1. A question may be investigated through experimentation. 2. A good scientific experiment is designed to provide evidence for cause/effect relationships.

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Presentation transcript:

1. A question may be investigated through experimentation. 2. A good scientific experiment is designed to provide evidence for cause/effect relationships. 3. A good scientific experiment also provides quantitative data that helps lead to some sort of repeatable conclusion.

4. An experiment is basically a comparison of two situations. 5. One of the situations is left constant, while one factor of the other situation is changed in order to test the effect of that specific change.

6. It is important to test the effect of changing only one variable in order to get accurate results. 7. If only one variable is changed and all the other factors are kept the same then we say that it is a controlled experiment. (one cause produces the effect) 8. Uncontrolled conditions can lead to inaccurate results.

9. There are three types of factors that may affect an experiment. These factors are called variables. a. The factor that is purposely changed by the experimenter is called the independent variable (the cause) b. The factor that changes in response to the independent variable is called the dependent variable (the results or effect that you are looking for) c. The rest of the factors that the scientists keep the same in the experiment are called the controlled variables.

10. During the experimentation, quantitative data should be collected. 11. This quantitative data will then be analyzed for possible cause/effect relationships, trends, or any other useful information about the phenomena being investigated. (This is where graphing comes into play!)

12. Once the data is analyzed there may be enough evidence to form some type of conclusion. 13. Often times a conclusion will prove our initial hypothesis incorrect, which leads to a new, refined question…and the scientific process continues.

a. Faulty experimental design (uncontrolled) b. Incorrect interpretation of data c. Using evidence Incorrectly d. Human Bias e. Human Error f. Small sample size g. others???