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Practices of Science: Variables

NGSS Science and Engineering Practices:

Imagine that you wanted to build a faster sailboat because you wanted to win a sailing race (SF Fig. 5.2). If you changed the length of your boat hull, the size of its sail, the shape of its sail and the shape of the bow all at the same time and your boat went faster, you would not know which of these factors impacted the speed. It would also be difficult to know how much each variable impacted the speed. One solution is to make one change at a time to find out how to maximize your boat speed.

 

<p><strong>SF Fig. 5.2.</strong> The U.S. sailing team jockeys for position and tries to find the best wind during the 6th race of the 3rd World Military Games sailing competition in Sicily, 2003.</p><br />
<p><strong>SF Fig. 5.3.</strong> Sample data showing the independent variable (boat hull length) plotted along the x-axis, and the dependent variable (maximum boat speed) plotted along the y-axis. Based on this data, as boat hull length increases, so does maximum boat speed.</p><br />


Scientists use systems of variables and controls in experiments so that they can gather the most accurate data possible. In a scientific experiment, the variable is a factor that changes. Scientists might deliberately change a specific variable to test its effect on some other part of the system. The independent variable is the variable manipulated in the experiment. The dependent variable is the factor that changes in response to the independent variable. When presenting results, the independent variable is normally plotted along the x-axis, the dependent variable is plotted along the y-axis (SF Fig. 5.3).

 

It is important when designing an experiment to eliminate additional variables, called confounding factors, as much as possible as they might confuse your results. For example, if you decided to test the effect of sailboat hull length on maximum speed, you might build eight sailboats with differing hull lengths. You do not want anything in your experiment to change other than the independent (hull length) and dependent (speed) variables, so you need to keep other factors constant throughout the experiment. If you tested each sailboat at different times of the day, the wind properties and sea conditions might change from one trial to the next, affecting the outcome of your tests. You might wrongly assume that the shortest boat tested at the beginning of the day was the fastest, but this might not have been because of hull length. Instead, the wind may have been stronger and sea calmer in the beginning of that day. To avoid confounding factors when answering your question, it would be best to test all of the boats at the same time of the day so that they each experience similar wind and wave conditions.

 

Question Set: 
  1. In your own words, describe the difference between an independent and dependent variable.
     
  2. In the maximum sailboat speed and boat hull length example, what might be some other confounding factors? How could you address them?
     
  3. Design an experiment to test the effect of sail size on maximum sailboat speed. What are some confounding factors and how would you address them?
     
  4. Scientists repeat an experiment multiple times before analyzing and reporting their data. Do you think repetition affects the influence of confounding factors in an experiment? Why or why not?

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Exploring Our Fluid Earth, a product of the Curriculum Research & Development Group (CRDG), College of Education. University of Hawaii, 2011. This document may be freely reproduced and distributed for non-profit educational purposes.