Remember, doing science is all about not fooling yourself and each data point you plot on your graph represents one trail. (A trail is a mini-experiment within your whole experiment to pin down one value of whatever you are testing [the dependent variable] against one value of whatever quantity you are changing in your experiment [the independent variable].) That's why scientists pull together all the trials they have done in their science experiment and plot them on a graph. Graphs allow you to see at a glance exactly how the dependent variable is affected the independent variable. (For example, growth rate vs. concentration of fertilizer.) Graphs paint a clear picture that is easy for anyone to understand. And that is exactly why they are used so frequently in science.
So one of the basic questions you must answer in order to design your science experiment is this: Just how many trails will you need to answer your experimental question? This advice should guide you.
Rule of Thumb #1: In general, for most experiments in which you are studying how one variable depends on another, you should conduct as many trails as you reasonably can. Of course, you want to change the independent variable enough to cause a measurable change in the dependent variable, but beyond that it's good to get as much data as you can to the limits of your time, money, materials and patients. Your patients is a very think for you to keep in mind. Whatever you do, don't set out to conduct so many trails that you overwhelm yourself with work. That's a good way to destroy your interest in your science project, and nobody wants that!
Rule of Thumb #2: Spread your measurements out evenly between the smallest value of the independent variable, and the largest value you are testing. For example, if your independent variable starts at zero and goes to say 100 units, you might select the values 0, 20, 40, 60, 80, and 100 to test. This strategy provides the best way to establish the relationship between the independent and dependent variables over the range of values you are studying in your experiment.
Rule of Thumb #3: Whatever you do, make sure you conduct at least 5 trails. This should not only be able to establish whether or not the dependent variable changes in some regular fashion with the independent variable, it should also let you see if the data fall along a straight line or a curve.
Dr. Shawn
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