Understanding Confounding in Experiments

What is the primary difference between an observational study and an experiment?

• Observational studies are based on observations without interventions.

• Experiments are based on surveys and polls.

• Experiments do not involve any treatments.

• Observational studies involve applying treatments.

Which of the following is an example of an experiment?

• Measuring the height and weight of gym members.

• Surveying people about their favorite food.

• Testing a new laundry detergent by using it.

• Observing traffic patterns in a city.

In the context of experiments, what is a 'treatment'?

• A factor applied to subjects to observe effects.

• A method of collecting observational data.

• A survey conducted on a sample.

• A statistical analysis technique.

Why is it important to isolate the treatment in an experiment?

• To make the experiment more complex.

• To reduce the cost of the experiment.

• To increase the sample size of the study.

• To ensure the treatment is the only variable affecting the outcome.

What is confounding in the context of experiments?

• A scenario where multiple factors make it unclear which caused the effect.

• A situation where the treatment is clearly identified.

• A study that uses only observational data.

• An experiment with a large sample size.

Which of the following is an example of confounding?

• A study where only one variable is tested.

• A company claims a gas additive improves mileage, but drivers also change driving habits.

• A survey conducted without any interventions.

• An experiment with a clear and isolated treatment.

What can be a downfall of many experiments if not properly addressed?

• Large sample sizes.

• Confounding variables.

• Clear treatment isolation.

• Simple experimental design.

What will the next lesson focus on to help reduce confounding?

• Reducing the sample size.

• Conducting more surveys.

• Using control groups.

• Increasing the number of treatments.