AP Bio - Scientific Method

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Experimental Design, and Null Hypothesis

Last updated 7:47 PM on 3/6/25
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16 Terms

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Independent Variable

The varianle that is being tested.

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Dependent Variable

The measured outcome resulting from the Independent Variable.

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A properly designed experiment is also known as…

A controlled experiment

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What do controlled experiments do?

They allow us to test only one thing, which is the Independent Variable.

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Difference between Control Group vs Experimental Group

  • Control Group = DOESN’T include the Independent variable

  • Experimental Group = INCLUDES the Independent Variable

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What is the purpose of an experiment?

To determine if there’s a significant difference between the results in the Control and Experimental group.

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When a difference between the Control and Experimental group is present…

There is a CORRELATION between the presence of the Independent Variable and an observed outcome.

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Controlled Variables

Variables that remain the same in the experiment.

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Why are controlled variables important?

They ensure that the only difference observed between the Control and Expeirmental group is the Independent Variable, rather than another variable.

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Scientists want to measure whether exposure to second-hand smoke causes cancer in mice. They exposed one group of mice to a cage with filtered air, and the other group of mice to a cage with environmental tobacco smoke. What is an example of a Controlled Variable in this experiment?

The temperature of the cages that each group of mice were put into.

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Hypothesis

A testable explanation for a set of observations and data.

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Null hypothesis

A hypothesis stating that the Independent Variable has no impact on the Dependent Variable.

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When should you accept the Null Hypothesis?

When X2 < critical value, or when the error bars overlap (no statistical difference).

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Chisquare equation

X² = ∑ (((observed - expected)²) ÷ expected)

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Alternative Hypothesis

A hypothesis stating that the Independent Variable does have ean impact on the Dependent Variable.

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When should you accept the Alternative Hypothesis and reject the Null Hypothesis?

When X² > critical value OR when the error bars DON’T overlap (statistical difference is present).

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