steps of the scientific method. 1. state the problem what problem are you trying to solve? normally...
TRANSCRIPT
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Steps of the Scientific Method
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1. State the Problem
• What problem are you trying to solve?
• Normally stated as a question.
• EXAMPLE: Will giving plants Brand X fertilizer every day for thirty days increase their growth?
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2. Research the Problem• The researcher should
gather as much information about the problem as possible.
• The researcher should consult scientific journals (magazines) or experts in the field. (must be reliable sources)
• EXAMPLE: Brand Z fertilizer is similar in composition to Brand X but does not contain phosphorous, and studies have demonstrated the effectiveness of Brand Z. Studies have also shown that phosphorous may increase plant growth.
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3. Form a Solution, or Hypothesis• Make an educated guess as to
what will solve the problem.
• Write the hypothesis as an “if-then” statement if possible.
• The hypothesis must be TESTABLE!
• EXAMPLE: If Brand X fertilizer is added to plants every day for 30 days, then they will grow taller than plants grown without it.
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4. Conduct an Experiment• EXAMPLE: Add Brand X fertilizer to 100 plants every day for 30
days to determine if they grow taller than plants grown without it.
• Variables are conditions that change, or vary, throughout an experiment.
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Independent Variable (I.V.)• I change the Independent
variable.
• This is the one and only variable that the experimenter changes from one group to another.
• EXAMPLE: Whether or not the plants receive Brand X fertilizer is the Independent variable because I, the experimenter, control which plants receive the fertilizer. I do not control how tall the plants grow.
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Dependent Variable (D.V.)• The response to the
independent variable.
• It is not under the experimenter’s control.
• EXAMPLE: The dependent variable is the height of the plants because it changes based upon whether or not the plants received Brand X fertilizer (I.V.) and is not under the control of the experimenter.
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Experimental Group
• The group or subject that receives the independent variable.
• EXAMPLE: The plants that receive Brand X fertilizer are in the experimental group.
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Control Group• The group or subject that does
not receive the independent variable.
• The control is used to compare data with the experimental group.
• EXAMPLE: The group that does not receive Brand X fertilizer is the control group. The height of the plants grown with Brand X fertilizer (experimental group) will be compared to the height of the plants grown without Brand X fertilizer (control group) to determine if Brand X fertilizer has an effect on plant height.
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Constants
• Constants are conditions that remain the same between the experimental and control groups in an experiment.
• To determine whether the independent variable is causing the result, all other variables must remain constant.
• EXAMPLE: To determine whether adding Brand X fertilizer is causing a difference in plant height, all plants must receive the same amount of sunlight, amount of water, type of soil, temperature, pot size, humidity, CO2, etc.
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Sample Size• Sample size refers to the number of subjects exposed
to the independent variable.
• The larger the sample size, the more valid the results.
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5. Record and Analyze the Data
• Data is typically recorded into data tables.
• Then, the data is graphed to increase understanding and visual appeal.
• EXAMPLE:
Effect of Brand X Fertilizer on Plant Height
8486889092949698
100102
Average Plant Height in cm
WithoutBrand X
WithBrand X
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6. State a Conclusion• Look at your results to
determine what they mean.
• Determine whether your hypothesis is correct.
• It is acceptable for your hypothesis to be wrong. An incorrect hypothesis can give you as much information as a correct one.
• EXAMPLE: The data suggests that adding Brand X fertilizer to plants every day for thirty days increases plant height.
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7. Repeat the work• This is the most
important step in scientific inquiry.
• If you only conduct the experiment once, your results may be written off as a “fluke”.
• Repeating the same results from different experiments lends them validity.
• Different results suggests that you should go back to the drawing board.