omitted
.)
(None of
the
points
are
complet
ed.)
ASPECT 3. Presenting processed data
Presents processed data appropriately & where relevant, includes errors and uncertainties.
Stu
den
t
Complete (2 marks)
che
ckli
st
a. Includes descriptive graph titles that make reference to the independent & dependent
variables (& if appropriate, essential control variables).
b. For graphs - Both axes are labeled with the correct units.
c. For graphs - Scale is even
d. For graphs - is sufficiently large (use at least half an A4 page) .
e. For graphs - Points are plotted accurately.
f. For bar graphs uncertainty in graphical analysis is accounted for by applying error bars
which are correctly drawn. Explains under the graph if error bars are not significant for
one or both variables.
g. For scatter-plot uncertainty in graphical analysis is accounted for by drawing an appropriate
line or curve of best fit
h. A brief description of trends/relationships observed in graphs is included.
Comments: ~ signifies that point was attempted but needs improvement to be considered complete
* Point h is a requirement for Aspect 3 if a Conclusion & Evaluation is not submitted for assessment.
Copyright: Science & Plants for Schools: www.saps.org.uk
Bubbling Cabomba Pondweed - Student Guide (revised 2012)
Teac
her
eval
uati
on
opti
onal
*
Partial
(1
mark)
Incompl
ete
(0
marks)
Presents
processe
d data
appropr
iately,
but with
some
mistake
s &/or
omissio
ns.
Presents
processe
d data
inappro
priately
or
incomprehensib
ly.
(Some
of the
points
are
omitted
.)
(None of
the
points
are
complet
ed.)
ASPECT 3. Improving the investigation (can be discussed with aspects 1 & 2 or in separate section)
Suggests realistic improvements for all identified errors, weaknesses and limitations.
Student
checklis
t
Complete (2 marks)
a. Suggestions on how to remove all systematic errors (if present) are made.
b. Suggests how the effect of all random errors could be removed or minimized. [Note: you can nearly always specify –
repeat more trials (except when there is a very high level of precision in data/very low uncertainty).]
c. Suggest how the control of variables could be improved (to ensure a fairer test of the variables, thus improving the validity
of the results).
d. Suggests how other significant weaknesses (e.g. management of time, large spread in data, etc.) could be improved.
e. Suggests how limitations in the procedure &/or equipment used could be improved (to increase accuracy &/or precision
of raw data, and hence, improve the reliability of the trend/relationship observed).
f. Improvement of all weaknesses & limitations identified in Aspect 2 are addressed.
g. Realistic, clearly specified improvements are suggested. Do not simply state generally that more precise equipment
should be used.
Copyright: Science & Plants for Schools: www.saps.org.uk
Bubbling Cabomba Pondweed - Student Guide (revised 2012)
Teacher
evaluatio
n
Partial
(1 mark)
Suggests only
superficial
improvements.
(Some of the
points are
omitted.)
Incomplete
(0 marks)
Suggests
unrealistic
improvements.
(None of the
points are
completed.)
Experiment Title:
Student name:
Submitted to Turn it In for plagiarism check:
CONCLUSION & EVALUATION
Teacher:
Ms. Tyler
Total
SL
Y
HL
N
Date:
ASPECT 1. Concluding
States a thorough conclusion, with justification, based on a reasonable interpretation of the data.
Student
checklis
t
Complete (2 marks)
Teacher
evaluatio
n
a. Research question is answered by correctly stating the relationship between the variables
b. Conclusion is justified by describing the trends or patterns revealed by the data and by referring to numerical data
from processed results.
c. States whether the hypothesis is supported or refuted by the data collected in this investigation.
d. If known physical quantities were calculated compares the experimental value(s) with the referenced accepted
value/s. May choose to calculate the percent discrepancy (error) between experimental and accepted value/s
e. If literature is used to determine accepted values then it must be referenced
Partial
(1 mark)
Incomplet
e
(0 marks)
States a
conclusion
based on
reasonable
interpretation of
the data.
States no
conclusion or
the conclusion
based on an
unreasonable
interpretation
of the data.
(Some of the
points are
omitted.)
(None of the
points are
completed.).
ASPECT 2. Evaluating procedure for controlling & measuring variables
Evaluates experimental weaknesses, limitations & reproducibility.
Student
checklis
t
Complete (2 marks)
Teacher
evaluatio
n
Partial
(1 mark)
Incomplet
e
(0 marks)
Identifies some
weaknesses &
limitations, but
the evaluation
is weak or
missing
Identifies
irrelevant
weaknesses &
limitations.
Accuracy & Precision
f. Accuracy of data collected is discussed. (Note: only required if known quantities were calculated, sources of systematic error
were evident or the quality of procedure/equipment used was questionable).
g. Precision of data collected is discussed [spread/variation (or uncertainty) in raw data indicated by standard deviation values].
h. Correctly identifies major systematic errors, if present [i.e. if all data points have shifted in same direction ]. The direction
of any systematic errors should be specified.
i. Correctly identifies sources of random error & discusses whether they had a significant impact on the data collected.
Experimental weaknesses and limitations
j. Fairness & validity is discussed (i.e. were there any unforeseen control variables / were all control variables kept constant, thus
ensuring a fair test that produced valid results, where changes measured in the dependent variable were a true reflection of
manipulating the independent variable).*
k. Other significant weaknesses (revealed during or after the experiment) are identified (e.g. management of time, large spread in
data, etc.).
l. Possible causes for any outliers (if identified) are discussed.*
m. Significant limitations (apparent before the experiment) in the ‘quality’ of procedure for manipulating & measuring
variables is discussed (data range & the number of data points manipulated/measured within the range, number of trials &/or
experimental techniques).
n. Significant limitations in the equipment used is discussed [precision (& if questionable, accuracy) of equipment]. [Note:
precision of equipment essentially refers to the number of decimal places (or power of 10) that could be measured with the instrument.]
o. Has some appreciation of the significance of weaknesses & limitations. (List in order of significance.)
Reproducibility & reliability of the experiment
p. Reproducibility of experiment is discussed i.e. whether another scientist could repeat the experiment & expect to get
the same results (Think: whether the method was detailed, explicit & easy to follow; whether the results were precise; and whether
the results were accurate).
Copyright: Science & Plants for Schools: www.saps.org.uk
q. The reliability of the relationship/trend observed Bubbling
is discussed
(depends
on the- Student
accuracyGuide
& precision
of 2012)
raw data, & how
Cabomba
Pondweed
(revised
close plotted data points are to the line/curve of best fit).
CONCLUSION & EVALUATION continued on the next page
(Some of the
points are
omitted.)
(None of the
points are
completed.)