Using Appropriate Tools for Scientific Tests & Data Collection

Lesson Transcript
Instructor: Elizabeth Friedl

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.

Careful planning is a critical first step in the process of designing an experiment. Learn how to design an experiment, choose the correct tools, and analyze data so you can properly and efficiently complete an experiment. Updated: 10/27/2021

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!

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  • 0:02 Designing an Experiment
  • 0:51 Choosing the Right Tools
  • 2:56 Analyzing the Data
  • 4:39 Lesson Summary
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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.

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