Unit 6: Investigative Project
C: Safely undertake the project, collecting, analysing and presenting the results
D: Review the investigative project using correct scientific principles
Project implementation and review
Abstract
An experiment was conducted on how concentration affects the rate of diffusion, after having conducted a literature
review and generating a project plan. The hypothesis investigated in this project was: Increasing the concentration
of hydrochloric acid will increase the rate of diffusion in agar. This report will provide an outline of the project
including its method, analysis of results and a detailed description of the skills that were developed over the course
of the project.
Method
Cubes of agar with a surface area to volume ratio of 1x1 cm3 were placed into different concentrations of
hydrochloric acid, with water being used as a control. The time taken for the hydrogen ions to diffuse into the cubes
was recorded so that the rate of diffusion can be calculated.
Results
There is a clear positive correlation between concentration levels and the rate of diffusion. The time taken for
hydrogen ions to diffuse into agar gel decreased with increasing concentration of acid. A faster rate of diffusion was
observed when higher concentrations of hydrochloric acid were used. Two outliers were obtained due to human and
systematic errors.
Conclusion
Increasing the concentration of hydrochloric acid increased the rate of diffusion into the agar cubes and decreased
the amount of time needed for hydrogen ions to completely diffuse into the agar gel.
Introduction
Diffusion is defined as the movement of molecules from an area of high concentration to an area of low
concentration, whilst moving across a concentration gradient (this exists when a membrane separates two different
concentrations of molecules) [LibreTexts, 2018]. The concept of diffusion is backed up by Fick’s first and second laws
of diffusion. Fick’s first law explains the diffusive flux within a medium to the gradient of the concentration
[SimScale, 2023]: the diffusion flux (movement of molecules) from a region of high concentration to a region of low
concentration is directly proportional to the magnitude of the concentration gradient of a substance [Science Facts,
2020]. Fick’s second law states that diffusion causes a change in concentration over time [SimScale, 2023].
Aim of investigation
The aim of the investigation was to investigate the effect of concentration on diffusion rate in agar gel. This was
achieved by preparing the agar gel (by combining agar powder, distilled water and phenolphthalein), using different
concentrations of hydrochloric acid (0, 0.25, 0.50, 1.0, 2.0 mol dm-3), calculating the rate of diffusion for each
concentration and constructing a graph showing the relationship between concentration and diffusion rate.
Alternative hypothesis: Increasing the concentration will increase the rate of diffusion
Null hypothesis: The concentration of hydrochloric acid will have no effect on the rate of diffusion.
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,Unit 6: Investigative Project
C: Safely undertake the project, collecting, analysing and presenting the results
D: Review the investigative project using correct scientific principles
Variables
Independent variable: Concentration of hydrochloric acid
Dependent variable: Time taken for agar to turn colourless (rate of diffusion)
Control variables: Surface area to volume ratio of agar, number of cubes for each concentration
Equipment and method
● Agar gel
● White tile
● Stop clocks x5
● Scalpel x1
● 0, 0.25, 0.50, 1.0, 2.0 mol dm-3 hydrochloric acid
● 80 ml beaker x5
● Distilled water
● Permanent marker
1. Prepare dilutions of hydrochloric acid (see Appendix 1.0)
2. Prepare 1x1 cm3 agar cubes (see Appendix 1.1)
3. Label each beaker with the concentration of acid to be used with a permanent marker.
4. Pour the acid into its corresponding beaker.
5. Place a stop clock in front of each beaker
Figure 1: Experimental setup before placing agar cubes in solution
6. Place an agar cube in each beaker. Start the stop clocks immediately.
7. Stop the stop clock every time that any of the agar cubes have decolourised. Place each decolourised cube
into an empty beaker after each use.
Figure 2: Agar cubes after completely reacting with hydrochloric acid
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,Unit 6: Investigative Project
C: Safely undertake the project, collecting, analysing and presenting the results
D: Review the investigative project using correct scientific principles
8. Record this value in a results table.
9. Calculate the rate of diffusion by using the formula:
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𝑇𝑖𝑚𝑒 𝑡𝑎𝑘𝑒𝑛 𝑓𝑜𝑟 𝑐𝑜𝑙𝑜𝑢𝑟 𝑐ℎ𝑎𝑛𝑔𝑒 𝑡𝑜 𝑜𝑐𝑐𝑢𝑟
Results
Raw results: Time taken for agar to completely diffuse
Concentration of HCl Time taken for agar to decolourise (s)
(mol dm-3)
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
0 0 0 0 0 0
0.25 1336 1162 1200 1085 1391
0.50 770 714 709 668 844
1.0 622 476 468 630 659
2.0 536 565 391 534 501
Raw results: Rate of diffusion for each concentration
Concentration of HCl Rate of diffusion (s-1)
(mol dm-3)
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
0 0 0 0 0 0
0.25 0.00075 0.00086 0.00083 0.00092 0.00072
0.50 0.0013 0.0014 0.0014 0.0015 0.0012
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,Unit 6: Investigative Project
C: Safely undertake the project, collecting, analysing and presenting the results
D: Review the investigative project using correct scientific principles
1.0 0.0016 0.0021 0.0021 0.0016 0.0015
2.0 0.0019 0.0018 0.0026 0.0019 0.0020
Results from average time taken for agar to decolourise
Concentration of HCl (mol dm-3) Average time taken for agar to decolourise (s)
0 0
0.25 1235
0.50 715
1.0 571
2.0 534
Results from average diffusion rate
Concentration of HCl (mol dm-3) Average rate of diffusion (s-1)
0 0
0.25 0.0008
0.50 0.0014
1.0 0.0018
2.0 0.0020
Statistical testing
Standard deviation
Standard deviation serves as a measure of how spread out the data points are around the mean
[TheKnowledgeAcademy, 2023], which allows me to assess the consistency of diffusion rates within each
concentration level. Using standard deviation is a valid approach for evaluating the effectiveness of my experiment
and understanding the variability within my data. By calculating the standard deviation for each concentration, I
would be able to compare the variability between different concentrations, identify outliers and determine the
significance of any observed differences. However, standard deviation has limitations. Outliers can have an effect on
standard deviation [Bobbitt, Z. 2023]. When significant outliers exist in a set of data, the standard deviation number
can increase and give a false representation of the spread of values in the dataset [Bobbitt, Z. 2023].
Figure 3: Formula for working out standard deviation [Dixon, K. 2021]
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, Unit 6: Investigative Project
C: Safely undertake the project, collecting, analysing and presenting the results
D: Review the investigative project using correct scientific principles
Standard deviation results
Concentration of HCl (mol dm-3) Standard deviation value
0 0
0.25 0.000082
0.50 0.00012
1.0 0.00026
2.0 0.00030
(See Appendix 1.3 for full calculation)
Spearman’s rank correlation coefficient
Spearman's rank correlation coefficient evaluates the strength and direction of a link between two ranked variables
[Gupta, A. 2023]. It measures the consistency of the relationship between two variables and how effectively the
relationship can be described by a function that is constant [Gupta, A. 2023]. Using Spearman’s rank correlation
coefficient is a suitable statistical test for my data because it does not make assumptions about the distribution of
my data [Statistics Solutions, 2022]. In my experiment, the relationship between concentration and rate of diffusion
is not linear [Laerd Statistics, 2018]. Therefore, Spearman's rank correlation coefficient can properly represent any
monotonic relationship between my two variables, whether it is increasing or decreasing [Laerd Statistics, 2018].
However, there are some limitations to this statistical test. Spearman's rank correlation coefficient takes only the
relative rankings of the variables into account rather than their actual values [Laerd Statistics, 2018]. This loss of
information may result in a less precise measurement of the relationship between concentration and rate of
diffusion [Laerd Statistics, 2018]. While Spearman's rank correlation coefficient can handle certain non-linear
relationships, it can be difficult to capture more complicated non-linear patterns in data [Statistics Online Support,
n.d.]. If the connection between concentration and rate of diffusion is extremely nonlinear, different statistical
methods may be needed [Statistics Online Support, n.d.].
Figure 4: Formula for calculating Spearman’s rank correlation coefficient [Data Analytics, 2019]
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