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The Scientific Method A Quick refresher
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The Scientific Method There are many ways to go about conducting experiments. The scientific method is used differently by different scientists in different fields. These fundamentals to the left are important regardless of the experiment.
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How to begin Always start your experimental design process by asking a question. This will lead us to conducting research. As we learn more about the topic we are researching, we may find a lot of the answers we are looking for. However, this will leave us with unknowns that we must run experiments to find. In order to conduct experiments, we must first determine our Hypothesis.
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Hypothesis As we have previously learned, a hypothesis is an educated guess. A strong hypothesis is written using: “If______ and Then_____” statements. As we near the end of an experiment, it may be necessary to return to our hypothesis to make alterations. Hypothesis Example: If I water plants 1 & 2 with 50% more water than I give to plants 3 & 4, Then plants 1 & 2 will grow to a greater height in less time.
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Testing our Hypothesis
Prior to testing our hypothesis, we want to plan our experiment as detailed as we can. In the real world, errors in the planning process can cost companies millions of dollars. Ex) Boeing rents a wind tunnel at NASA Langley Research Center for $5,000 per hour to test a new airplane wing prototype. If they arrive on site without properly planning for their trials, they may not be able to test the prototype at all during their visit. It is best to anticipate as many errors that we can foresee based on what we know after completing research. Ex) During their trials in the wind tunnel, the prototype wing falls apart due to incorrect screws being used. The screws used could not withstand the forces acting on the wing. This was an oversite by the designers that they could have caught. Proposed Test: I can test this Hypothesis by watering 4 plants differently.
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The Experiment Employ good reasoning when designing your experiment. This will help you alleviate error and prevent wasting time/money. For example, you should run numerous trials to ensure the results you are getting are accurate. Ex) With our plant experiment, we are watering 2 plants instead of 1 for each amount of water. Document your testing as you go. This may mean recording data, taking pictures, drawing diagrams, etc. Ex) If we take a picture of our plants each day, we will have direct evidence to prove or disprove our hypothesis. Plan out any tools that you will need during testing. Ex) We will need flower pots, a water source, a source of light, a way to measure the plants, etc.
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Analyzing Your Results
Now that you have all of your data, it’s time to see if your results supported your hypothesis. Results are often not as obvious as you may expect. More often than not, our Hypothesis is not fully supported. At this point, you can return to your hypothesis and rework it. You may also return to your experimental design to change the way you are testing your hypothesis. Ex) We observed that all of our plants grew the same amount even though we watered them with different amounts of water. We can revisit our hypothesis and/or experimental design.
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Communicate Your Results
When communicating your results, it’s very important to describe your findings in a way that everyone can understand. Ideally you would have given enough background information previously so that the reader or viewer is up to speed with your experiment and your terminology. Ex) If you name plants used and different types of liquid compounds that you watered your plants with, this should not be the first time the viewer is hearing of these terms. Discuss what parts of your experiment supported your hypothesis. Discuss what parts of your experiment failed and why. Discuss ways that you could change your experiment in future trails.
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Real Car Vs. Toy Car Drag Race
Today we are going to design our own experiment. A real car and a toy car race downhill for ¼ mile, which will win? We will utilize the Scientific Method and propose our THEORETICAL conclusion as we are not running a full-size test.
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