Biology for Kids: Investigative Skills and Experimental Design
Investigating Biology and Designing Experiments
In this article we will look at the basic investigative skills needed by biologists to design good experiments.
By the time you've finished this article, you should be able to:
- understand the core principles of experimental design as they apply in biological contexts
- be capable of applying this knowledge to new biological investigations
- know and understand the key technical terms relating to experimental design
There's a quick quiz at the end so you can test your knowledge and understanding.
What is a Biological Investigation?
In biology, the term investigation means an experiment or practical work undertaken to find something out about living organisms.
However, investigations can be good or bad depending on how well thought out the design of the experiment is. In this article we are examining the core components of good experimental design.
Hypothesis and Prediction
Most good investigations are inspired by certain observations which lead to questions and ideas which might explain what is happening.
An idea that might explain the observations is known in science as a hypothesis.
But a hypothesis isn't just a wild guess. It is always based on applying relevant scientific knowledge to an observable phenomenon. So, if you were investigating the diffusion of a substance through water and you observed that diffusion occurred faster in warm water and slower in cold water, you might suggest the following hypothesis:
"Diffusion of the substance occurs faster in warm water because particles move faster at higher temperatures."
A good hypothesis can make predictions about what will happen in a set of circumstances. For example, if the substance you were investigating was black ink diffusing through water, you might use the above hypothesis to predict that:
"At higher temperatures, the ink will diffuse faster and so it will take less time for all the water to change color."
A prediction leads to an experiment which can then verify or disprove the hypothesis by a practical procedure.
Test Your Understanding: Formulate a Hypothesis and Make a Prediction
Over the last several years, more people suffer from skin cancer in the USA than ever. Can you think of a hypothesis which might explain this fact? Based on the hypothesis you came up with before, can you come up with a prediction which you could use to test it?
Once you have a hypothesis and a prediction, you need to plan a practical experiment to test your ideas. The way you do your experiment is called the method.
Your method will include the materials you need to conduct your experiment, what you do with them, and how you measure and record results.
The materials and equipment used to carry out your experiment are the apparatus. You must plan everything you need and write it down to make sure the experiment runs smoothly.
In a laboratory your apparatus might include glassware such as test tubes, flasks, beakers, thermometers, and so on. In a field experiment, you might need binoculars, notebooks, a compass, sample containers, measuring tools, and a map.
Your apparatus doesn't have to be "scientific". Anything you use, your cell phone, say, or a pencil, is part of your apparatus.
Risk Assessment and Safety
Practical experiments often involve an element of risk to safety. It's an important part of scientific method to assess any potential hazards and consider how to minimize the risks to yourself and others. This process is a risk assessment.
In a laboratory experiment you might identify harmful chemicals, flammable materials, or the risk of airborne bacterial contamination, for example. You might then decide it's important to add protective clothing, a fire extinguisher, and a face mask to your apparatus.
In a field experiment, you might identify uneven ground, poisonous snake bites, and getting lost as potential risks. A long stick, good walking boots, leg-protectors, an antidote, and a portable GPS device might help safeguard against those risks.
Your risk assessment should be thorough and always be written for reference.
Test Your Understanding: Method, Apparatus, Risk Assessment
Think about the hypothesis and prediction you made earlier about skin cancer. See if you can come up with a method for testing your prediction. Then list the apparatus you would need and write up a risk assessment of your proposed experiment.
Any factors or conditions which might change during your experiment are variables. In a laboratory experiment, variables might be the temperature, light intensity, humidity, or time, for example. In a field experiment, variables might include the weather, other people, time of day, or the season among other possibilities.
Whether your experiment is in a laboratory or in the field, you will always have one variable you change so you can see and measure the effect changing it has on the subject of your experiment. This variable, the one you change, is the independent variable.
The subject of your study is the dependent variable. It's called that because you want to understand what happens to it when you change the independent variable.
All variables are categoric variables or continuous variables. Any variable that belongs in a category and can be labeled with a word description is a categoric variable. For example, the color of a substance ("blue liquid"). Any variable which exists on a scale and is best described in numbers is a continuous variable. For example, temperature, length, speed, and time.
Sometimes continuous variables can be mistaken for categoric variables if the numeric measurement is implied or relative and described in words. So while no numbers are specified in the variable "higher temperature", for example, or "faster runner", they are still continuous variables as they imply a numeric measurement along a scale rather than a fixed category.
Is Your Experiment Valid?
Whatever your experimental design, you must make sure that the results will be valid.
Besides the dependent and independent variables there may be many other factors which could change the outcome of your experiment. To avoid unwanted effects, you must keep the other factors constant. This is the only way to be certain that the changes you see in your dependent variable are caused by changes you make in your independent variable.
When you keep all the other variables constant, you can say your experiment is a fair test.
Other variables you keep constant are control variables. If you can’t control certain variables, they are uncontrolled variables.
To make sure a test is valid you must eliminate all the uncontrolled variables. This is easier to achieve in laboratory experiments and much harder in field experiments.
Test Your Understanding: Variables and Validity
Now think about the hypothesis, predication and experiment you've worked out for the observation about skin cancer in the USA.
Imagine your experiment aims to investigate the effect of time spent sunbathing on the diagnosis of skin cancer. Now answer the following questions:
1. Can you name the dependent and independent variables?
2. What other variables are there besides exposure time?
3. How could you control these variables to make your experiment valid?
Reliability of Experiments
After finishing an investigation, it's important to check that you got the right answer to your experimental question. You need to know your results are reliable. The scientific method for checking the results of an experiment is to repeat the readings several times. This is doing replicates.
When carrying out experiments, it's easy to make mistakes. Replicating your results helps guard against human error. You might misread an instrument such as a thermometer or a stopwatch, for example. In biology you may see an organism behaving abnormally and not know it. If you only take a measurement, or carry out a procedure, once, you may not spot the abnormality. But if you repeat your measurements, any problems will be easy to spot.
As an example, imagine you have taken readings and got the following results:
24.2, 23.5, 56.4, 24.5, 22.8, 24.0
You can see the third measurement is unusual. Such a reading is an anomalous result. It's an exception to the pattern of the other results. If you get an anomalous result, you should either repeat the measurement, or ignore the result when analyzing your data.
Replicating results also allows you to calculate an average which in many cases gives a more reliable answer than any single reading from a range.
Experimental Design: Accuracy and Precision
Don't confuse accuracy and precision.
An accurate measurement is close to the true value. A precise measurement is stated to several decimal places but may be wrong.
Here's an example. Let's say in an experiment you are timing how long it takes for an animal to run a certain distance. You time the run and check the stopwatch, noting down it took the animal 7.25 seconds. That is a very precise measurement, to one hundredth of a second.
But if your stopwatch was faulty, or you misread it, and the animal completed the run in 15 seconds, it would be inaccurate. In that case, another student who recorded a time of 8 seconds would have a less precise, but more accurate measurement.
In biology, accuracy is more important than precision.
Here's a quick summary of everything you've learned on this page:
- In biology, an experiment is an investigation to find something out about a living organism or organisms
- Observations lead to a hypothesis which predicts how the organism will behave in given circumstances
- The experimental method tests the prediction and hypothesis
- Anything used in the experiment is part of the apparatus
- For an experiment to be valid, you must control all the variables
- Measurements can be accurate, precise, or both. In biology, accuracy is more important than precision
- Replicates help make sure your results are reliable
- Dependent variable
- Continuous variable
- Control variable
- Uncontrolled variable
- Fair test
- Anomalous result
Experimental Design Quizview quiz statistics
© 2018 Amanda Littlejohn