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Experimentation
Experimentation
(a) Pilot study
(a) Pilot study
Integral to the development of an investigation, a pilot study is used to help plan procedures, assess validity and check techniques. This allows evaluation and modification of experimental design. The use of a pilot study can ensure an appropriate range of values for the independent variable. In addition, it allows the investigator to establish the number of repeat measurements required to give a representative value for each independent datum point.
Reference for image: Smith, B. and Campbell, D. (2016), SCHOLAR Guide: CfE Advanced Higher Biology Unit 3, Edinburgh, Heriot-Watt University, Available from https://scholar.hw.ac.uk/ [accessed on 06.04.20]
Go to SCHOLAR to try the "2.2.1 Pilot Study Examples" and "2.7 Extended response questions".
Task 3
Task 3
Wee Jonny couldn't wait to get to Biology on Wednesday. He burst in through Dr McRobbie's classroom door: "Miss, I have this mad wee experiment to do today, don't I?"
"Yes, Jonny, you do - You are going to investigate if aspirin inhibits catalase activity".
Jonny thought for a second: "Och, naw Miss, are we working with those tatties again?"
Dr McRobbie had some exciting news for wee Jonnie: "No Jonny, we are using liver as the source of catalase today".
Jonny was beyond delighted. He was feeling a little cautious so opted for the "height of foam" approach. He collected his apparatus and set up his control first - in this tube, he added hydrogen peroxide and detergent before enthusiastically lobbing in 1g of liver. His smile beamed from ear to ear as the foam, resulting from oxygen production, rose up the test tube. After a minute, he could cope no more and measured the height of foam using a ruler.
Wee Jonny repeated the experiment by placing hydrogen peroxide, detergent and 0.01% aspirin into the test tube before finally kicking things off with 1g liver.
The results are shown below.
Wee Jonny concluded that aspirin did not inhibit catalase activity. Is this a valid conclusion? How could he improve his approach to this investigation using a pilot study?
Suggested answers to this task can be found here.
(b) Experimental Design
(b) Experimental Design
Independent and Dependent Variables
Independent and Dependent Variables
An independent variable is the variable that is changed in a scientific experiment. It is manipulated by the investigator. An independent variable could be continuous (e.g. temperature) or discrete (e.g. named inhibitors of enzymes).
A dependent variable is the variable being measured in a scientific experiment. It could be continuous (e.g. the absorbance of a solution) or discrete (e.g. type of behaviour existed by an organism following a stimulus).
In all investigations, a control group should always be included for comparison to the treatment group, e.g. when investigating the effect of caffeine on Daphnia heart rate, a suitable control group would involve measuring Daphnia heart rate in the absence of caffeine.
Tired of reading? Let's review Pilot Studies, Variables and Controls in this short video.
Tired of reading? Let's review Pilot Studies, Variables and Controls in this short video.
Go to SCHOLAR to try "2.3.3 Controls".
Discrete and continuous variables give rise to qualitative, quantitative or ranked data:
Qualitative data is subjective and descriptive.
Quantitative data can be measured objectively, usually with a numerical value.
Ranked data refers to the data transformation in which numerical values are replaced by their rank when the data are sorted from lowest to highest. An example of a type of investigation that might use ranked data is an animal behaviour investigation. An investigator might be interested in monitoring dominant behaviours in a group of 10 monkeys. The frequency of dominant behaviours are recorded and this can be used to rank the relative dominance of the monkeys from most to least.
The type of variable being investigated has consequences for any graphical display or statistical test that may be used.
Let's review Variables and Data in this 3 min video.
Let's review Variables and Data in this 3 min video.
Go to SCHOLAR to read more about ranked data in section "2.6 Presentation of data".
Simple versus multi-factorial experiments
A simple experiment involves measuring the effect of one independent variable on a dependent variable, e.g. measuring the effect of temperature on enzyme activity. This type of experiment has the advantage of being easier to conduct and easier to control with respect to laboratory conditions. This is important when trying to draw valid conclusions. However, a drawback of these simple investigation is that its findings may not be applicable to a wider setting.
This image was taken of one of my pupil's investigations into potential antibacterial properties of lavender oil. An example of a "simple experiment", although it didn't feel like it at the time!
Task 4
Task 4
Once upon a time, Dr McRobbie had another job, working in a parasitology lab. Her colleagues were involved in the development of drugs designed to act upon the parasite that causes malaria. Ultimately, these researchers were aiming to develop a drug that effectively eliminated the parasite from humans. However, to achieve this, many simple experiments had to be carried out within test tubes in the lab, e.g. investigating how particular metabolic enzymes work in the parasite and to establish if they could be a drug target. Why might the findings of these simple experiments not be "applicable to a wider setting"?
Suggested answers are available here.
Controlling confounding variables during fieldwork is much more challenging, e.g. imagine you were investigating how seasonal variations affect beaver foraging behaviour. How can you be absolutely sure that any changes in beaver foraging behaviour were solely the result of seasonal variations?
In contrast to a simple experiment, a multifactorial experiment involves a combination of more than one independent variable. This complex type of investigation is common when investigating the effect of multiple drugs on human physiology, e.g. many forms of cancer have been shown to respond more effectively to combined therapies/polytherapy. It is much more appropriate to understand the physiological outcome on a patient under these polytherapeutic conditions rather than changing one drug at a time.
Another example of a multifactorial experiment might be in social health experiments where a researcher might be interested in the effect of age and gender on the incidence of a particular health condition, e.g. diabetes.
Image shared from a former pupil's AH investigation into seasonal variations of beaver foraging. This image shows a tree felled by a beaver, with teeth marks visible.
Observational Studies
For other research interests, some researchers must use groups that already exist - and in this regard, no truly independent variable exists since the investigator cannot manipulate it (usually for ethical or logical reasons). An example of such a study would be attempting to investigate a link between playing violent video games and being violent/aggressive in real life. The researchers cannot ask a group of people to play excessive amounts of violent video games in case there is as association - this would be unethical! So they use pre-existing groups of people in society.
Observational studies are good at detecting correlation - this is an association or relationship between 2 variables. However observational studies are less useful for determining causation. Causation can only exist if the changes in the value of the independent variable are known to directly cause changes to the value of the dependent variable. During observational studies, confounding variables cannot be controlled - so a change in the "dependent variable" cannot be attributed to your factor of interest (in the example above, this would be playing violent video games).
Task 5
Task 5
For each of the examples that follow, establish whether it is an example of a simple, multifactorial or observational experiment. For an added bonus point, spot the deliberate mistake.
1. Holly carried out a study involving two groups of adults; one group were very engaged in regular exercise; the second group did not take part in any exercise in an average week. Holly measured their blood pressure and concluded that regular exercise caused lower blood pressure.
2. Andra wanted to investigate the optimal laser (pulse repetition frequency, pulse energy and exposure time ) and environmental (pH, NaCl concentration and wet or dry samples) parameters that should be employed to efficiently decontaminate bacterially-infected surfaces. She found that higher pulse laser frequencies for short periods under dry, low pH and low salt environments resulted in optimal decontamination of surfaces.
3. David investigated the optimum pH of amylase activity. He established that pH7 conditions led to higher rates of starch degradation by amylase.
The answers to Task 5 can be found here.
Your teacher might now issue you with Learner Check 2 to check your learning of the Topic 3 content.
Task 6
Task 6
Use the information below to select the correct answer:
A. There is no correlation between mass of fertiliser and mass of algae.
B. There is a weak negative correlation between mass of fertiliser and mass of algae.
C. There is a strong positive correlation between mass of fertiliser and mass of algae.
Answer can be found here.
Supporting information:
A positive correlation exists when an increase in one variable is accompanied by an increase in the other variable.
A negative correlation exists when an increase in one variable is accompanied by a decrease in the other variable.
The strength of the correlation is proportional to the spread of values from the line of best fit.
Let's review Types of Experiments in this short video.
Let's review Types of Experiments in this short video.
Confounding Variables
Confounding Variables
Due to the complexities of biological systems, other variables besides the independent variable may affect the dependent variable. These confounding variables must be held constant if possible, or at least monitored so that their effect on the results can be accounted for in the analysis.
Task 7
Task 7
Olivia aimed to find the effect of enzyme type on the volume of juice extracted from apples. Pectinase, cellulase and amylase were individually incubated with apples for a period of time and the volume of juice released was measured.
Identify at least 4 confounding variables that would have to be kept constant so that they did not affect the dependent variable.
Suggested answers can be found here.
Randomised Block Design
In cases where confounding variables cannot easily be controlled, a randomised block design could be used. Randomised blocks of treatment and control groups can be distributed in such a way that the influence of any confounding variable is likely to be the same across the treatment and control groups.
It might be appropriate to apply a randomised block design to an investigation into the effect of caffeine concentration on Daphnia heart rate. Many confounding variables exist here, including size of the Daphnia. This is really tricky to control experimentally - you are usually relieved to have captured a single Daphnia in your pipette - so it would be time-consuming and stressful (for both yourself and Daphnia) if you were trying somehow to only capture those organisms of a particular size!
However, you could categorise your Daphnia stock based on relative size into 5 groups (see image below). For each block of experiments, a Daphnia from each size category could be used. This way, over your 5 repeats, any influence of size on heart rate should be approximately equivalent. Whilst you have not controlled size as a confounding variable, you have minimised its impact on the overall trend in results.
Tired of reading? Let's review Confounding variables in this important video.
Tired of reading? Let's review Confounding variables in this important video.
SQA Past Paper Question 2
SQA Past Paper Question 2
Try the question below - the answer can be found here.
Reference: SQA (2018), CfE Advanced Higher Biology examination paper, section 1, question 14 (page 8), available at https://www.sqa.org.uk/pastpapers/findpastpaper.htm?subject=Biology&level=NAH [accessed on 04.04.20]
Copyright © Scottish Qualifications Authority
Controls
Controls
Control results are used for comparison with the results of treatment groups. Negative and positive controls may be used.
A negative control provides results in the absence of a treatment.
A positive control is a treatment that is included to check that the system can detect a positive result when it occurs.
Placebos can be included as a treatment without the presence of the independent variable being investigated. Placebo effect is a measurable change in the dependent variable as a result of a patient's expectation, rather than changes in the independent variable.
Placebos can be included as a treatment without the presence of the independent variable being investigated. Placebo effect is a measurable change in the dependent variable as a result of a patient's expectation, rather than changes in the independent variable.
An experiment from our BGE courses looking at antimicrobial effects of different cleaning fluids. Here, a negative control has been included whereby the "treatment" has been replaced with water.
Go to SCHOLAR to read some good examples of Placebos and double blind experiments in section "2.3 Experimental design".
Tired of reading? Let's review Controls in this short video.
Tired of reading? Let's review Controls in this short video.
Task 8
Task 8
Two different investigations will be presented below. For each, identify suitable control(s) that should be included during the experimental design.
Investigation 1: To investigate the antimicrobial effects of lavender oil on the growth of E. coli
Investigation 2: To investigate the effect of temperature on pepsin activity.
Suggested responses can be found here.
In vivo and in vitro studies
In vivo and in vitro studies
In vitro refers to the technique of performing a given procedure in a controlled environment outside of a living organism. These types of experiments are less expensive and time-consuming when compared to in vivo experiments. However, the results often do not translate into a precise understanding of what happens in a living organism, e.g. an experiment looking at catalase activity in a test tube would reveal quite different conclusions to how catalase performs inside the human liver. Examples of in vitro experiments include:
Cells growing in culture medium
Proteins in solution
Purified organelles
In vivo refers to experimentation using a whole, living organisms. While expensive and more time-consuming than in vitro experiments, working on a whole, live organism is a more precise approach that accurately represents the in vivo situation.
The link below, in the pink box, takes a look at the role of animal testing. It looks at the role of in vitro verus in vivo experiments and also gives us a chance to reflect back on the 3Rs we met during our look at Ethics.
Try this quick Quizlet to test your understanding of the Keywords used so far in Topic 3.
Your teacher might now issue you with Learner Check 3 to check your learning of the Topic 3 content.
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