steps of the scientific method. 1. state the problem what problem are you trying to solve? normally...

Steps of the Scientific Method

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?

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.

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.

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.

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.

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.

Experimental Group

• The group or subject that receives the independent variable.

• EXAMPLE: The plants that receive Brand X fertilizer are in the experimental group.

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.

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.

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.

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

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.

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.