Independent and Dependent Variables in Experiments

The video tutorial reviews the nature of science, focusing on key concepts such as observations, inferences, predictions, and hypotheses. It explains the differences between these terms and how they apply to scientific experiments. The tutorial also covers the types of variables in experiments—independent, dependent, and controlled—and provides tips for designing reliable experiments, emphasizing the importance of sample size and repeatability.

Which of the following is an example of an observation?

• The tree is three feet tall.

• The tree uses light for photosynthesis.

• The tree is tall because it is near the light.

• The tree will grow better with more light.

What is an inference?

• A direct measurement using the senses.

• A statement about future events.

• An explanation that can be tested.

• A guess based on prior knowledge.

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Which statement is a prediction?

• Plants use light to power photosynthesis.

• If I plant a tree in more light, it will grow better.

• The tree is tall because it is near the light.

• The tree is three feet tall.

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What distinguishes a hypothesis from a prediction?

• A hypothesis is a guess based on prior knowledge.

• A hypothesis is a statement about future events.

• A hypothesis includes an explanation that can be tested.

• A hypothesis is a direct observation.

In an experiment, what is the independent variable?

• The factor that is measured.

• The factor that is kept the same.

• The factor that is observed.

• The factor that is changed by the researcher.

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What is the dependent variable in an experiment?

• The factor that is observed.

• The factor that is measured.

• The factor that is changed by the researcher.

• The factor that is kept the same.

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Which of the following is a controlled variable?

• The height of the plants.

• The amount of light each plant receives.

• The type of plant used.

• The distance of the plants from the light.

Why is it important to have a large sample size in an experiment?

• To ensure the experiment is quick.

• To reduce the number of variables.

• To increase the reliability and accuracy of the data.

• To make the experiment more complex.

What is the benefit of repeating an experiment multiple times?

• To use up all the available resources.

• To ensure the results are consistent and reliable.

• To test different hypotheses.

• To make the experiment more interesting.

What should be kept constant in an experiment to ensure valid results?

• The dependent variable.

• All factors except the one being tested.

• The independent variable.

• The hypothesis.

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