Elizabeth, a Licensed Massage Therapist, has a Master's in Zoology from North Carolina State, one in GIS from Florida State University, and a Bachelor's in Biology from Eastern Michigan University. She has taught college level Physical Science and Biology.
Designing an Experiment
Before you can embark on an experiment, you need to design it. There's a lot of planning that goes into experimental design:
- During what time of year will it occur?
- What time of day?
- How long will you collect data for?
- How often will you collect measurements and other data?
- Who will be the one collecting those data?
You should spend as much time as necessary planning all of the details of your experiment, because the better you plan, the better your experiment will go. The when, where and who are all very important components of your plan, but just as important is the how and what. This includes the type of instruments you'll be using during the experiment, as well as the types of analyses you'll perform after your experiment has ended. Just because you're done collecting data doesn't mean you're done using it!
Choosing the Right Tools
It sounds pretty straightforward, but deciding which tools and equipment can be one of the most challenging parts of designing an experiment. For example, if you want to measure the length of something, do you use a standard ruler, a meter stick or a measuring tape? Which units are you going to measure with? You have lots of choices - centimeters, inches, meters, etc. It all depends on what you're measuring and what you're going to do with those measurements afterward.
Typically, scientific publications prefer metric measurements because these are the standard units of measure. So, if you initially measure in inches, you'll have to do a lot of converting to get your data into metric, but you'll also lose some accuracy because of rounding errors. So, knowing ahead of time that you'll use standard metric units will save you a lot of time and energy down the line!
But there are also lots of different size units to use. If you're a fisheries biologist measuring small juvenile fish, you may want to go with millimeters. But using millimeters for measuring adult sharks is silly, because they are so much larger, so you'll need to use something larger.
Perhaps your experiment is a little more qualitative, and you're trying to observe the movement of hummingbird wings as they hover near a flower. How can you go about doing this? You'll probably need a high-speed video camera and a tripod to put it on. But there are many different video recording speeds and a plethora of different cameras to choose from. Selecting the right camera is critical because it needs to be able to record fast enough but also provide you with clear video so you can see those wings in action.
Even working in the lab takes preparation and thought. If you're mixing and measuring chemicals, what type of containers will you need? Can you use beakers or should you use flasks? What size and shape will best suit your needs? What if you're working with tissue samples from human subjects? You'll need to ensure you have even 'basic' equipment - petri dishes, gloves, pipettes, tweezers, etc. You may also need to work under a ventilation hood if what you're working with is dangerous to inhale.
Analyzing the Data
After you've collected your data, you'll need to analyze them to get an idea of what those data mean. The actual analysis comes after the data collection, but you should have some idea of how you're going to work with your data before you even begin your experiment. This is because how you collect your data influences the types of analyses you can perform.
For example, ANOVA, or analysis of variance, tests the difference in the means of different groups. But a chi-square analysis compares experimental data to the results we expect to get. Which is best for you? It all depends on your experimental question and data collection techniques.
Not all data analysis requires statistical tests, but will still require some forethought. Think back to your hummingbird flight experiment. You can record video of hummingbirds all day long, but if you don't have the proper software to watch those videos, your data are useless. Knowing ahead of time what speed you're recording at and what analysis tools you'll need to go through those videos frame by frame will need to be determined ahead of time if you want to get anything meaningful from your experiment.
Sometimes successful analysis hinges on something as simple as using the right computer program for storing your data. Spreadsheets are common because you can work with many different types of data and manipulate, sort and visually display them in a number of ways. But if you have very large data sets, those spreadsheets may not be adequate. You may decide you want something that more quickly queries and organizes your data or a program where you can write your own code to run models and examine patterns. Again, it all depends on what data you have and how you want to use them.
The old saying 'an ounce of prevention is worth a pound of cure' really rings true for scientific experiments. Planning ahead will save you time, money and frustration. Spending as much time as possible planning out your experimental details will help ensure that your experiment goes right and that the data you collect are useful and meaningful.
This includes the tools, equipment and analysis you will use during and after your experiment. You'll need to decide which units, measuring tools and containers will be most appropriate for collecting your data. But even after data collection occurs, you'll need to determine what types of analyses best fit your data. Statistical tests, software and models come in all shapes and sizes, and the types of data you have and how you collect them will influence how you examine and find meaning in your experimental data.
After you've reviewed this lesson, you are ready to:
- Identify the importance of planning your experimental details
- Describe the factors you should consider when planning your tools, equipment and analysis for your scientific experiment
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