Understanding Experiments and Observational Studies

What is a key difference between causation and association?

• Causation implies a direct effect, while association does not.

• Neither implies a direct effect.

• Association implies a direct effect, while causation does not.

• Both imply a direct effect.

What is a lurking variable?

• A variable that is always constant.

• A variable that is irrelevant to the study.

• A variable that is hidden and affects the relationship between variables.

• A variable that is directly measured.

How does an experiment differ from an observational study?

• Observational studies are more reliable than experiments.

• Experiments involve observation only.

• Experiments involve applying treatments to provoke responses.

• Observational studies involve applying treatments.

What is an experimental unit?

• Anything the experiment is performed on.

• A condition applied to a subject.

• A hidden variable affecting the study.

• A variable being measured.

What is a factor in an experiment?

• The response variable being measured.

• The hidden variable affecting results.

• The outcome of the study.

• The explanatory variable causing change.

In the example experiment, what is the response variable?

• Level of oral health

• Brand of toothpaste

• Number of individuals

• Brushing time

How many treatments are there in the example experiment?

• Two

• Three

• Six

• Nine

What is the purpose of randomization in an experiment?

• To reduce the number of subjects needed

• To increase bias

• To ensure all subjects receive the same treatment

• To prevent biased results

Why is repetition important in experiments?

• To decrease the number of treatments

• To apply different treatments to the same subject

• To reduce variation and ensure consistency

• To increase variation in results

What does control in an experiment help to achieve?

• It eliminates the need for randomization.

• It ensures all variables are hidden.

• It increases the number of variables.

• It compares treatments to control lurking variables.